Wireless charger and high speed data off-loader

Information

  • Patent Grant
  • 10447347
  • Patent Number
    10,447,347
  • Date Filed
    Monday, August 14, 2017
    6 years ago
  • Date Issued
    Tuesday, October 15, 2019
    4 years ago
Abstract
A wireless charging system for a wearable sensor device can include a wireless charging device and a user device. The wireless charging device can include a transmitter for sending a power signal to charge the wearable sensor device, a first receiver to receive a data signal and a second to receive a low energy signal. The wearable sensor device can include at least one memory for storing sensor data, a first receiver for receiving the power signal from the wireless charging device, a first transmitter to transmit a data signal and a second receive to receive a low energy signal. The user device can include a low energy transmitter for communicating with the wireless charging device and sensor device to control the charging function and the data communication function of the wireless charging device to selectively charge and transfer data with wearable sensor device.
Description
TECHNICAL FIELD

The present disclosure relates generally to sensors. More particularly, aspects of this disclosure relate to sensors wearable on a body, such as a human body.


BACKGROUND

Integrated circuits (ICs) are the cornerstone of the information age and the foundation of today's information technology industries. The integrated circuit, a.k.a. “chip” or “microchip,” is a set of interconnected electronic components, such as transistors, capacitors, and resistors, which are etched or imprinted onto a semiconducting material, such as silicon or germanium. Integrated circuits take on various forms including, as some non-limiting examples, microprocessors, amplifiers, Flash memories, application specific integrated circuits (ASICs), static random access memories (SRAMs), digital signal processors (DSPs), dynamic random access memories (DRAMs), erasable programmable read only memories (EPROMs), and programmable logic. Integrated circuits are used in innumerable products, including computers (e.g., personal, laptop and tablet computers), smartphones, flat-screen televisions, medical instruments, telecommunication and networking equipment, airplanes, watercraft and automobiles.


Advances in integrated circuit technology and microchip manufacturing have led to a steady decrease in chip size and an increase in circuit density and circuit performance. The scale of semiconductor integration has advanced to the point where a single semiconductor chip can hold tens of millions to over a billion devices in a space smaller than a U.S. penny. Moreover, the width of each conducting line in a modern microchip can be made as small as a fraction of a nanometer. The operating speed and overall performance of a semiconductor chip (e.g., clock speed and signal net switching speeds) has concomitantly increased with the level of integration. To keep pace with increases in on-chip circuit switching frequency and circuit density, semiconductor packages currently offer higher pin counts, lower power consumption, greater power dissipation, more protection, and higher speeds than packages of just a few years ago.


The advances in integrated circuits have led to related advances within other fields. One such field is sensors. Advances in integrated circuits have allowed sensors to become smaller and more efficient, while simultaneously becoming more capable of performing complex operations. Other advances in the field of sensors and circuitry in general have led to wearable circuitry, a.k.a. “wearable devices” or “wearable systems.” Within the medical field, as an example, wearable devices have given rise to new methods of acquiring, analyzing, and diagnosing medical issues with patients, by having the patient wear a sensor that monitors specific characteristics. Related to the medical field, other wearable devices have been created within the sports and recreational fields for the purpose of monitoring physical activity and fitness. For example, a user may don a wearable device, such as a wearable running coach, to measure the distance traveled during an activity (e.g., running, walking, etc.), and measure the kinematics of the user's motion during the activity.


However, current wearable devices rely on a battery for power. Such devices are therefore limited by the lifespan of the battery as such batteries cannot be easily replaced or recharged. It is also desirable to download data from such devices for further analysis. However, data must be transferred by existing wireless protocols that require a long period of time to transmit large amounts of data. Typically rates of data transmission are kept low in order to conserve device energy, a tradeoff to avoid losing data when the battery runs out of power. For example, performing bulk data downloads using the current Bluetooth Low Energy transmission protocols can be very slow (e.g., approximately 2 kBytes/s-5 kBytes/s). To download 32 MBytes of data, it would take as long as 4.44 hours.


Thus there is need for a system that allows rapid remote recharging of a wearable sensor device. There is also a need for a system that allows rapid download of data from the wearable sensor device. There is also a need to control the downloading of data and charging of these wearable devices.


SUMMARY

According to some embodiments, a wireless control system for wireless charging and data off-loading is disclosed. The wireless control system can include a wireless charging device having a transmitter to transmit a charging signal, a first receiver to receive a data signal and a second receiver to receive a low energy signal. The system can include a sensor device having a memory for storing sensed data, a first receiver to receive a charging signal, a transmitter to transmit a data signal, and a second receiver to receive a low energy signal. The system can include a user device having a transmitter in communication with the second receiver of the wireless charging device and the second receiver of the sensor device. The user device is operative to initiate a data transfer from the sensor device to the wireless charging device.


Another example is a method of transmitting data from a sensor device to a wireless charging device. The sensor device can include a memory for storing sensed data, a first receiver to receive a charging signal, a transmitter to transmit a data signal, and a second receiver to receive a low energy signal. The charging device can include a transmitter to transmit a charging signal, a first receiver to receive a data signal and a second receiver to receive a low energy signal. Sensed data is stored in the memory of the sensor device. Communication is initiated between a user device and the wireless charging device via a transmitter on the user device. Communication is initiated between the user device and the charging device via the transmitter on the user device. Data transfer is initiated between the sensor device and the charging device via the transmitter of the sensor device based on authorization from the user device.


The above summary is not intended to represent each embodiment or every aspect of the present disclosure. Rather, the foregoing summary merely provides an exemplification of some of the novel aspects and features set forth herein. The above features and advantages, and other features and advantages of the present disclosure, will be readily apparent from the following detailed description of representative embodiments and modes for carrying out the present invention when taken in connection with the accompanying drawings and the appended claims.





BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure will be better understood from the following description of exemplary embodiments together with reference to the accompanying drawings, in which:



FIG. 1 is a block diagram of a system of implantable devices being in communication with a charger and data downloader;



FIG. 2 illustrates an example sensor device in FIG. 1 that is a wearable device;



FIG. 3 is a block diagram of a charging device circuit facilitating wireless charging;



FIG. 4 is a block diagram of the charging device in FIG. 1;



FIG. 5 is a flow diagram for the communication of the smart device, charger and implantable device; and



FIG. 6 is a flow diagram for the prioritization of charging and transferring data from multiple devices.





The present disclosure is susceptible to various modifications and alternative forms, and some representative embodiments have been shown by way of example in the drawings and will be described in detail herein. It should be understood, however, that the invention is not intended to be limited to the particular forms disclosed. Rather, the disclosure is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.


DETAILED DESCRIPTION OF THE ILLUSTRATED EMBODIMENTS

This disclosure is susceptible of embodiment in many different forms. There are shown in the drawings, and will herein be described in detail, representative embodiments with the understanding that the present disclosure is to be considered as an exemplification of the principles of the present disclosure and is not intended to limit the broad aspects of the disclosure to the embodiments illustrated. To that extent, elements and limitations that are disclosed, for example, in the Abstract, Summary, and Detailed Description sections, but not explicitly set forth in the claims, should not be incorporated into the claims, singly or collectively, by implication, inference, or otherwise. For purposes of the present detailed description, unless specifically disclaimed: the singular includes the plural and vice versa; and the word “including” means “including without limitation.” Moreover, words of approximation, such as “about,” “almost,” “substantially,” “approximately,” and the like, can be used herein in the sense of “at, near, or nearly at,” or “within 3-5% of,” or “within acceptable manufacturing tolerances,” or any logical combination thereof, for example.



FIG. 1 shows a system 100 that includes a smart user device 110 that allows control of wireless charging and data transfer from sensor devices such as different wearable devices 112, 114, 116 and 118. The user device 110 may be a smart phone, a personal digital assistant, a laptop or desktop computer, a tablet computer or similar device such as an iPhone or iPad (from Apple, Inc., Cupertino, Calif.), an Android based device (Nexus, Google, Inc., Mountain View, Ca). The wearable sensing devices 112, 114, 116 and 118 can be worn on (or implanted in) the body of a user and include sensors to monitor a user's biological functions and generate information (e.g., sensor data or information derived from sensor data) about the user's biological functions. The wearable devices can also include a processor and associated memory to generate and/or store the user information and other information, such as, programs, commands, instructions, configuration information, status, and sensor data. The wearable devices can also include a first receiver to receive a charging signal, a first transmitter to transmit a data signal, and a second receiver to receive a low energy signal. One example of a wearable device 112, 114, 116, 118 includes the BioStamp RC device available from MC10 Inc. (Lexington, Mass.). As will be explained below, the wearable devices 112, 114, 116 and 118 can each include a power source such as a battery or a capacitor that can be wirelessly recharged. Further, each of the wearable devices 112, 114, 116 and 118 includes one or more transceivers to enable the device to send and receive information, such as, programs, commands, instructions, configuration information, status, and sensor data. The wearable devices can include more than one transceiver each having a transmitter and receiver and each configured to operate on a different frequency and/or use a different communication protocol. Alternatively, the wearable device can include one transceiver that can operate in two or more modes of operation. For example, a first low energy transceiver can be used to conserve power while enabling the device to send and receive commands and status or data at low data rates while a second higher rate higher energy transceiver may be used when ample power is available to transmit data at higher data rates, such as for bulk data offloading.


The wearable devices 112, 114, 116 and 118 can be moved in proximity to a wireless charging device 120 in order to recharge the power sources of the respective wearable devices and transmit collected data from the wearable devices to a remote computer system (e.g., a cloud server) for storage and analysis. The wireless charging device 120 can simultaneously charge one or more of the wearable devices 112, 114, 116 and 118 at different charging rates as well as transfer data between one or more of the wearable devices 112, 114, 116 and 118 and a remote computer system (e.g., at different transmission rates). The wireless charging device 120 can include a transmitter to transmit a charging signal, a first receiver to receive a data signal and a second receiver to receive a low energy signal. The charging device 120 therefore can incorporate such transmitters and receivers in more than one transceiver (e.g., a low energy transceiver and a higher transmission rate, higher energy transceiver). The user device 110 can be in wireless communication with one or more of the wearable devices 112, 114, 116 and 118 as well as the charging device 120 in order to configure, initiate and control the transfer of data between one or more of the wearable devices 112, 114, 116 and 118 and the charging device while one or more of the wearable devices 112, 114, 116 and 118 is charged (e.g., at one or more charging rates). Communications 122 and 124 between the user device 110 and the wearable devices 112, 114, 116, and 118 and the charging device 120 are generally made with a low energy protocol for the low energy transceivers (e.g., Bluetooth Low Energy (BLE)). As will be explained below, the user device 110 initiates handshaking between at least one of the devices 112, 114, 116 and 118 and the charging device 120 for purposes of establishing a communications 126 between the charging device 120 and the devices 112, 114, 116, and 118 for configuring, initiating and controlling charging and data transfer.


In this example, the initiation and transfer of this data and instructions to charge is gated by the smart user device 110 with a relatively low energy communication protocol such as BLE. The smart user device can communicate with both the charging device 120 and one or more of the wearable devices 112, 114, 116 and 118 either simultaneously or sequentially, in order to configure them in one of several data-transfer modes and one of several charging mode.


The charging device 120 can include a connection to a computer 130 that is in turn in communication with cloud server 140 or can directly communicate with the cloud server 140. The computer 130 can be wirelessly connected to the charging device 120 or may be connected via a hardware connection such as via USB connector. The computer 130 can be connected to a network such as the Internet to transmit received data for storage on the cloud server 140.



FIG. 2 shows a diagrammatic example of a wearable sensor device 200 such as the wearable device 112 in FIG. 1 in accord with aspects of the present invention. The wearable device 200 provides conformal sensing capabilities, providing mechanically transparent close contact with a surface (such as the skin or other organ of the body) to provide sensing, measurement and/or analysis of biological or physiological information. According to some embodiments, the wearable device 200 senses, measures, or otherwise quantifies the motion of at least one body part of a user upon which the wearable device 200 is located. Additionally, or in the alternative, according to some embodiments, the wearable device 200 senses, measures, or otherwise quantifies the temperature of the environment of the wearable device 200, including, for example, the skin and/or body temperature at the location that the wearable device 200 is coupled to the body of a user. Additionally, or in the alternative, according to some embodiments, the wearable device 200 senses, measures, or otherwise quantifies other characteristics and/or parameters of the body (e.g., human or animal body) and/or surface of the body, including, for example, electrical signals associated with cardiac activity (e.g., ECG), electrical signals associated with muscle activity (e.g., electromyography (EMG)), changes in electrical potential and/or impedance (e.g., sensed at specific locations of the skin, electrical signals of the brain (e.g., electroencephalogram (EEG)), bioimpedance monitoring (e.g., body-mass index, stress characterization, and sweat quantification), and optically modulated sensing (e.g., photoplethysmography and pulse-wave velocity), and the like.


The wearable device 200 described herein can be formed as a patch. The wearable device 200 can be flexible and/or stretchable, and can include conformal (e.g. stretchable and/or flexible) electronics and conformal electrodes disposed in or on a flexible and/or stretchable substrate. Alternatively, the wearable device 200 may be rigid but otherwise attachable to a user. Thus, the wearable device 200 can be any device that is wearable on a user, such as coupled to the skin of the user, to provide measurement and/or analysis of biological and/or physiological information of the user. For example, the wearable device can be adhered to the body by adhesive, held in place against the body by tape or straps, or held in place against the body by clothing.


In general, the wearable device 200 device of FIG. 2 can include a processor 201 and associated memories, including one or more memory storage module 203. The wearable device 200 further includes one or more sensors, such as an accelerometer 205 and/or a temperature sensor 213. The wearable device 200 can optionally include one or more wireless transceivers, such as transceiver 207, for communicating with other devices. In this example, one transceiver 207 can be a low energy consuming device that uses a low data transmission rate communication protocol such as Bluetooth Low Energy for transferring commands and status information and another transceiver 208 can be a higher speed communication device using a higher capability transmission protocol such as the Gazelle or Shockwave protocol of Nordic Semiconductors. The transceiver 208 can be part of a subsystem for receiving wireless charging signals (e.g., using different charging protocols, such as, Qi™, from the Wireless Power Consortium or AirFuel™ from the AirFuel Alliance). The wearable device 200 can also include a power source (e.g., battery) 209 that provides power for the components of the wearable device 100 and induction coil or other antenna (and charging circuitry) enabling the wearable device 200 to receive electrical energy to recharge the power source 209. In this example, the wearable device 200 can be configured to be recharged by drawing power from a wireless connection or an electromagnetic field (e.g., an induction coil, an NFC reader device, microwaves, and light). The antenna can also be used for transmitting and receiving communications signals. Such communication signals can serve as a communication channel to relay information including but not limited to charge status, device presence, and sensor identification


The processor 201 can be a controller that is configured to control the wearable device 200 and components thereof based on computer program code. Thus, the processor 201 can control the wearable device 200 to measure and quantify data indicative of temperature, motion and/or other physiological data, and/or analyze such data indicative of temperature, motion and/or other physiological data according to the principles described herein.


The memory storage module 203 can include one or more submodules and can be configured to save the generated sensor data (e.g., accelerometer 205 information, temperature sensor 213 information, or other biological and/or physiological information, such as ECG, EMG, etc.) or information representative of acceleration and/or temperature and/or other biological and/or physiological information derived from the sensor data. Further, according to some embodiments, the memory storage module 203 can be configured to store the computer program code that controls the processor 201. In some implementations, the memory storage module 203 can be volatile and/or non-volatile memory. For example, the memory storage module 203 can include flash memory, static memory, solid state memory, removable memory cards, or any combination thereof. In certain examples, the memory storage module 203 can be removable from the wearable device 200. In some implementations, the memory storage module 203 can be local to the wearable device 200, while in other examples the memory storage module 203 can be remote from the wearable device 200. For example, the memory storage module 203 can be internal memory of a smartphone such as the user device 110 in FIG. 1 that is in wired or wireless communication with the wearable device 200, such as through radio frequency communication protocols including, for example, WiFi, ZigBee, Bluetooth®, and near-field communication (NFC), and/or optically using, for example, infrared or non-infrared LEDs. In such an example, the wearable device 100 can optionally communicate with the smartphone via an application (e.g., program) executing on the smartphone.


In some embodiments, the generated data, including the temperature information, the acceleration information, and/or the other biological and/or physiological information (e.g., ECG, EMG, etc.), can be stored on the memory storage module 203 for processing at a later time. Thus, in some embodiments, the wearable device 200 can include more than one memory storage module 203, such as one volatile and one non-volatile memory storage module 203. In other examples, the memory storage module 203 can store the information indicative of motion (e.g., acceleration information), temperature information, physiological data, or analysis of such information indicative of motion, temperature, physiological data according to the principles described herein, such as storing historical acceleration information, historical temperature information, historical extracted features, and/or historical locations. The memory storage module 203 can also store time and/or date information about when the information was received from the sensor.


Although described as the processor 201 being configured according to computer program code, the functionality of the wearable device 200 can be implemented based on hardware, software, or firmware or a combination thereof. For example, the memory storage module 203 can include computer program code that can be retrieved and executed by the processor 201. The processor 201 executes the computer program code that implements the functionality discussed below with respect to determining the on-body status of the wearable device 200, the location of the wearable device 200 on a user, and configuring functionality of the wearable device 200. Alternatively, one or more other components of the wearable device 200 can be hardwired to perform some or all of the functionality.


The power source 209 can be any type of rechargeable power source for an electronic device, such as, but not limited to, one or more capacitors, electrochemical cells or batteries. In accordance with some embodiments of the invention, power source can include one or more photovoltaic cells configured to charge one or more capacitors, electrochemical cells and/or batteries. In accordance with some embodiments, the power source 209 can be a small battery or capacitor that stores enough energy for the device to power up and execute a predefined program sequence before running out of energy, for example, an NFC sensing device. As will be explained below, the power source 209 can be charged via a receiver coil from the charging device 120 in FIG. 1.


As discussed above, the wearable device 200 can include one or more sensors, such as the accelerometer 205, a temperature sensor 213, electrical contacts 215 (e.g., electrical contacts or electrodes), and/or an optical sensor 217. In accordance with some embodiments, one or more of the sensors, such as accelerometer 205, the optical sensor 217 and/or electrical contacts 215, can be separate components from the wearable device 200. That is, the wearable device 200 can be connected (by wire or wirelessly) to each sensor (e.g., accelerometer 205, temperature sensor 213, electrical contacts 215, and optical sensor 217). This enables the wearable device 200 to sense conditions at one or more locations that are remote from the wearable device 200. In accordance with some embodiments, the wearable device 200 can include one or more integral sensors in addition to one or more remote sensors.


The accelerometer 205 can be configured to measure and/or generate acceleration information indicative of a motion and/or acceleration of the wearable device 200, including information indicative of a user wearing, and/or body parts of the user wearing, the wearable device 200. In accordance with one embodiment, the accelerometer 205 within the wearable device 200 can include a 3-axis accelerometer that generates acceleration information with respect to the x-axis, the y-axis, and the z-axis of the accelerometer based on the acceleration experienced by the wearable device 200. Alternatively, the wearable device 200 can include three independent accelerometers (not shown for illustrative convenience) that each generate acceleration information with respect to a single axis, such as the x-axis, the y-axis, or the z-axis of the wearable device 200. Alternatively, the wearable device 200 can include an inertial measurement unit (IMU) that measures the velocity, the orientation, and the acceleration using a combination of one or more accelerometers, gyroscopes, and magnetometers. Thus, although generally referred to herein as an accelerometer 205, the accelerometer 205 can be any motion sensing element or combination of elements that provides acceleration information.


According to some embodiments, the accelerometer 205 includes a detection range of ±4 times the force of gravity (Gs). However, other accelerometers having a detection range between ±2 Gs or less and ±10 Gs or more can be used. Further, the accelerometer 205 can have a sampling rate of 50 hertz (Hz) such that each second the accelerometer 205 generates 150 points of acceleration information, or 50 points within each axis. However, the sampling rate can vary, such as being 20 Hz to 100 Hz depending of the mode or attribute being monitored.


According to some embodiments, one or more sensors of the wearable device 200, such as the accelerometer 205, can include a built-in temperature sensor, such as the temperature sensor 211 within the accelerometer 205. For example, the temperature sensor 211 within the accelerometer 205 can be used to calibrate the accelerometer 205 over a wide temperature range and to measure the temperature of the area of the body that the accelerometer 205 is coupled to. Other temperature sensors included with other device components can also be used. Other than the accelerometer 205, and temperature sensor 211, other subcomponents or elements of the wearable device 200 can include one or more microelectromechanical system (MEMS) components within the wearable device 200 that is designed to measure motion or orientation (e.g., angular-rate gyroscope, etc.). Alternatively, or in addition, the wearable device 200 can include a discrete temperature sensor, such as the temperature sensor 213 which can be positioned in a different location from the wearable device 200. The wearable device 200 can use the temperature information detected by the temperature sensor 211 and/or the temperature sensor 213 according to various methods and processes, as discussed in greater detail below. For purposes of convenience, reference is made below to the temperature sensor 211. However, such reference is not limited to apply only to the temperature sensor 211, but applies to any one or more temperature sensors within or connected to the wearable device 200.


The electrical contacts 215 can be formed of conductive material (e.g., copper, silver, gold, aluminum, a hydrogel, conductive polymer, etc.) and provide an interface between the wearable device 200 and the skin of the user 100, for receiving electrical signals (e.g., ECG, EMG, etc.) from the skin. The electrical contacts 215 can include one or more electrical contacts 215, such as two electrical contacts 215, electrically connecting the skin of the user 100 to an amplifier circuit that can be part of an analog front end circuit 216, to amplify and condition electrical signals (e.g., ECG, EMG, etc). With two electrical contacts 215, one contact can be electrically configured as a positive contact and the other contact can be electrically configured as a negative contact. However, in some aspects, there may be more than two electrical contacts, such as four electrical contacts 215 (e.g., two positive and two negative electrical contacts), six electrical contacts 215, etc.


The optical sensor 217 can measure the photoplethysmography (PPG) signal when placed on the skin's surface, allowing for the monitoring of various biometrics including, but not limited to, heart rate, respiration, and blood oxygen measurements. The optical sensor 217 can include one or more light emitters that can emit red, green, infrared light or a combination thereof and one or more optical transducers (e.g., photodiode, CCD sensors). Using the one or more optical transducers, the optical sensor 217 can sense the wavelength of the reflected light. In this example, the optical sensor 217 illuminates the skin and the reflected light changes intensity based on the concentration of oxygen in a blood vessel such as an artery or a capillary bed. Thus, a pulse can be detected as a change in the amount of the reflected light due to a change in the concentration of oxygen in a blood vessel and thus the reflected light detected by the optical sensor 217. Of course other sensors can be included on the wearable device 200 to detect the pulse such as the accelerometer 205, a pressure sensor, a strain gauge sensor or an acoustic sensor to measure the mechanoacoustic signatures of the pulse.


In addition to the above-described components, the wearable device 200 can include one or more additional components without departing from the spirit and scope of the present disclosure. Such components can include a display (e.g., one or more light-emitting diodes (LEDs), liquid crystal display (LCD), organic light-emitting diode (OLED)), a speaker, a microphone, a vibration motor, a barometer, a light sensor, a photoelectric sensor, or any other sensor for sensing, measuring, or otherwise quantifying parameters and/or characteristics of the body. In other embodiments of the invention, the wearable device 200 can include components for performing one or more additional sensor modalities, such as, but not limited to, hydration level measurements, conductance measurements, capacitance measurements, and/or pressure measurements. For example, the wearable device 200 can be configured to, or include one or more components that, perform any combination of these different types of sensor measurements, in addition to the accelerometer 205 and temperature sensor 211.


Referring back to the temperature sensor 211, according to some embodiments, the primary purpose of the temperature sensor 211 is for calibrating the accelerometer 205. Accordingly, the temperature sensor 211 does not rely on direct contact to an object to detect the temperature. By way of example, the temperature sensor 211 does not require direct contact to the skin of a user when coupled to the user to determine the skin temperature. For example, the skin temperature affects the temperature information generated by the wearable device 200 without direct contact between the temperature sensor 211 and the skin. Accordingly, the temperature sensor 211 can be fully encapsulated and, therefore, be waterproof for greater durability. The thermal conductivity of the encapsulating material can be selected to control the ability of the temperature sensor 211 to detect the temperature without direct contact.


Temperature information generated by the temperature sensor 211 can be used by the wearable device 200 to determine an on-body status of the wearable device 200. Detection of the on-body status allows the wearable device 200 to automatically determine when the device is or is not coupled to a user. Functionality of the wearable device 200 (e.g., the computer program executed and/or components activated) can be selected or changed based on the detected on-body status.


The wearable device 200 can use the temperature information from the temperature sensor 211 based on the relationship that exists between the detected temperature information when the wearable device 200 is coupled to the body versus when the wearable device 200 is not coupled the body. More specifically, the wearable device 200 can use the difference between ambient air temperature and the skin temperature of the user to determine on body status.


When the wearable device 200 is coupled to the body, the measured temperature is primarily influenced by the skin temperature at the coupling location. In contrast, when the wearable device 200 is not coupled to the body, the measured temperature is primarily influenced by the ambient air temperature. That is, in general, when coupled to the body of the user, the heat generated by the user's body elevates the measured temperature to greater than the ambient air temperature. For most ambient air temperatures, the skin temperature at the coupling location is greater than the ambient air temperature. Thus, the wearable device 200 being off the body versus on the body is reflected in the changes of the temperature information generated by the temperature sensor 211.


The temperature information can be used to determine an on-body state of the wearable device 200. The temperature information can be raw temperature information (e.g., un-scaled) or normalized temperature information (e.g., scaled). Such normalization can include relating the raw temperature information to a specific temperature scale, such as Celsius, Fahrenheit, etc. Further, the temperature information detected by the temperature sensor 211 can include the temperature (raw or normalized), the change in temperature, and/or the rate of change in temperature. Depending on one or more of the temperature, the change in temperature, and the rate of change in temperature, the wearable device 200 can determine the on-body state by, for example, comparing the temperature, change in temperature, or rate of change in temperature to an ambient temperature value or a predefined value (e.g., from a lookup table or a decision tree).


By way of example, and without limitation, during a first state or period, the temperature sensor 211 within the wearable device 200 may generate a detected normalized temperature of 20° C. Subsequently, the wearable device 200 may generate a detected normalized temperature of 31° C. The normalized temperatures can be used to determine the on-body status of the wearable device 200. According to some embodiments, the temperature (e.g., 31° C.) alone indicates the on-body status of the wearable device 200. One or more specific temperature values (e.g., scaled or un-scaled) can be correlated to an on-body status, such as on the body or off of the body. Accordingly, when one of the specific temperature values is reached (or a temperature change is reached), the wearable device 200 determines on-body status accordingly. Alternatively, or in addition, one or more thresholds may be previously correlated to an on-body status. Accordingly, when one of the thresholds is met, the wearable device 200 determines its on-body status accordingly. By way of example, and without limitation, a threshold may be 24° C. such that a temperature above 24° C. correlates to the wearable device 200 being on the body.


According to some embodiments, the wearable device 200 can include machine learning to, for example, modify the thresholds based on repeated usage of the wearable device 200, such that the on-body status (and/or specific locations) determined by one sensing modality (e.g., accelerometer based location) can be used to update the thresholds or indicators for use with another sensing modality (e.g., temperature). Further, according to some embodiments, specific individuals have specific heat signatures or variations in temperature with respect to location of the wearable device 200. Thus, according to some embodiments, the wearable device 200 can use historical temperature information to determine the identity of the user wearing the wearable device 200, in addition to determining the on-body status. The determination as to the identity of the wearer of the wearable device 200 can also use information from one or more of the components of the wearable device 200.


According to some embodiments, the change in temperature (e.g., 20° C. to 31° C.) indicates the on-body status of the wearable device 200. The wearable device 200 can use the change in temperature to omit false on-body statuses that are based on, for example, elevated ambient temperatures. By way of example, depending on certain locations and/or activities, the ambient air temperature's effect on the temperature sensor 211 may give a false on-body status. Accordingly, the change in temperature can be used to determine the on-body status in which a lower temperature is used as an indicator of, for example, the ambient air temperature (e.g., the wearable device 200 not coupled to the body). A change in temperature from, for example, 20° C. to 31° C. can indicate that the wearable device 200 went from being off of the body (e.g., in an ambient air environment at 20° C.) to being on the body and now registering a temperature of 31° C. (e.g., body surface temperature).


Along with the temperature information, the temperature sensor 211, or another sensor or component within the wearable device 200 (e.g., processor 201, transceiver 207, etc.), can measure time or can generate information based on a set rate (e.g., one measurement every three seconds). The measured time can be correlated to the temperature information. Such correlation of the time to the temperature information can be used for determining the on-body state of the wearable device 200. For example, the rate of change in temperature (e.g., 20° C. to 31° C. over the course of, for example, 30 seconds) can indicate the on-body status of the wearable device 200. Whereas, for example, the rate of change in temperature (e.g., 20° C. to 31° C. over the course of, for example, 30 minutes) can indicate the wearable device 200 is left in the sun or a hot car and this information can be combined with other sensor data, such as accelerometer data, to confirm a lack of movement. Using both the change in the temperature and the time during which the change occurred to obtain the rate can further eliminate false on-body statuses, such as eliminating the ambient air temperature changing over a period of time, which could possibly provide a false on-body status.



FIG. 3 shows a wireless charging circuit 300 on the wearable device 200 shown in FIG. 2. The wireless charging circuit 300 can include a RF power chain (shown below). In this example, the RF power chain 300 ensures a 90% battery charge in roughly 90 minutes on the wearable device 200.


In accordance with some embodiments of the invention, the RF chain can include an RF source circuit 310, an attenuation and filtering circuit 312, a gain circuit 314, and matching network circuit 316 to generate a charging signal in a coil 320. The RF source circuit 310 can include a crystal 320. In this example, the crystal 320 has 30 parts per million error over a suitable temperature range of 30 to 60 degrees C. In this example, the RF source is generated using a filtered and buffered digital output from the microcontroller 201 in FIG. 2 to provide a low output impedance rail to rail 13.56 MHz signal output 322.


In accordance with some embodiments of the invention, the buffered digital clock output from the microprocessor 201 is routed to the attenuation and filtering circuit 312. The attenuation and filtering circuit 312 can include a filter circuit 324 that filters out higher harmonics in the square wave to produce a sinusoid signal. This results in less reflections, better power transfer, and less unwanted RF radiation.


In accordance with some embodiments of the invention, the signal from the attenuation and filtering circuit 312 can be sent to a gain circuit 314. The gain circuit 314 can include two operational amplifiers 330 and 332. In the gain circuit 314, the signal can be amplified to maximize the voltage driving the coil. The operational amplifiers 330 and 332 can be split into two stages to avoid gain bandwidth issues. The operational amplifiers 332 can be selected for high frequency capabilities and high output current.


In accordance with some embodiments of the invention, a matching network circuit 340 can be used to minimize reflections and maximize wireless power transfer. The matching network circuit 340 can include tuning capacitors and inductors. A series tuning capacitor 344 can be used to maximize power through a coil 346 at the resonance frequency, 13.56 MHz.



FIG. 4 is a block diagram of the charging device 120 in FIG. 1 according to some embodiments of the invention. The charging device 120 can include a microcontroller or microprocessor 400 that controls the internal components. The charging device 120 can include a low energy transceiver 402, a wireless charging transceiver 404, and a fast data transceiver 406. The charging device 120 also includes a memory 410 for storage of data. The data in the memory 410 may be transferred to another computing device via input/output interface 412 that may be a USB port in this example. Of course other wired and wireless interfaces may be used.


In this example, the low energy transceiver 402 can use the Bluetooth Low Energy (BLE) transmission protocol. Thus, performing bulk data downloads using the BLE hardware and firmware is very slow (roughly 2 kBytes/s-5 kBytes/s). For example, downloading 32 MBytes of data from the example wearable device 112 takes as long as 4.44 hours. The fast data transceiver 406 has a faster rate of data transmission than the low energy transceiver 402. In this example, the fast data transceiver 406 is a NRF51822, Microcontroller capable of the Gazelle or Enhanced Shock Burst protocol by Nordic Semiconductor. In this example, the fast data transceiver 406 has a data throughput as high as 25 kBytes/s, a 5-10× improvement over the low energy transceiver 402. Switching between the Gazelle protocol of the fast transceiver 406 and the Bluetooth Low Energy (BTLE) of the low energy transceiver 402 can be performed on the fly in firmware on the charging device 120, enabling the low power advantages of the BTLE protocol and the high data throughput of the Gazelle protocol on the same device with no hardware changes. In order to enable this advantage, both the wireless charging device 120 and the wearable device 112 both have a transceiver controller capable of the high speed transmission protocol such as the NRF51822 Microcontroller.


The microcontroller or microprocessor 400 can be part of the same hardware component (e.g., a system on a chip device) as the transceiver 406 or it can be a separate device. The microprocessor 400 operates the general functions of the charging device 120. The microprocessor 400 also runs applications to control the charging and data reception from wearable devices via communication with the user device 110 in FIG. 1.


As explained above, the initiation and transfer of this data between the wearable sensor device 112 and the charging device 120 can be controlled by a smart device with a BTLE transceiver, such as the smart device 110. As explained above, the smart device 110 communicates to both the charging device 120 and wearable device 112 in order to put them in one or more data-transfer mode. FIG. 4 shows the process by the smart device 110 controlling the charging and data transfer to the charging device 120 in FIG. 1. As shown in FIG. 5, a low energy communication channel 502 is established between the user device 110 and the wearable device 112. Similarly, a low energy communication channel 504 is established between the user device 110 and the charging device 120. A wireless charging and data transmission channel 506 is established between the wearable device 112 and the charging device 120.


The low energy communication channel 502 serves to provide device configuration, interface and general management of the wearable device 112 from the user smart device 110. The management includes identifying the particular wearable device, status information on the power level of the wearable device 112 and how much data has been collected by the wearable device 112. The low energy communication channel 504 serves to provide charger configuration and bulk download configuration from the user smart device 110 to the charging device 120. These instructions may include the selection of charging or data transmission, the rate of charging or data transmission, the identification of the specific wearable device, the charge state of the device, and the memory state of the device (e.g., ready for download/downloaded). After authorization from the user device 110, the charging and communication channel 406 is established between the charging device 120 and the wearable device 110. The communication rate is established by command from the user device 110.



FIG. 6 is a flow diagram of the procedure to download data from the wearable device 112 in the environment in FIG. 1 using the communication links in FIG. 5. Initially, the charging device 120 is in Bluetooth low energy advertising mode. Once a user device 110 is in range of the charging device, the user device 110 initiates handshaking with the wearable device 112 and the charging device 120 (600). After initiation of handshaking, the user device 110 instructs the charging device 120 and the wearable device 112 when to initiate data transfer (602). The two devices will pair up via Gazelle automatically based on their MAC addresses that are received from the user device 110 (604). The pairing process disconnects the charging device 120 and the wearable device 112 from the user device 110. The charging device 120 and the wearable device 112 initiate a handshake protocol for either charging or wireless data transmission. The charging device 120 will download the data at the designated data transmission rate (606). The charging device 120 then either stores that data to local memory, or offloads this data through a wired connection to another device such as a computer 130 (e.g., PC/tablet) or via an unwired connection such as WiFi (608). This data can then be sent to the cloud server 140, and the wearable device 112 returns to normal operation for monitoring and gathering data while the charging device 120 returns to Bluetooth low energy advertising mode. Individual device detection is performed via a handshaking protocol where individual channels of the charging device periodically modulate the local wireless power signal in a predefined pattern that is detectable by the wearable devices. Once the wearable devices detect the load modulation pattern they communicate with the charging device and other wearable devices over the low energy communication channel to arbitrate and assign/unassign device/channel pairings.


In another example, the charger 120 can communicate simultaneously with multiple wearable devices such as the wearable devices 112, 114, 116 and 118 in FIG. 1. For the detection and charging of multiple devices, a separate charging coil 344, gain stage 314, and matching network 316 shown in FIG. 3 is required for each device. Detection of multiple devices can be handled by the charging device 120 through antenna backscattering or by the wearable device through detection of valid power received via the charging circuitry. In the embodiment using antenna backscattering the microcontroller 400 measures the amount of electrical current delivered to any of its charging coils 344. This electrical current will change from baseline when a device is placed in proximity to the charging device 140. The device to be charged uses this detection mechanism to send a keyed signature back to the charging device 120 by detuning its own charging coil periodically. Once the charging device 120 confirms the unique backscattering signature from the device, it will begin transmitting power continuously through its charging coil 344. With multiple charging coils on a single charging device, the microcontroller 400 can determine what device is on which coil—especially if each device has its own unique signature—and will only deliver power to charging coils coupled with confirmed devices. In the embodiment where detection of multiple devices is handled by the wearable device, the charging device 120 periodically modulates the local wireless power signal in a predefined pattern sequentially for each channel. Once wearable devices detect the load modulation pattern they communicate with the charging device and other wearable devices over the low energy communication channel to arbitrate and assign/unassign device/channel pairings.


In this architecture, the charging device 120 can prioritize and queue data transfer from each wearable device 112, 114, 116 and 118 based on an optimization scheme. This data scheme can be based on a set of assumptions and real time metrics from the wearable devices to determine a Figure of Merit (FOM) that the charger can use to rank and prioritize data-offloading using the following procedure. Data can be transferred from the devices to the charging using the following protocols: Bluetooth, Bluetooth Low Energy, ANT, Enhanced Shock Burst (Gazelle), Wifi, and any other wireless protocol which is carried on the 2.4 GHz wavelength. The charging device 120 can receive data relating to battery voltages, files to download, and used-memory capacity from each of the user devices 112, 114, 116 and 118 in the area, either directly (e.g, based on commands issued from the user device 110) or indirectly (e.g., through the user device 110). The microprocessor 400 of the charging device 120 can include a program or process that performs an assessment of each wearable device by determining the Figure of Merit:

FOM=Battery Voltage*number of Files/Used Memory

where Battery Voltage is in Volts (V), number of Files is unitless, and Used Memory is in Megabytes (MB).


The output of the FOM is a numerical value that is directly proportional to the battery level, the amount of data to be off loaded (e.g., number of data files or recordings) and indirectly proportional to an amount of memory used by the device to store the data. The user device 110 and/or the wireless charger 120 can use the FOM to identify the wearable devices that have high battery capacity or a large number of records to download and to rank or prioritize these devices for data transfer to prevent data loss.


In accordance with some embodiments of the invention, the user device 110 (or the wireless charger 120) can compare the FOM of a wearable device to a predefined threshold to determine whether the wearable device has a FOM below that threshold, and the user device 110 can communicate instructions to the charger device 120 (e.g., via the Bluetooth Low Energy communication 122) to charge the wearable device prior to data transfer. After the wearable device is charged (e.g., either fully or at or above a predefined threshold), the user device 110 can communicate instructions to the charging device 120 to switch to charging mode. If the user device 110 (or the charger device 120) determines that the wearable device has a FOM above the predefined threshold, the user device 110 can communicate instructions to the charging device 120 instructing it to queue the wearable device (based on its FOM) for data offload and perform a data transfer according to its position in the queue, relative to some or all other wearable devices.


The system 100 allows charging of wearable sensor devices wirelessly and performing bulk data downloads at higher throughputs than Bluetooth Low Energy currently provides. The system 100 also allows execution of intelligent charging and data-offloading strategies to accommodate the needs of multiple devices simultaneously. In addition, the system 100 allows different levels of access to faster data-offloading speeds from the wearable sensor device, so consumers no longer need to wait after they collect data to perform an analysis. The wearable sensor device can switch between multiple protocols enabling the wearable sensor device to be power efficient while also having high data throughput capabilities


In accordance with some embodiments of the invention, the wireless charger 120 can include software and/or hardware that are capable of wirelessly charging a device (e.g., a user device 110) at different rates. For example, the Qi wireless charging standard from the Wireless Power Consortium includes a standard charging rate (e.g., 5 watts) and a fast charging rate (e.g., 15 watts). The wireless charger 120 can include a processor and associated memory and execute one or more programs that enable the wireless to selectively operate in the standard charging rate mode or a fast charging rate mode. By default, when a user device 110 is placed on the wireless charger 120, the wireless charger 120 will operate in standard charging rate mode. In accordance with some embodiments of the invention, the wireless charger 120 can communicate with the user device 110 either directly (e.g., using WiFi or Bluetooth) or indirectly (e.g., using WiFi or Bluetooth through a remote device) to negotiate a different (e.g., faster) charging rate, optionally for a fee or other consideration. In accordance with some embodiments of the invention, the user device 110 can negotiate a faster charging rate for a one-time fee that places the wireless charger in a faster charging rate mode and enables the user device 110 to be charged at the higher rate for a predefined period of time (e.g., 15 min., 30 min., 45 min., 1 hr., 90 min., 2 hrs., 3 hrs., 24 hrs., or longer). For example, the wireless charger 120 can provide a token to the user device 110 that In accordance with some embodiments of the invention, the user device 110 can negotiate a faster charging rate for a flat or periodic fee (e.g., establishing a wireless charging account) that places the wireless charger in a faster charging rate mode and enables the user device 110 to be charged at the higher rate for as long as the account is active or maintained (e.g., paid up).


In accordance with some embodiments of the invention, the wireless charger 120 can include software and/or hardware that are capable of communicating with a device (e.g., a user device 110) or controlling a remote wireless access point to communicate with a device (e.g., a user device 110) at different data rates. For example, the WiFi standards include several different communication standards (e.g., IEEE 802.11b, 802.11g, 802.11ac, 802.11n) that support different data rates. Similarly, Bluetooth™ also supports multiple data rate modes of operation (e.g., classic, enhanced data rate and high speed). The wireless charger 120 can include a processor and associated memory and execute one or more programs that enable the wireless charger 120 to selectively communicate with the user device 110 at a standard data rate or a faster date rate. By default, when a user device 110 is placed on the wireless charger 120, the wireless charger 120 will communicate in a standard data rate mode. Similarly, the wireless charger 120 can communicate with the user device 110 either directly (e.g., using WiFi or Bluetooth) or indirectly (e.g., using WiFi or Bluetooth through a remote device) to negotiate a different (e.g., faster) data communication rate, optionally for a fee or other consideration. In accordance with some embodiments of the invention, the user device 110 can negotiate a faster data rate for a one-time fee that places the wireless charger 120 (or the wireless access point) in a faster data rate mode and enables the user device 110 to access a network (e.g., the Internet) at the higher data rate for a predefined period of time (e.g., 15 min., 30 min., 45 min., 1 hr., 90 min., 2 hrs., 3 hrs., 24 hrs., or longer). For example, the user device 110 can purchase a token and provide the token to the wireless charger 120 that expires after a predefined period of time. In accordance with some embodiments of the invention, the user device 110 can negotiate a faster data rate for a flat or periodic fee (e.g., establishing a wireless charging account) that places the wireless charger 120 (or wireless access point) in a faster data rate mode and enables the user device 110 to access a network (e.g., the Internet) at the higher data rate for as long as the account is active or maintained (e.g., paid up).


In some embodiments, the aforementioned methods include at least those steps enumerated above. It is also within the scope and spirit of the present disclosure to omit steps, include additional steps, and/or modify the order of steps presented herein. It should be further noted that each of the foregoing methods can be representative of a single sequence of related steps; however, it is expected that each of these methods will be practiced in a systematic and repetitive manner.


The disclosure discussed herein can be applied to any wearable device 100 and/or system including the capability of determining 3-axis accelerometer information, which can enable a broad range of commercial applications. Such applications may include one that requires the user to place a sensor at different body locations to derive location-specific information. A wearable running coach, a wearable cross-fit monitor, and a wearable Parkinson's disease motor symptom monitor are but a few examples of such applications.


While particular embodiments and applications of the present disclosure have been illustrated and described, it is to be understood that the present disclosure is not limited to the precise construction and compositions disclosed herein and that various modifications, changes, and variations can be apparent from the foregoing descriptions without departing from the spirit and scope of the invention as defined in the appended claims.

Claims
  • 1. A wireless control system comprising: a wireless charging device including a transmitter to transmit a charging signal, a first receiver to receive a data signal and a second receiver to receive a low energy signal;a sensor device including a memory for storing sensed data, a first receiver to receive a charging signal, a first transmitter to transmit a data signal, and a second receiver to receive a low energy signal, wherein the transmitter of the wireless charging device is a transceiver operating in a fast data transfer protocol and the second receiver of the wireless charging device operates in a slower data transfer protocol, and wherein one of the protocols is used for the data transfer from the sensor device; anda user device including a low energy transmitter in communication with the second receiver of the wireless charging device and the second receiver of the sensor device, the user device operative to initiate a data transfer from the sensor device to the wireless charging device.
  • 2. The wireless control system of claim 1, wherein the sensor device is one of a plurality of sensor devices, each of the plurality of sensor devices in communication via a low energy signal with the user device.
  • 3. The wireless control system of claim 2, wherein the user device is operative to initiate the transmission of a charging signal from the charging device to the sensor device.
  • 4. The wireless control system of claim 3, wherein the user device prioritizes one of the plurality of sensor devices for receiving the charging signal from the charging device.
  • 5. The wireless control system of claim 4, wherein the prioritization is based on a power level of each of the plurality of sensor devices.
  • 6. The wireless control system of claim 3, wherein the prioritization is based on payment by a user through the user device for the sensor device.
  • 7. The wireless control system of claim 2, wherein the user device prioritizes one of the plurality of sensor devices for transmitting the data signal to the charging device.
  • 8. The wireless control system of claim 7, wherein the prioritization is based on the amount of data stored on each of the plurality of sensor devices.
  • 9. The wireless control system of claim 7, wherein the prioritization is based on the power level on each of the plurality of sensor devices.
  • 10. The wireless control system of claim 7, wherein the prioritization is based on payment by a user through the user device for the sensor device.
  • 11. The wireless control system of claim 1, wherein the sensor device is a wearable device adhered to the skin of a user.
  • 12. The wireless control system of claim 1, wherein the user device transmitter and the second receiver of the sensor device and second receiver of the charging device are Bluetooth low energy transceivers.
  • 13. The wireless control system of claim 1, wherein the transmitter of the wireless charging device transmits a charging signal and the second receiver of the wireless charging device receives the data signal from the sensor device simultaneously.
  • 14. The wireless control system of claim 1, wherein the user device selects the fast data transfer protocol or the slower data transfer protocol for the charging device receiving the data signal from the sensor device.
  • 15. The wireless control system of claim 1, wherein the fast data transfer protocol is the Enhanced Shock Burst data protocol and the slower data transfer protocol is the Bluetooth protocol.
  • 16. The wireless control system of claim 1, wherein the selection of the protocol is based on payment received from a user through the user device.
  • 17. The wireless control system of claim 1, wherein the user device is one of a smart phone, a lap top computer, a tablet, or a personal data assistant.
  • 18. A method of transmitting data from a sensor device to a wireless charging device, the sensor device including a memory for storing sensed data, a first receiver to receive a charging signal, a transmitter to a data signal, and a second receiver to receive a low energy signal, wherein the transmitter of the wireless charging device is a transceiver operating in a fast data transfer protocol and the second receiver of the wireless charging device operates in a slower data transfer protocol, and wherein one of the protocols is used for the data transfer from the sensor device, the charging device including a transmitter to transmit a charging signal, a first receiver to receive a data signal and a second receiver to receive a low energy signal, the method comprising: storing sensed data in the memory of the sensor device;initiating communication between a user device and the charging device via a low energy transmitter on the user device;initiating communication between the user device and the charging device via the low energy transmitter on the user device; andinitiating data transfer between the sensor device and the charging device via the first transmitter of the sensor device based on authorization from the user device.
  • 19. The method of claim 18, wherein the sensor device is one of a plurality of sensor devices, each of the plurality of sensor devices in communication via a low energy signal with the user device.
  • 20. The method of claim 19, further comprising initiating transmission of a charging signal from the charging device to the sensor device by the user device.
  • 21. The method of claim 20, wherein the user device prioritizes one of the plurality of sensor devices for receiving the charging signal from the charging device.
  • 22. The method of claim 21, wherein the prioritization is based on a power level of each of the plurality of sensor devices.
  • 23. The method of claim 20, wherein the prioritization is based on payment by a user through the user device for the sensor device.
  • 24. The method of claim 19, wherein the user device prioritizes one of the plurality of sensor devices for transmitting the data signal to the charging device.
  • 25. The method of claim 24, wherein the prioritization is based on the amount of data stored on each of the plurality of sensor devices.
  • 26. The method of claim 24, wherein the prioritization is based on the power level on each of the plurality of sensor devices.
  • 27. The method of claim 24, wherein the prioritization is based on payment by a user through the user device for the sensor device.
  • 28. The method of claim 18, wherein the sensor device is a wearable device adhered to the skin of a user.
  • 29. The method of claim 18, wherein the user device transmitter and the second receiver of the sensor device and the second receiver of the charging device are Bluetooth low energy transceivers.
  • 30. The method of claim 18, wherein the wireless charging device transmits a charging signal and receives the data signal from the sensor device simultaneously.
  • 31. The method of claim 18, further comprising selecting the fast data transfer protocol or the slower data transfer protocol for the charging device receiving the data signal from the sensor device.
  • 32. The method of claim 31, wherein the selection of the protocol is based on payment received from a user of the user device.
  • 33. The method of claim 18, wherein the fast data transfer protocol is the Enhanced Shock Burst data protocol and the slower data transfer protocol is the Bluetooth protocol.
  • 34. The method of claim 18, wherein the user device is one of a smart phone, a lap top computer, a tablet, or a personal data assistant.
PRIORITY CLAIM

This application claims the benefit of U.S. Provisional Patent Application Ser. No. 62/374,510 filed Aug. 12, 2016 entitled “Wireless Charger And High Speed Data Off-Loader.

US Referenced Citations (515)
Number Name Date Kind
3207694 Gogek Sep 1965 A
3716861 Root Feb 1973 A
3805427 Epstein Apr 1974 A
3838240 Schelhorn Sep 1974 A
3892905 Albert Jul 1975 A
4136162 Fuchs Jan 1979 A
4278474 Blakeslee Jul 1981 A
4304235 Kaufman Dec 1981 A
4416288 Freeman Nov 1983 A
4658153 Brosh Apr 1987 A
4911169 Ferrari Mar 1990 A
4968137 Yount Nov 1990 A
5059424 Cartmell Oct 1991 A
5064576 Suto Nov 1991 A
5272375 Belopolsky Dec 1993 A
5278627 Aoyagi Jan 1994 A
5306917 Black Apr 1994 A
5326521 East Jul 1994 A
5331966 Bennett Jul 1994 A
5360987 Shibib Nov 1994 A
5413592 Schroeppel May 1995 A
5471982 Edwards May 1995 A
5454270 Brown Oct 1995 A
5491651 Janic Feb 1996 A
5567975 Walsh Oct 1996 A
5580794 Allen Dec 1996 A
5617870 Hastings Apr 1997 A
5676144 Schoendorfer Oct 1997 A
5811790 Endo Sep 1998 A
5817008 Rafert Oct 1998 A
5907477 Tuttle May 1999 A
6063046 Allum May 2000 A
6220916 Bart Apr 2001 B1
6265090 Nishide Jul 2001 B1
6270872 Cline Aug 2001 B1
6282960 Samuels Sep 2001 B1
6343514 Smith Feb 2002 B1
6387052 Quinn May 2002 B1
6410971 Otey Jun 2002 B1
6421016 Phillips Jul 2002 B1
6450026 Desarnaud Sep 2002 B1
6455931 Hamilton Sep 2002 B1
6567158 Falcial May 2003 B1
6626940 Crowley Sep 2003 B2
6628987 Hill Sep 2003 B1
6641860 Kaiserman Nov 2003 B1
6775906 Silverbrook Aug 2004 B1
6784844 Boakes Aug 2004 B1
6825539 Tai Nov 2004 B2
6965160 Cobbley Nov 2005 B2
6987314 Yoshida Jan 2006 B1
7259030 Daniels Aug 2007 B2
7265298 Maghribi Sep 2007 B2
7302751 Hamburgen Dec 2007 B2
7337012 Maghribi Feb 2008 B2
7487587 Vanfleteren Feb 2009 B2
7491892 Wagner Feb 2009 B2
7521292 Rogers Apr 2009 B2
7557367 Rogers Jul 2009 B2
7618260 Daniel Nov 2009 B2
7622367 Nuzzo Nov 2009 B1
7727228 Abboud Jun 2010 B2
7739791 Brandenburg Jun 2010 B2
7759167 Vanfleteren Jul 2010 B2
7815095 Fujisawa Oct 2010 B2
7960246 Flamand Jun 2011 B2
7982296 Nuzzo Jul 2011 B2
8097926 De Graff Jan 2012 B2
8198621 Rogers Jun 2012 B2
8207473 Axisa Jun 2012 B2
8217381 Rogers Jul 2012 B2
8332053 Patterson Dec 2012 B1
8372726 De Graff Feb 2013 B2
8389862 Arora Mar 2013 B2
8431828 Vanfleteren Apr 2013 B2
8440546 Nuzzo May 2013 B2
8536667 De Graff Sep 2013 B2
8552299 Rogers Oct 2013 B2
8609471 Xu Dec 2013 B2
8618656 Oh Dec 2013 B2
8664699 Nuzzo Mar 2014 B2
8679888 Rogers Mar 2014 B2
8729524 Rogers May 2014 B2
8754396 Rogers Jun 2014 B2
8865489 Rogers Oct 2014 B2
8886334 Ghaffari Nov 2014 B2
8905772 Rogers Dec 2014 B2
9012784 Arora Apr 2015 B2
9082025 Fastert Jul 2015 B2
9105555 Rogers Aug 2015 B2
9105782 Rogers Aug 2015 B2
9107592 Litt Aug 2015 B2
9119533 Ghaffari Sep 2015 B2
9123614 Graff Sep 2015 B2
9133024 Phan Sep 2015 B2
9159635 Elolampi Oct 2015 B2
9168094 Lee Oct 2015 B2
9171794 Rafferty Oct 2015 B2
9186060 De Graff Nov 2015 B2
9226402 Hsu Dec 2015 B2
9247637 Hsu Jan 2016 B2
9289132 Ghaffari Mar 2016 B2
9295842 Ghaffari Mar 2016 B2
9320907 Bogie Apr 2016 B2
9324733 Rogers Apr 2016 B2
9372123 Li Jun 2016 B2
9408305 Hsu Aug 2016 B2
9420953 Litt Aug 2016 B2
9450043 Nuzzo Sep 2016 B2
9515025 Rogers Dec 2016 B2
9516758 Arora Dec 2016 B2
9545216 D'Angelo Jan 2017 B2
9545285 Ghaffari Jan 2017 B2
9554850 Lee Jan 2017 B2
9579040 Rafferty Feb 2017 B2
9583428 Rafferty Feb 2017 B2
D781270 Li Mar 2017 S
9622680 Ghaffari Apr 2017 B2
9629586 Ghaffari Apr 2017 B2
9647171 Rogers May 2017 B2
9655560 Ghaffari May 2017 B2
9662069 De Graff May 2017 B2
9702839 Ghaffari Jul 2017 B2
9704908 De Graff Jul 2017 B2
9706647 Hsu Jul 2017 B2
9723122 Ghaffari Aug 2017 B2
9723711 Elolampi Aug 2017 B2
9750421 Ghaffari Sep 2017 B2
9757050 Ghaffari Sep 2017 B2
9761444 Nuzzo Sep 2017 B2
9768086 Nuzzo Sep 2017 B2
9801557 Ghaffari Oct 2017 B2
9844145 Hsu Oct 2017 B2
9810623 Ghaffari Nov 2017 B2
9833190 Ghaffari Dec 2017 B2
9839367 Litt Dec 2017 B2
9846829 Fastert Dec 2017 B2
9894757 Arora Feb 2018 B2
9899330 Dalal Feb 2018 B2
9949691 Huppert Apr 2018 B2
10032709 Rafferty Jul 2018 B2
D825537 Li Aug 2018 S
10064269 Rogers Aug 2018 B2
10186546 De Graff Jan 2019 B2
20010012918 Swanson Aug 2001 A1
20010021867 Kordis Sep 2001 A1
20010043513 Grupp Nov 2001 A1
20020000813 Hirono Jan 2002 A1
20020026127 Balbierz Feb 2002 A1
20020060633 Crisco, III May 2002 A1
20020077534 Durousseau Jun 2002 A1
20020079572 Khan Jun 2002 A1
20020082515 Campbell Jun 2002 A1
20020094701 Biegelsen Jul 2002 A1
20020107436 Barton Aug 2002 A1
20020113739 Howard Aug 2002 A1
20020128700 Cross, Jr. Sep 2002 A1
20020145467 Minch Oct 2002 A1
20020151934 Levine Oct 2002 A1
20020158330 Moon Oct 2002 A1
20020173730 Pottgen Nov 2002 A1
20020193724 Stebbings Dec 2002 A1
20030017848 Engstrom Jan 2003 A1
20030045025 Coyle Mar 2003 A1
20030097165 Krulevitch May 2003 A1
20030120271 Burnside Jun 2003 A1
20030162507 Vatt Aug 2003 A1
20030214408 Grajales Nov 2003 A1
20030236455 Swanson Dec 2003 A1
20040006264 Mojarradi Jan 2004 A1
20040085469 Johnson May 2004 A1
20040092806 Sagon May 2004 A1
20040106334 Suzuki Jun 2004 A1
20040118831 Martin Jun 2004 A1
20040135094 Niigaki Jul 2004 A1
20040138558 Dunki-Jacobs Jul 2004 A1
20040149921 Smyk Aug 2004 A1
20040178466 Merrill Sep 2004 A1
20040192082 Wagner Sep 2004 A1
20040201134 Kawai Oct 2004 A1
20040203486 Shepherd Oct 2004 A1
20040221370 Hannula Nov 2004 A1
20040238819 Maghribi Dec 2004 A1
20040243204 Maghribi Dec 2004 A1
20050021103 DiLorenzo Jan 2005 A1
20050029680 Jung Feb 2005 A1
20050030408 Ito Feb 2005 A1
20050065486 Fattman Mar 2005 A1
20050067293 Naito Mar 2005 A1
20050070778 Lackey Mar 2005 A1
20050096513 Ozguz May 2005 A1
20050113744 Donoghue May 2005 A1
20050139683 Yi Jun 2005 A1
20050171524 Stern Aug 2005 A1
20050203366 Donoghue Sep 2005 A1
20050204811 Neff Sep 2005 A1
20050248312 Cao Nov 2005 A1
20050261617 Hall Nov 2005 A1
20050258050 Bruce Dec 2005 A1
20050285262 Knapp Dec 2005 A1
20060003709 Wood Jan 2006 A1
20060009700 Brumfield Jan 2006 A1
20060038182 Rogers Feb 2006 A1
20060071349 Tokushige Apr 2006 A1
20060084394 Engstrom Apr 2006 A1
20060106321 Lewinsky May 2006 A1
20060122298 Menon Jun 2006 A1
20060128346 Yasui Jun 2006 A1
20060154398 Qing Jul 2006 A1
20060160560 Josenhans Jul 2006 A1
20060235314 Migliuolo Oct 2006 A1
20060248946 Howell Nov 2006 A1
20060257945 Masters Nov 2006 A1
20060264767 Shennib Nov 2006 A1
20060270135 Chrysler Nov 2006 A1
20060276702 McGinnis Dec 2006 A1
20060286785 Rogers Dec 2006 A1
20070027374 Wihlborg Feb 2007 A1
20070027514 Gerber Feb 2007 A1
20070031283 Davis Feb 2007 A1
20070069894 Lee Mar 2007 A1
20070083079 Lee Apr 2007 A1
20070108389 Makela May 2007 A1
20070113399 Kumar May 2007 A1
20070123756 Kitajima May 2007 A1
20070139451 Somasiri Jun 2007 A1
20070151358 Chien Jul 2007 A1
20070179373 Pronovost Aug 2007 A1
20070190880 Dubrow Aug 2007 A1
20070196957 Akutagawa Aug 2007 A1
20070215890 Harbers Sep 2007 A1
20070270672 Hayter Nov 2007 A1
20070270674 Kane Nov 2007 A1
20080036097 Ito Feb 2008 A1
20080046080 Vanden Bulcke Feb 2008 A1
20080074383 Dean Mar 2008 A1
20080091089 Guillory Apr 2008 A1
20080096620 Lee Apr 2008 A1
20080139894 Szydlo-Moore Jun 2008 A1
20080157235 Rogers Jul 2008 A1
20080185534 Simon Aug 2008 A1
20080188912 Stone Aug 2008 A1
20080190202 Kulach Aug 2008 A1
20080193749 Thompson Aug 2008 A1
20080200973 Mallozzi Aug 2008 A1
20080204021 Leussler Aug 2008 A1
20080211087 Mueller-Hipper Sep 2008 A1
20080237840 Alcoe Oct 2008 A1
20080259576 Johnson Oct 2008 A1
20080262381 Kolen Oct 2008 A1
20080275327 Faarbaek Nov 2008 A1
20080287167 Caine Nov 2008 A1
20080297350 Iwasa Dec 2008 A1
20080309807 Kinoshita Dec 2008 A1
20080313552 Buehler Dec 2008 A1
20090000377 Shipps Jan 2009 A1
20090001550 Li Jan 2009 A1
20090015560 Robinson Jan 2009 A1
20090017884 Rotschild Jan 2009 A1
20090048556 Durand Feb 2009 A1
20090076363 Bly Mar 2009 A1
20090088750 Hushka Apr 2009 A1
20090107704 Vanfleteren Apr 2009 A1
20090154736 Lee Jun 2009 A1
20090184254 Miura Jul 2009 A1
20090204168 Kallmeyer Aug 2009 A1
20090215385 Waters Aug 2009 A1
20090225751 Koenck Sep 2009 A1
20090261828 Nordmeyer-Massner Oct 2009 A1
20090273909 Shin Nov 2009 A1
20090283891 Dekker Nov 2009 A1
20090291508 Babu Nov 2009 A1
20090294803 Nuzzo Dec 2009 A1
20090317639 Axisa Dec 2009 A1
20090322480 Benedict Dec 2009 A1
20100002402 Rogers Jan 2010 A1
20100030167 Thirstrup Feb 2010 A1
20100036211 La Rue Feb 2010 A1
20100041966 Kang Feb 2010 A1
20100059863 Rogers Mar 2010 A1
20100072577 Nuzzo Mar 2010 A1
20100073669 Colvin Mar 2010 A1
20100087782 Ghaffari Apr 2010 A1
20100090781 Yamamoto Apr 2010 A1
20100090824 Rowell Apr 2010 A1
20100116526 Arora May 2010 A1
20100117660 Douglas May 2010 A1
20100245011 Chatzopoulos Sep 2010 A1
20100254092 Dong Oct 2010 A1
20100271191 De Graff Oct 2010 A1
20100298895 Ghaffari Nov 2010 A1
20100317132 Rogers Dec 2010 A1
20100321161 Isabell Dec 2010 A1
20100327387 Kasai Dec 2010 A1
20110011179 Gustafsson Jan 2011 A1
20110019370 Koh Jan 2011 A1
20110019371 Koh Jan 2011 A1
20110034760 Brynelsen Feb 2011 A1
20110034912 De Graff Feb 2011 A1
20110051384 Kriechbaum Mar 2011 A1
20110054583 Litt Mar 2011 A1
20110071603 Moore Mar 2011 A1
20110098583 Pandia Apr 2011 A1
20110101789 Salter May 2011 A1
20110121822 Parsche May 2011 A1
20110136436 Hoyt Jun 2011 A1
20110140856 Downie Jun 2011 A1
20110140897 Purks Jun 2011 A1
20110175735 Forster Jul 2011 A1
20110184320 Shipps Jul 2011 A1
20110185611 Adams Aug 2011 A1
20110193105 Lerman Aug 2011 A1
20110213559 Pollack Sep 2011 A1
20110215931 Callsen Sep 2011 A1
20110218756 Callsen Sep 2011 A1
20110218757 Callsen Sep 2011 A1
20110220890 Nuzzo Sep 2011 A1
20110221580 Marsanne Sep 2011 A1
20110222375 Tsubata Sep 2011 A1
20110263950 Larson Oct 2011 A1
20110270049 Katra Nov 2011 A1
20110277813 Rogers Nov 2011 A1
20110284268 Palaniswamy Nov 2011 A1
20110306851 Wang Dec 2011 A1
20110317737 Klewer Dec 2011 A1
20120016258 Webster Jan 2012 A1
20120028575 Chen Feb 2012 A1
20120051005 Vanfleteren Mar 2012 A1
20120052268 Axisa Mar 2012 A1
20120065937 De Graff Mar 2012 A1
20120068848 Campbell Mar 2012 A1
20120074546 Chong Mar 2012 A1
20120087216 Keung Apr 2012 A1
20120091594 Landesberger Apr 2012 A1
20120092178 Callsen Apr 2012 A1
20120092222 Kato Apr 2012 A1
20120101413 Beetel Apr 2012 A1
20120101538 Ballakur Apr 2012 A1
20120108012 Yasuda May 2012 A1
20120116382 Ku May 2012 A1
20120126418 Feng May 2012 A1
20120150072 Revol-Cavalier Jun 2012 A1
20120150074 Yanev Jun 2012 A1
20120157804 Rogers Jun 2012 A1
20120165759 Rogers Jun 2012 A1
20120172697 Urman Jul 2012 A1
20120178367 Matsumoto Jul 2012 A1
20120179075 Perry Jul 2012 A1
20120206097 Scar Aug 2012 A1
20120215127 Shikida Aug 2012 A1
20120220835 Chung Aug 2012 A1
20120245444 Otis Sep 2012 A1
20120256308 Helin Oct 2012 A1
20120256492 Song Oct 2012 A1
20120314382 Wesselmann Dec 2012 A1
20120316455 Rahman Dec 2012 A1
20120327608 Rogers Dec 2012 A1
20130035751 Shalev Feb 2013 A1
20130041235 Rogers Feb 2013 A1
20130044215 Rothkopf Feb 2013 A1
20130066365 Belson Mar 2013 A1
20130079693 Ranky Mar 2013 A1
20130085552 Mandel Apr 2013 A1
20130099358 Elolampi Apr 2013 A1
20130100618 Rogers Apr 2013 A1
20130116520 Roham May 2013 A1
20130118255 Callsen May 2013 A1
20130123587 Sarrafzadeh May 2013 A1
20130131660 Monson May 2013 A1
20130147063 Park Jun 2013 A1
20130185003 Carbeck Jul 2013 A1
20130192356 De Graff Aug 2013 A1
20130197319 Monty Aug 2013 A1
20130200268 Rafferty Aug 2013 A1
20130211322 Degen Aug 2013 A1
20130211761 Brandsma Aug 2013 A1
20130214300 Lerman Aug 2013 A1
20130215467 Fein Aug 2013 A1
20130237150 Royston Sep 2013 A1
20130245387 Patel Sep 2013 A1
20130245388 Rafferty Sep 2013 A1
20130253285 Bly Sep 2013 A1
20130261415 Ashe Oct 2013 A1
20130261464 Singh Oct 2013 A1
20130285836 Proud Oct 2013 A1
20130313713 Arora Nov 2013 A1
20130316442 Meurville Nov 2013 A1
20130316487 De Graff Nov 2013 A1
20130316645 Li Nov 2013 A1
20130320503 Nuzzo Dec 2013 A1
20130321373 Yoshizumi Dec 2013 A1
20130325357 Walerow Dec 2013 A1
20130328219 Chau Dec 2013 A1
20130331914 Lee Dec 2013 A1
20130335011 Bohringer Dec 2013 A1
20140001058 Ghaffari Jan 2014 A1
20140002242 Fenkanyn Jan 2014 A1
20140012160 Ghaffari Jan 2014 A1
20140012242 Lee Jan 2014 A1
20140022746 Hsu Jan 2014 A1
20140039290 De Graff Feb 2014 A1
20140097944 Fastert Apr 2014 A1
20140110859 Rafferty Apr 2014 A1
20140125458 Bachman May 2014 A1
20140140020 Rogers May 2014 A1
20140188426 Fastert Jul 2014 A1
20140191236 Nuzzo Jul 2014 A1
20140206976 Thompson Jul 2014 A1
20140216524 Rogers Aug 2014 A1
20140275835 Lamego Sep 2014 A1
20140303452 Ghaffari Oct 2014 A1
20140303520 Telfort Oct 2014 A1
20140303680 Donnelly Oct 2014 A1
20140308930 Tran Oct 2014 A1
20140316191 De Zambotti Oct 2014 A1
20140340857 Hsu Nov 2014 A1
20140342174 Tominaga Nov 2014 A1
20140350883 Carter Nov 2014 A1
20140371547 Gartenberg Dec 2014 A1
20140371823 Mashiach Dec 2014 A1
20140374872 Rogers Dec 2014 A1
20140375465 Fenuccio Dec 2014 A1
20150001462 Rogers Jan 2015 A1
20150019135 Kacyvenski Jan 2015 A1
20150025394 Hong Jan 2015 A1
20150035743 Rosener Feb 2015 A1
20150100135 Ives Apr 2015 A1
20150116814 Takakura Apr 2015 A1
20150126878 An May 2015 A1
20150150505 Kaskoun Jun 2015 A1
20150161342 Takakura Jun 2015 A1
20150164377 Nathan Jun 2015 A1
20150178806 Nuzzo Jun 2015 A1
20150181700 Rogers Jun 2015 A1
20150194817 Lee Jul 2015 A1
20150237711 Rogers Aug 2015 A1
20150241288 Keen Aug 2015 A1
20150248833 Arne Sep 2015 A1
20150272652 Ghaffari Oct 2015 A1
20150335254 Fastert Nov 2015 A1
20150359469 Jacobs Dec 2015 A1
20150371511 Miller Dec 2015 A1
20150373487 Miller Dec 2015 A1
20160006123 Li Jan 2016 A1
20160015962 Shokoueinejad Maragheh Jan 2016 A1
20160037478 Skaaksrud Feb 2016 A1
20160058324 Cao Mar 2016 A1
20160058380 Lee Mar 2016 A1
20160066854 Mei Mar 2016 A1
20160086909 Garlock Mar 2016 A1
20160095652 Lee Apr 2016 A1
20160099214 Dalal Apr 2016 A1
20160099227 Dalal Apr 2016 A1
20160111353 Rafferty Apr 2016 A1
20160135740 Ghaffari May 2016 A1
20160178251 Johnson Jun 2016 A1
20160213262 Ghaffari Jul 2016 A1
20160213424 Ghaffari Jul 2016 A1
20160228640 Pindado Aug 2016 A1
20160232807 Ghaffari Aug 2016 A1
20160240061 Li Aug 2016 A1
20160249174 Patel Aug 2016 A1
20160256070 Murphy Sep 2016 A1
20160261151 Kim Sep 2016 A1
20160271290 Humayun Sep 2016 A1
20160284544 Nuzzo Sep 2016 A1
20160287177 Huppert Oct 2016 A1
20160293794 Nuzzo Oct 2016 A1
20160309594 Hsu Oct 2016 A1
20160322283 McMahon Nov 2016 A1
20160331232 Love Nov 2016 A1
20160336804 Son Nov 2016 A1
20160338646 Lee Nov 2016 A1
20160361015 Wang Dec 2016 A1
20160371957 Ghaffari Dec 2016 A1
20160381789 Rogers Dec 2016 A1
20170011210 Cheong Jan 2017 A1
20170019988 McGrane Jan 2017 A1
20170049397 Sun Feb 2017 A1
20170071491 Litt Mar 2017 A1
20170079588 Ghaffari Mar 2017 A1
20170079589 Ghaffari Mar 2017 A1
20170083312 Pindado Mar 2017 A1
20170086747 Ghaffari Mar 2017 A1
20170086748 Ghaffari Mar 2017 A1
20170086749 Ghaffari Mar 2017 A1
20170095670 Ghaffari Apr 2017 A1
20170095732 Ghaffari Apr 2017 A1
20170105795 Lee Apr 2017 A1
20170110417 Arora Apr 2017 A1
20170164865 Rafferty Jun 2017 A1
20170164866 Rafferty Jun 2017 A1
20170181659 Rafferty Jun 2017 A1
20170186727 Dalal Jun 2017 A1
20170188942 Ghaffari Jul 2017 A1
20170200670 Rafferty Jul 2017 A1
20170200679 Rogers Jul 2017 A1
20170200707 Rogers Jul 2017 A1
20170223846 Elolampi Aug 2017 A1
20170244285 Raj Aug 2017 A1
20170244543 Raj Aug 2017 A1
20170296114 Ghaffari Oct 2017 A1
20170331524 Aranyosi Nov 2017 A1
20170340236 Ghaffari Nov 2017 A1
20180076336 Graff Mar 2018 A1
20180111353 Huppert Apr 2018 A1
20180159361 Cong Jun 2018 A1
20180190704 Graff Jul 2018 A1
20180192918 Ives Jul 2018 A1
20180199884 Huppert Jul 2018 A1
20180205417 Raj Jul 2018 A1
20180293472 Fastert Oct 2018 A1
20180302980 Arora Oct 2018 A1
20180302988 Hsu Oct 2018 A1
20180308799 Dalal Oct 2018 A1
Foreign Referenced Citations (141)
Number Date Country
101084038 Dec 2007 CN
202068986 Dec 2011 CN
102772246 Nov 2012 CN
103165478 Jun 2013 CN
103313671 Sep 2013 CN
103619590 Mar 2014 CN
10 2006 011 596 Sep 2007 DE
10 2006 051 745 May 2008 DE
10 2007 046 886 Apr 2009 DE
10 2008 044 902 Mar 2010 DE
0526855 Feb 1993 EP
0585670 Mar 1994 EP
0779059 Jun 1997 EP
0952542 Oct 1999 EP
1100296 May 2001 EP
1808124 Jul 2007 EP
2259062 Dec 2010 EP
2498196 Sep 2012 EP
2541995 Jan 2013 EP
H 04-290489 Oct 1992 JP
05-087511 Apr 1993 JP
H 05-102228 Apr 1993 JP
9-201338 Aug 1997 JP
H10-155753 Jun 1998 JP
03-218797 Oct 2001 JP
2002-90479 Mar 2002 JP
2002-263185 Sep 2002 JP
2003-046291 Feb 2003 JP
2005-052212 Mar 2005 JP
2006-520657 Sep 2006 JP
2006-523127 Oct 2006 JP
2007-042829 Feb 2007 JP
2007-502136 Feb 2007 JP
2008-194323 Aug 2008 JP
2009-150590 Jul 2009 JP
2009-158839 Jul 2009 JP
2009-170173 Jul 2009 JP
2011-082050 Apr 2011 JP
2011-103914 Jun 2011 JP
2011-122732 Jun 2011 JP
2012-134272 Jul 2012 JP
2012-515436 Jul 2012 JP
2013-089959 May 2013 JP
2013-128060 Jun 2013 JP
2013-130384 Jul 2013 JP
2013-536592 Sep 2013 JP
WO 1999038211 Jul 1999 WO
WO 2002047162 Jun 2002 WO
WO 2003021679 Mar 2003 WO
WO 2004084720 Oct 2004 WO
WO 2005083546 Sep 2005 WO
WO 2005122285 Dec 2005 WO
WO 2006013573 Feb 2006 WO
WO 2007003019 Jan 2007 WO
WO 2007024983 Mar 2007 WO
WO 2007116344 Oct 2007 WO
WO 2007136726 Nov 2007 WO
WO 2008030960 Mar 2008 WO
WO 2008055212 May 2008 WO
WO 2008143635 Nov 2008 WO
WO 2009036260 Mar 2009 WO
WO 2009111641 Sep 2009 WO
WO 2009114689 Sep 2009 WO
WO 2010029966 Mar 2010 WO
WO 2010036807 Apr 2010 WO
WO 2010042653 Apr 2010 WO
WO 2010042957 Apr 2010 WO
WO 2010046883 Apr 2010 WO
WO 2010056857 May 2010 WO
WO 2010081137 Jul 2010 WO
WO 2010082993 Jul 2010 WO
WO 2010102310 Sep 2010 WO
WO 2010132552 Nov 2010 WO
WO 2011003181 Jan 2011 WO
WO 2011041727 Apr 2011 WO
WO 2011084450 Jul 2011 WO
WO 2011084709 Jul 2011 WO
WO 2011124898 Oct 2011 WO
WO 2011127331 Oct 2011 WO
WO 2012094264 Jul 2012 WO
WO 2012125494 Sep 2012 WO
WO 2012166686 Dec 2012 WO
WO 2013010171 Jan 2013 WO
WO 2013022853 Feb 2013 WO
WO 2013033724 Mar 2013 WO
WO 2013034987 Mar 2013 WO
WO 2013049716 Apr 2013 WO
WO 2013052919 Apr 2013 WO
WO 2013059671 Apr 2013 WO
WO 2013063634 May 2013 WO
WO 2013144738 Oct 2013 WO
WO 2013144866 Oct 2013 WO
WO 2013170032 Nov 2013 WO
WO 2014007871 Jan 2014 WO
WO 2014058473 Apr 2014 WO
WO 2014059032 Apr 2014 WO
WO 2014106041 Jul 2014 WO
WO 2014110176 Jul 2014 WO
WO 2014124044 Aug 2014 WO
WO 2014124049 Aug 2014 WO
WO 2014130928 Aug 2014 WO
WO 2014130931 Aug 2014 WO
WO 2014179343 Nov 2014 WO
WO 2014186467 Nov 2014 WO
WO 2014197443 Dec 2014 WO
WO 2014205434 Dec 2014 WO
WO 2015021039 Feb 2015 WO
WO 2015054312 Apr 2015 WO
WO 2015077559 May 2015 WO
WO 2015080991 Jun 2015 WO
WO 2015102951 Jul 2015 WO
WO 2015103483 Jul 2015 WO
WO 2015103580 Jul 2015 WO
WO 2015127458 Aug 2015 WO
WO 2015134588 Sep 2015 WO
WO 2015138712 Sep 2015 WO
WO 2015145471 Oct 2015 WO
WO 2015159280 Oct 2015 WO
WO 2016010983 Jan 2016 WO
WO 2016025430 Feb 2016 WO
WO 2016048888 Mar 2016 WO
WO 2016054512 Apr 2016 WO
WO 2016057318 Apr 2016 WO
WO 2016081244 May 2016 WO
WO 20160127050 Aug 2016 WO
WO 2016134306 Aug 2016 WO
WO 2016-140961 Sep 2016 WO
WO 2016205385 Dec 2016 WO
WO 2017015000 Jan 2017 WO
WO 2017059215 Apr 2017 WO
WO 2017062508 Apr 2017 WO
WO 2017184705 Oct 2017 WO
WO 2018013569 Jan 2018 WO
WO 2018013656 Jan 2018 WO
WO 2018057911 Mar 2018 WO
WO 2018081778 May 2018 WO
WO 2018085336 May 2018 WO
WO 2018093751 May 2018 WO
WO 2018119193 Jun 2018 WO
WO 2018136462 Jul 2018 WO
WO 2018208523 Nov 2018 WO
Non-Patent Literature Citations (33)
Entry
Carvalhal et al., “Electrochemical Detection in a Paper-Based Separation Device”, Analytical Chemistry, vol. 82, No. 3, (1162-1165) (4 pages) (Jan. 7, 2010).
Demura et al., “Immobilization of Glucose Oxidase with Bombyx mori Silk Fibroin by Only Stretching Treatment and its Application to Glucose Sensor,” Biotechnology and Bioengineering, vol. 33, 598-603 (6 pages) (1989).
Ellerbee et al., “Quantifying Colorimetric Assays in Paper-Based Microfluidic Devices by Measuring the Transmission of Light through Paper,” Analytical Chemistry, vol. 81, No. 20 8447-8452, (6 pages) (Oct. 15, 2009).
Halsted, “Ligature and Suture Material,” Journal of the American Medical Association, vol. LX, No. 15, 1119-1126, (8 pages) (Apr. 12, 1913).
Kim et al., “Complementary Metal Oxide Silicon Integrated Circuits Incorporating Monolithically Integrated Stretchable Wavy Interconnects,” Applied Physics Letters, vol. 93, 044102-044102.3 (3 pages) (Jul. 31, 2008).
Kim et al., “Dissolvable Films of Silk Fibroin for Ultrathin Conformal Bio-Integrated Electronics,” Nature, 1-8 (8 pages) (Apr. 18, 2010).
Kim et al., “Materials and Noncoplanar Mesh Designs for Integrated Circuits with Linear Elastic Responses to Extreme Mechanical Deformations,” PNAS, vol. 105, No. 48, 18675-18680 (6 pages) (Dec. 2, 2008).
Kim et al., “Stretchable and Foldable Silicon Integrated Circuits,” Science, vol. 320, 507-511 (5 pages) (Apr. 25, 2008).
Kim et al., “Electrowetting on Paper for Electronic Paper Display,” ACS Applied Materials & Interfaces, vol. 2, No. 11, (3318-3323) (6 pages) (Nov. 24, 2010).
Ko et al., “A Hemispherical Electronic Eye Camera Based on Compressible Silicon Optoelectronics,” Nature, vol. 454, 748-753 (6 pages) (Aug. 7, 2008).
Lawrence et al., “Bioactive Silk Protein Biomaterial Systems for Optical Devices,” Biomacromolecules, vol. 9, 1214-1220 (7 pages) (Nov. 4, 2008).
Meitl et al., “Transfer Printing by Kinetic Control of Adhesion to an Elastomeric Stamp,” Nature, vol. 5, 33-38 (6 pages) (Jan. 2006).
Omenetto et al., “A New Route for Silk,” Nature Photonics, vol. 2, 641-643 (3 pages) (Nov. 2008).
Omenetto et al., “New Opportunities for an Ancient Material,” Science, vol. 329, 528-531 (5 pages) (Jul. 30, 2010).
Siegel et al., “Foldable Printed Circuit Boards on Paper Substrates,” Advanced Functional Materials, vol. 20, No. 1, 28-35, (8 pages) (Jan. 8, 2010).
Tsukada et al., “Structural Changes of Silk Fibroin Membranes Induced by Immersion in Methanol Aqueous Solutions,” Journal of Polymer Science, vol. 32, 961-968 (8 pages) (1994).
Wang et al., “Controlled Release From Multilayer Silk Biomaterial Coatings to Modulate Vascular Cell Responses” Biomaterials, 29, 894-903 (10 pages) (Nov. 28, 2008).
Wikipedia, “Ball bonding” article [online]. Cited in PCT/US2015/051210 search report dated Mar. 1, 2016 with the following information “Jun. 15, 2011 [retrieved on Nov. 15, 2015}. Retrieved 12-18, 29 from the Internet: <URL: https://web.archive.org/web/20110615221003/http://en.wikipedia.org/wiki/Ball_bonding>., entire document, especially para 1, 4, 5, 6,” 2 pages, last page says (“last modified on May 11, 2011”).
Bossuyt et al., “Stretchable Electronics Technology for Large Area Applications: Fabrication and Mechanical Characterizations”, vol. 3, pp. 229-235 (7 pages) (Feb. 2013).
Jones et al., “Stretchable Interconnects for Elastic Electronic Surfaces”. vol. 93, pp. 1459-1467 (9 pages) (Aug. 2005).
Lin et al., “Design and Fabrication of Large-Area, Redundant, Stretchable Interconnect Meshes Using Excimer Laser Photoablation and In Situ Masking”, (10 pages) (Aug. 2010).
Kim et al., “A Biaxial Stretchable Interconnect With Liquid-Alloy-Covered Joints on Elastomeric Substrate”, vol. 18, pp. 138-146 (9 pages) (Feb. 2009).
Kinkeldi et al., “Encapsulation for Flexible Electronic Devices”, IEE Electron Device Letters, 32(12):1743-5 (2011).
Hsu et al., “Epidermal electronics: Skin sweat patch”, Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT), 2012 7th International. IEEE, 2012.
Siegel et al.,“Foldable printed circuit boards on paper substrates”, Advanced Functional Materials, 20:28-35 (2010).
Ellerbee et al.,“Quantifying colorimetric assays in paper-based microfluidic devices by measuring the transmission of light through paper”, Anal. Chem., 81(20):8447-52 (2009).
Wehner et al.; “A Lightweight Soft Exosuit For Gait Assistance”; IEEE International Conference on Robotics and Automation (ICRA), May 6-10, 2013 Retrieved from https://micro.seas.harvard.edu/papers/Wehner_ICRA13.pdf (8 pages).
Cauwe et al., “Flexible and Stretchable Circuit Technologies for Space Applications,” 5th Electronic Materials, Processes and Packaging for Space, May 20-22, 2014 (18 pages).
Hild, “Surface Energy of Plastics,” Dec. 16, 2009. Retrieved from https://www.tstar.com/blog/bid/33845/surface-energy-of-plastics (3 pages).
Hodge et al., “A Microcolorimetric Method for the Determination of Chloride,” Microchemical Journal, vol. 7, Issue 3, Sep. 30, 1963, pp. 326-330 (5 pages).
Bonifácio et al., “An improved flow system for the chloride determination in natural waters exploiting solid-phase reactor and long pathlength spectrophotometry,” Talanta, vol. 72, Issue 2, Apr. 30, 2007, pp. 663-667 (5 pages).
Meyer et al., “The Effect of Gelatin Cross-Linking on the Bioequivalence of Hard and Soft Gelatin Acetaminophen Capsules,” Pharmaceutical Research, vol. 17, No. 8, Aug. 31, 2000, pp. 962-966 (5 pages).
Bang et al.; “The Smart House for Older Persons and Persons With Disabilities: Structure, Technology Arrangements, and Perspectives”; IEEE Transactions on Neural Systems and Rehabilitation Engineering, IEEE Service Center, New York, New York; vol. 12, No. 2, pp. 228-250; Jun. 1, 2004; XP011113818; ISSN: 1534-4320 (23 pages).
Related Publications (1)
Number Date Country
20180205417 A1 Jul 2018 US
Provisional Applications (1)
Number Date Country
62374510 Aug 2016 US