The invention relates to medical devices, and more particularly, to medical devices used for chronic therapy provision.
A variety of types of medical devices are used for chronic, e.g., long-term, provision of therapy to patients. As examples, pulse generators are used for chronic provision of cardiac pacing and neurostimulation therapies, and pumps are used for chronic delivery of therapeutic agents, such as drugs. Typically, such devices provide therapy continuously or periodically according to parameters, e.g., a program, specified by a clinician.
In some cases, the patient is allowed to activate and/or modify the therapy. For example, the symptoms, e.g., the intensity of pain, of patients who receive spinal cord stimulation (SCS) therapy may vary over time based on the activity level or posture of the patient, the specific activity undertaken by the patient, or the like. For this reason, a patient who receives SCS therapy from an implantable medical device (IMD), e.g., an implantable pulse generator, is often given a patient programming device that communicates with his IMD via device telemetry, and allows the patient to activate and/or adjust the intensity of the delivered neurostimulation.
In general, the invention is directed to techniques for providing automatic adjustments to a therapy. A medical device, such as an implanted medical device (IMD) for delivering a therapy or a programming device, automatically adjusts delivery of the therapy in response to detecting a previously defined event. By automatically adjusting therapy in response to detecting a previously defined event, the medical device can automatically provide appropriate therapy to address changes in the symptoms of a patient, and/or changes in the efficacy or side effects of the therapy associated with the event. The medical device may deliver neurostimulation therapy, and an event may be an activity and/or posture undertaken by the patient, such as running or sitting in a chair, which will likely impact the type or level of symptoms and/or the paresthesia experienced by the patient.
In exemplary embodiments, the medical device enters a learning mode in response to a command received from a user, e.g., the patient. In such embodiments, the medical device defines the event, collects the therapy information, and associates the therapy information with the defined event while operating in the learning mode. In some embodiments, the medical device defines the event based on an indication of the event received from the user. In other embodiments, the medical device defines the event based on the output of a sensor that indicates the activity, posture, or a physiological parameter of the patient during the learning mode. The sensor may be an accelerometer, which generates an output that reflects motion and/or posture of the patient. The medical device may collect therapy information by recording values of one or more therapy parameters, such as pulse amplitude, width and rate, and/or changes made to the parameters by the user during the learning mode.
When a patient undertakes certain activities and/or postures, the patient may experience an uncomfortable increase in the intensity of the neurostimulation delivered by a medical device. This phenomenon is referred to as a “jolt.” Some of the events detected by the medical device may correspond to a jolt. In response to detecting these events, the medical device may suspend delivery of neurostimulation therapy for a period of time, which may advantageously allow the medical device avoid providing uncomfortable stimulation to the patient.
In one embodiment, the invention is directed to a method in which a command to enter a learning mode is received from a user. An event is defined, and therapy information is associated with the defined event, in response to the command. The defined event is subsequently detected, and therapy is provided to a patient via a medical device according to the therapy information in response to the detection.
In another embodiment, the invention is directed to a medical device that comprises a memory and a processor. The processor receives a command to enter a learning mode from a user, and defines an event and associates therapy information with the defined event within the memory in response to the command. The processor subsequently detects the event, and controls delivery of therapy to a patient according to the therapy information in response to the detection.
In another embodiment, the invention is directed to a computer-readable medium containing instructions. The instructions cause a programmable processor to receive a command from a user to enter a learning mode, and define and event and associate therapy information with the defined event in response to the command. The computer-readable medium further comprises instructions that cause a programmable processor to subsequently detect the defined event, and control delivery of therapy to a patient via a medical device according to the therapy information in response to the detection.
The invention may provide advantages. For example, by automatically adjusting therapy in response to a detected event, a medical device can provide therapy that better addresses changes in the symptoms of a patient and/or level of efficacy or side effects of the therapy associated with an activity undertaken by the patient. The medical device may automatically provide the appropriate therapy for frequently occurring events, e.g., activities that the patient frequently undertakes, allowing the patient to avoid having to manually adjust the therapy each time the event occurs. Manual adjustment of stimulation parameters can be tedious, requiring the patient to, for example, depress one or more keys of a keypad of a patient programmer multiple times during the event to maintain adequate symptom control. Instead, according to the invention, the patient may perform such adjustments a single time during a learning mode, and the medical device may automatically provide the adjustments during subsequent occurrences of the event.
The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.
IMD 12 delivers neurostimulation therapy to patient 14 via leads 16A and 16B (collectively “leads 16”). Leads 16 may, as shown in
In exemplary embodiments, IMD 12 delivers therapy to patient 14 according to a program. A program includes one or more parameters that define an aspect of the therapy delivered by the medical device according to that program. For example, a program that controls delivery of neurostimulation by IMD 12 may define a voltage or current pulse amplitude, a pulse width, a pulse rate, for stimulation pulses delivered by IMD 12 according to that program. Further, each of leads 16 includes electrodes (not shown in
In the illustrated example, system 10 also includes a programming device 20, which is a medical device, and may, as shown in
Programming device 20 may, as shown in
In exemplary embodiments, programming device 20 is a patient programmer used by patient 14 to control the delivery of neurostimulation therapy by IMD 12. Patient 14 may use programming device 20 to activate or deactivate neurostimulation therapy. Patient 14 may also use programming device 20 to adjust one or more program parameters, e.g., adjust the amplitude, width, or rate of delivered stimulation pulse. Where more than one program is available to IMD 12 for delivery of neurostimulation to patient 14, patient 14 may use programming device 20 to select from among the available programs. The programs available for selection by patient 14 may be stored in either of IMD 12 and programming device 20.
As will be described in greater detail below, one or both of IMD 12 and programming device 20 provide automatic adjustment of the therapy delivered by IMD 12 according to the invention. Specifically, one of IMD 12 and programming device 20 detects a previously defined event, and the delivery of therapy by IMD 12 is automatically adjusted according to therapy information stored in association with defined event. In exemplary embodiments, the one of IMD 12 and programming device 20 may make automatic adjustments to the therapy over a period of time in response to detection of the previously defined event, e.g., provide a series of therapy adjustments defined by the therapy information associated with the event. By automatically adjusting therapy in response to a detected event, system 10 can provide therapy that better addresses changes in the symptoms of patient 14 associated with the event.
For ease of description, the provision of automatic therapy adjustment will be described hereinafter primarily with reference to embodiments in which IMD 12 provides automatic therapy adjustments. However, it is understood that both of IMD 12 and programming device 20 are medical devices capable of providing automatic therapy adjustments according to the invention.
In exemplary embodiments, IMD 12 provides a learning mode. IMD 12 may enter the learning mode in response to a command received from a user. For example, patient 14 may direct IMD 12 to enter the learning mode via keypad 24 of patient programmer 20.
When operating in the learning mode, IMD 12 defines events and associates therapy information with the events. In some embodiments, IMD 12 defines the event based on the indication of the event to IMD 12 by a user. In such embodiments, IMD 12 later detects the event by receiving the indication from the user, and automatically adjusts therapy according to information stored in association with that indication, e.g., with the event.
For example, patient 14 may indicate the occurrence of an event to IMD 12 via keypad 24 of patient programmer 20. In some embodiments, a particular key of keypad 24 is associated with the event. The event may correspond to an activity undertaken by patient 14, such as running, golfing, taking medication, sleeping, or a particular activity related to an occupation of patient 14. A first time patient 14 undertakes the activity, the activity, e.g., event, may be associated with a key of keypad 24. Subsequent times patient 14 undertakes the activity, patient 14 may press the key to cause IMD 12 to provide therapy adjustment according to therapy information associated with depression of the key.
In other embodiments, IMD 12 defines the event based on the output of a sensor (not shown in
The output of the sensor may reflect motion, posture, and/or one or more physiological parameters of patient 14. Consequently, events defined by IMD 12 based on the sensor output may correspond to an activity undertaken by patient 14. For example, patient 14 may direct IMD 12 to enter the learning mode via patient programmer 20 when patient 14 is about to undertake an activity, such as running IMD 12 may record the output of the sensor in response to the command, and, when no longer in the learning mode, use the recorded exemplar to detect when patient 14 is running so as to automatically provide an appropriate therapy adjustment according to therapy information stored in association with the exemplar.
IMD 12 may associate therapy information with the defined event while operating in the learning mode, and provide therapy, e.g., automatically adjusts the therapy, according to the therapy information in response to subsequent detection of the defined event. The therapy information may be the values of one or more parameters, e.g., pulse amplitude, pulse width, or pulse rate, recorded by IMD 12 upon entering, or at some point after entering, the learning mode. The therapy information may be a change to a parameter made by a user while IMD 12 is operating in the learning mode. In exemplary embodiments, IMD 12 records a series of changes made to parameters by the user over a period of time while IMD 12 is operating in the learning mode.
For example, patient 14 may direct IMD 12 to enter the learning mode so that IMD 12 will learn the appropriate adjustment or adjustments to make to the stimulation parameters while patient 14 is running. Patient 14 may indicate the occurrence of the event to IMD 12, e.g., may associate a key of keypad 24 with the activity of running, or may simply begin running and allow IMD 12 to record an exemplar of the sensor output while patient 14 is running. In any case, while patient 14 is running during the learning mode, patient 14 uses programming device 20, e.g., keypad 24, to change one or more stimulation parameters in an attempt to maintain adequate symptom control during the activity. IMD 12 may record the value of the parameters when patient 14 indicates satisfaction, or the one or more changes made by patient 14 over a period of time while running IMD 12 stores the values or a recording of the changes over the time period in association with the event, and, when no longer operating in the learning mode, delivers therapy according to the therapy information upon subsequently detecting that patient 14 is running.
By associating therapy information with defined events, IMD 12 may automatically provide appropriate therapy to patient 14 for frequently occurring events, e.g., activities that patient 14 frequently undertakes. By providing therapy adjustments automatically, IMD 12 may allow patient 14 to avoid having to manually adjust the therapy each time the event occurs. Such manual adjustment of stimulation parameters can be tedious, requiring patient 14 to, for example, depress one or more keys of keypad 24 multiple times during the event to maintain adequate symptom control. Instead, according to the invention, patient 14 may perform such adjustments a single time during the learning mode, and IMD 12 may automatically provide the adjustments during subsequent occurrences of the event.
Electrodes 30 are electrically coupled to a therapy delivery circuit 32 via leads 16. Therapy delivery circuit 32 may, for example, include an output pulse generator coupled to a power source such as a battery. Therapy delivery circuit 32 may deliver electrical pulses to patient 14 via at least some of electrodes 30 under the control of a processor 34.
Processor 34 may control therapy delivery circuit 32 to deliver neurostimulation therapy according to a selected program. Specifically, processor 34 may control circuit 32 to deliver electrical pulses with the amplitudes and widths, and at the rates specified by the program. Processor 34 may also control therapy delivery circuit 32 to deliver the pulses via a selected subset of electrodes 40 with selected polarities, as specified by the program.
Processor 34 may also provide a learning mode of IMD 12 as described above. Specifically, processor 34 may receive commands from a user to enter the learning mode, may define an event during the learning mode, and may associate therapy information with the defined event within memory 36, as described above. When processor 34 is no longer operating in the learning mode, processor 34 and/or monitor 42 may detect previously defined events, and control therapy delivery circuit 32 to deliver therapy via at least some of electrodes 30 as indicated by the associated therapy information. Specifically, processor 34 may control therapy delivery circuit to deliver stimulation pulses with the amplitude, width, and rate indicated by the therapy information, and, in some embodiments, may control therapy delivery circuit to adjust the amplitude, width, and/or rate over time as indicated by the therapy information.
IMD 12 also includes a telemetry circuit 38 that allows processor 34 to communicate with programming device 20. Processor 34 may receive program selections, commands to enter a learning mode, indications of events, and adjustments to therapy made by a user, e.g., patient 14, using programming device 20 via telemetry circuit 38. In some embodiments, as will be described in greater detail below, processor 34 communicates with a clinician programmer to provide diagnostic information stored in memory 36 to a clinician via telemetry circuit 38. Telemetry circuit 38 may correspond to any telemetry circuit known in the implantable medical device arts.
In exemplary embodiments, as described above, IMD 12 includes a sensor 40, and processor 34 defines events based on the output of sensor 40. Sensor 40 is a sensor that generates an output based on motion, posture, and/or one or more physiological parameters of patient 14. In exemplary embodiments, sensor 40 is an accelerometer, such as a piezoresistive and/or micro-electro-mechanical accelerometer.
In some embodiments, IMD 12 includes an activity/posture monitor 42 that processes the analog output of sensor 40 to provide digital activity and/or posture information to processor 34. For example, where sensor 40 comprises a piezoresistive accelerometer, monitor 42 may process the raw signal provided by sensor 40 to provide activity counts to processor 34. In some embodiments, IMD 12 includes multiple sensors oriented along various axes, or sensor 40 comprises a single multi-axis, e.g., three-axis, accelerometer. In such embodiments, monitor 42 may process the signals provided by the one or more sensors 40 to provide velocity of motion information for each direction to processor 34.
In exemplary embodiments, the one or more sensors 40 are housed within a housing (not shown) of IMD 12. However, the invention is not so limited. In some embodiments, one or more sensors 40 are coupled to monitor 42 housed within IMD 12 via additional leads 16 (not shown). Such sensors may be located anywhere within patient 14. In some embodiments, IMD 12 may include multiple accelerometer sensors 40 located at various positions within patient 14 or on the external surface of patient 14, and processor 34 may receive more detailed information about the posture of and activity undertaken by patient 14. For example, accelerometer sensors 40 may be located within the torso and at a position within a limb, e.g. a leg, of patient 14.
Sensors 40 may be coupled to a single monitor 42, or IMD 12 may include multiple monitors 42 coupled to one or more sensors 40. Further, the invention is not limited to embodiments of IMD 12 that include a monitor 42. Rather, sensors 40 may be coupled directly to processor 34, which may include an analog-to-digital converter, and perform the functions attributed to monitor 42. In some embodiments, sensors located external to patient 12 may communicate wirelessly with processor 34, either directly or via programming device 20. In some embodiments, one or more sensors 40 may be included as part of or coupled to programming device 20.
Moreover, the invention is not limited to embodiments where sensors 40 are accelerometers. In some embodiments, one or more sensors 40 may take the form of, for example, a thermistor, a pressure transducer, or electrodes to detect thoracic impedance or an electrogram. Such sensors 40 may be appropriately positioned within or on an external surface of patient 14 to measure a physiological parameter of patient 14, such as a skin temperature, an arterial or intracardiac pressure, a respiration rate, a heart rate, or a Q-T interval of patient 14. In such embodiments, one or more monitor circuits 42 may provide appropriate circuitry to process the signals generated by such sensors, and to provide values of the physiological parameter to processor 34.
Processor 34 may include a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), discrete logic circuitry, or the like. Memory 38 may include program instructions that, when executed by processor 34, cause IMD 12 to perform the functions ascribed to IMD 12 herein. Memory 36 may include any volatile, non-volatile, magnetic, optical, or electrical media, such as a random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically-erasable programmable ROM (EEPROM), flash memory, and the like.
Memory 38 stores events 52 defined by processor 34 during operation in the learning mode, and learned therapies 54, i.e., the therapy information collected during operation in the learning mode. As described above, an event 52 may be information describing an event indication received from a user, e.g., patient 14 (
In some embodiments, as described above, processor 34 defines events 52 based on the output of one or more sensors 40. Processor 34 may store one or more sample of the output of sensor 40 and/or monitor 42 collected while operating in the learning mode as an event, or one or more results of an analysis such samples. For example, processor 34 may store information related to the detection of features within the one or more samples, such as peaks, zero-crossings, or the like, or the results of a Fourier or wavelet analysis of the one or more samples as a defined event 52.
As described above, learned therapies 54 comprises information describing values of stimulation parameters and/or information describing one or more changes to parameters made by a user while processor 34 is operating in the learning mode. In exemplary embodiments, a learned therapy 54 comprises information describing initial parameter values and changes to be made to some or all of the parameter values over a period of time. In such embodiments, the learned therapy may include time values associated with parameter values, so that processor 34 may direct changes to parameter values at appropriate times. Memory 36 maintains associations between events 52 and corresponding learned therapies 54.
Processor 34 may also collect diagnostic information 56 and store diagnostic information 56 within memory 36 for future retrieval by a clinician. Diagnostic information 56 may, for example, include selected recordings of the output of sensor 40 and/or of therapy changes made by patient 14. In exemplary embodiments, diagnostic information 56 includes information identifying the time at which defined events occurred, either during operation in a learning mode or as subsequently detected by processor 34. Diagnostic information 56 may include other information or events indicated by patient 14 outside of learning mode using programming device 20, such as changes in symptoms, taking medication, or other activities undertaken by patient 14 for which patient 14 does not wish IMD 12 to learn a therapy. A clinician programming device (not shown in FIGS.) may present diagnostic information 56 to a clinician in a variety of forms, such as timing diagrams, or a graph resulting from statistical analysis of diagnostic information 56, e.g., a bar graph.
Programming device 20 also includes a telemetry circuit 64 that allows processor 60 to communicate with IMD 12. In exemplary embodiments, processor 60 communicates commands, indications, and therapy changes made by patient 14 via user interface 62 to IMD 12 via telemetry circuit 64. Telemetry circuit 64 may correspond to any telemetry circuit known in the implantable medical device arts.
Programming device also includes a memory 66. In some embodiments, memory 66, rather than memory 36 of IMD 12, may store programs 50 that are available to be selected by patient 14 for delivery of neurostimulation therapy. Memory 66 may also include program instructions that, when executed by processor 60, cause programming device 20 to perform the functions ascribed to programming device 20 herein. Memory 66 may include any volatile, non-volatile, fixed, removable, magnetic, optical, or electrical media, such as a RAM, ROM, CD-ROM, hard disk, removable magnetic disk, memory cards or sticks, NVRAM, EEPROM, flash memory, and the like.
When operating in the learning mode, processor 34 defines an event 52 by receiving an indication from patient 14 (72). Patient 14 may indicate the event by, for example, pressing a key of keypad 24 that patient will thereafter use to identify the event to processor 34. The event 52 may be an activity and/or posture to be undertaken by patient 14, and the key may be used by patient 14 in the future to indicate to processor 34 that patient 14 is about to undertake the activity. Processor 34 may store information identifying the signal received by via telemetry circuit 38 when patient presses the key as the event 52 within memory 36.
Processor 34 then records therapy information, e.g., a learned therapy 54, while operating in the learning mode (74). As described above, the learned therapy 54 may be stimulation parameter values and/or one or more changes made to stimulation parameters by patient 14 over a period of time during operation within the learning mode. Processor 34 may store therapy information as a learned therapy at any time after receiving the command to enter the learning mode, e.g., before or after receiving an indication of the event from patient 14. Processor 34 stores the learned therapy 54 within memory 36, and associates the learned therapy 54 with the defined event 52 within memory 36 (76).
In exemplary embodiments, patient 14 adjusts stimulation parameters over a period of time after directing IMD 12 to enter the learning mode, e.g., during the event. For example, patient 14 may direct IMD 12 to enter the learning mode, so that IMD 12 learns appropriate adjustments to therapy to provide while patient 14 is running, and may adjust stimulation parameters while running to maintain effective and comfortable neuro stimulation therapy. IMD 12 may store the stimulation parameters and/or changes to the stimulation parameters and associate times with the parameters or changes, so that stimulation according to the parameters and changes to the stimulation may be provided at appropriate times during a subsequent occurrence of patient 14 running.
In other embodiments, rather than IMD 12 recording therapy information over time, patient 14 may use programming device 20 to enter a learned therapy 54 that includes time as a parameter. For example, patient 14 may create a learned therapy 54 for the “running” event that includes increases to pulse amplitude and width at particular time after the event is detected by IMD 12, and/or after N minutes that the event continues to be detected by IMD 12.
While operating in the learning mode, processor 34 records at least one of the output of sensor 40 or the information provided by monitor circuit 42 based on the sensor output (82). Processor 34 may record the sensor output or information over any length of time, may record multiple samples, and may make the recording or recordings at any time after entering the learning mode. Processor 34 may store the recording(s), or the result of an analysis, e.g. feature, Fourier, or wavelet, or the recording(s) in memory 36 as an event 52. Processor 34 records therapy information as a learned therapy 54 during operation in the learning mode (84), and associates the learned therapy 54 with the defined event 52 (86), as described above with reference to
If processor 34 detects a previously defined event 52 (92), processor 34 controls therapy delivery circuit 32 to deliver therapy according to the learned therapy 54 associated with the detected event 52 in memory 36 (94). Processor 34 may control circuit 32 to deliver therapy according to parameter values of the learned therapy 54. Processor 34 may also control circuit 32 to change the parameter values over time according to the learned therapy 54.
If processor 34 detects that patient 14 has made changes to stimulation parameters during provision of therapy according to the learned therapy 54 (96), processor 34 may query patient 14 via programming device 20 as to whether the changes should be saved as a modification to the learned therapy 54 (98). If patient 14 wishes to save the changes, processor 34 modifies the learned therapy 54 according to the changes (100).
As described above, an event 52 may be an activity or posture undertaken by patient 14. For example, an event 52 may be patient 14 running, and the learned therapy 54 may include changes to stimulation parameters occurring at associated times during the “running” event such that effective and comfortable therapy is maintained. Other activities and postures that may affect the symptoms experienced by patient 14, or the effectiveness and side effects of the stimulation may include golfing, gardening, driving a car, sitting in a chair, twisting, or bending over. In some cases the duration of a particular activity or posture may affect the symptoms experienced by patient 14, or the effectiveness and side effects of the stimulation. In such cases an event 52 may be defined as occurring after patient 14 maintains an activity or posture for a defined duration.
In some cases, an activity or posture undertaken by patient 14 is results in an uncomfortable increase in the intensity of the stimulation delivered by IMD 12. This phenomenon is referred to as a “jolt.”. Activities and postures that may lead to “jolts” include sitting in a seat, twisting, bending over, rapid posture changes, or other like postures or transitions between postures. Patient 14 may use the learning mode provided by IMD 12 as described herein to cause IMD 12 to define events 52 associated with the activities or postures that lead to “jolts,” and associate such “jolt” events with therapy information 54 that causes IMD 12 to suspend or reduce the intensity of stimulation upon subsequent detection of the “jolt” events. Consequently, embodiments of IMD 12 may advantageously provide efficacious therapy during certain defined events 52, and avoid providing uncomfortable therapy during other defined events 52.
In the illustrated timing diagram, a curve 110 representing the activity level of patient 14, e.g., the output of one or both of sensor 40 and monitor 42, over time is displayed. Markers 112A-E are used to indicate the occurrence of events, which may be defined events 52. A second curve 114 illustrates the symptom, e.g., pain, intensity indicated by patient 14 over time. Curve 114 may be estimated based on intensity values 116A-F periodically entered by patient 14 using programming device 20.
Various embodiments of the invention have been described. However, one skilled in the art will appreciate that various modification may be made to the described embodiments without departing from the scope of the invention. For example, the invention is not limited to medical devices that deliver neurostimulation therapy or to implantable medical devices. Rather, systems that facilitate automatic therapy adjustment according to the invention may include one or more implantable or external medical devices, of any type, that deliver therapy to a patient. For example, in some embodiments, an implantable or external pump that delivers a therapeutic agent to a patient can provide automatic therapy adjustment according to the invention
In some embodiments, a medical device that does not itself deliver therapy, such as a programming device, provides automatic therapy adjustment according to the invention. In such embodiments, the programming device may receive a command to enter a learning mode, an indication of an event, and therapy changes from the patient via a keypad, for example. The programming device may include a memory to store defined events and associated therapy information. When the user, e.g., the patient, again indicates occurrence of the event to the programming device via the keypad, the programming device controls a therapy delivery device to deliver therapy according to therapy information associated with the defined event.
The invention is not limited to embodiments wherein a programming device is a patient programmer. For example, in some embodiments, a programming device may be a clinician programmer used by a clinician to, for example, create the programs that control the delivery of therapy by a therapy delivery device. The clinician may use the clinician programmer, during a programming session for example, to cause the clinician programmer or the therapy delivery device to learn therapies for defined events as described herein
In other embodiments, a system that facilitates automatic therapy adjustment does not include a programming device at all. Where a system includes an external medical device that provides therapy to a patient, for example, a user may interact with a user interface provided by the medical device and a programming device may therefore be unnecessary. A user may also interact with an implanted medical device using a magnetic activator, or by tapping over the implanted medical device, which may be detected via an accelerometer, as is known in the art. These and other embodiments are within the scope of the following claims.
This application is a continuation of, and claims priority to, U.S. application Ser. No. 10/691,917 filed Oct. 23, 2003, issued as U.S. Pat. No. 8,396,565 B2 on Mar. 12, 2013, which claims priority to U.S. Provisional Application Ser. No. 60/503,218, filed Sep. 15, 2003, the entire content of both of which are incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
4297685 | Brainard, II | Oct 1981 | A |
4365633 | Loughman | Dec 1982 | A |
4543955 | Schroeppel | Oct 1985 | A |
4550736 | Broughton et al. | Nov 1985 | A |
4566456 | Koning et al. | Jan 1986 | A |
4771780 | Sholder | Sep 1988 | A |
4776345 | Cohen et al. | Oct 1988 | A |
4846180 | Buffet | Jul 1989 | A |
4846195 | Alt | Jul 1989 | A |
5031618 | Mullett | Jul 1991 | A |
5040534 | Mann et al. | Aug 1991 | A |
5040536 | Riff | Aug 1991 | A |
5058584 | Bourgeois | Oct 1991 | A |
5125412 | Thornton | Jun 1992 | A |
5154180 | Blanchet et al. | Oct 1992 | A |
5158078 | Bennett et al. | Oct 1992 | A |
5167229 | Peckham et al. | Dec 1992 | A |
5233984 | Thompson | Aug 1993 | A |
5275159 | Griebel | Jan 1994 | A |
5312446 | Holschbach et al. | May 1994 | A |
5335657 | Terry, Jr. et al. | Aug 1994 | A |
5337758 | Moore et al. | Aug 1994 | A |
5342409 | Mullett | Aug 1994 | A |
5354317 | Alt | Oct 1994 | A |
5425750 | Moberg | Jun 1995 | A |
5476483 | Bornzin et al. | Dec 1995 | A |
5487755 | Snell et al. | Jan 1996 | A |
5513645 | Jacobson et al. | May 1996 | A |
5514162 | Bornzin et al. | May 1996 | A |
5558640 | Pfeiler et al. | Sep 1996 | A |
5562707 | Prochazka et al. | Oct 1996 | A |
5593431 | Sheldon | Jan 1997 | A |
5622428 | Bonnet | Apr 1997 | A |
5628317 | Starkebaum et al. | May 1997 | A |
5643332 | Stein | Jul 1997 | A |
5645053 | Remmers et al. | Jul 1997 | A |
5674258 | Henschel et al. | Oct 1997 | A |
5711316 | Elsberry et al. | Jan 1998 | A |
5716377 | Rise et al. | Feb 1998 | A |
5720770 | Nappholz et al. | Feb 1998 | A |
5732696 | Rapoport et al. | Mar 1998 | A |
5741310 | Wittkampf | Apr 1998 | A |
5782884 | Stotts et al. | Jul 1998 | A |
5814093 | Stein | Sep 1998 | A |
5832932 | Elsberry et al. | Nov 1998 | A |
5833709 | Rise et al. | Nov 1998 | A |
5836989 | Shelton | Nov 1998 | A |
5851193 | Arikka et al. | Dec 1998 | A |
5865760 | Lidman et al. | Feb 1999 | A |
5885471 | Ruben et al. | Mar 1999 | A |
5893883 | Torgerson et al. | Apr 1999 | A |
5895371 | Levitas et al. | Apr 1999 | A |
5904708 | Goedeke | May 1999 | A |
5911738 | Sikorski et al. | Jun 1999 | A |
5913727 | Ahdoot | Jun 1999 | A |
5919149 | Allum | Jul 1999 | A |
5938690 | Law et al. | Aug 1999 | A |
5941906 | Barreras, Sr. et al. | Aug 1999 | A |
5944680 | Christopherson et al. | Aug 1999 | A |
5957957 | Sheldon | Sep 1999 | A |
6027456 | Feler et al. | Feb 2000 | A |
6044297 | Sheldon et al. | Mar 2000 | A |
6083475 | Sikorski et al. | Mar 2000 | A |
6045513 | Stone et al. | Apr 2000 | A |
6059576 | Brann | May 2000 | A |
6081750 | Hoffberg et al. | Jun 2000 | A |
6095991 | Krausman et al. | Aug 2000 | A |
6099479 | Christopherson et al. | Aug 2000 | A |
6102874 | Stone et al. | Aug 2000 | A |
6120467 | Schallhorn | Sep 2000 | A |
6128534 | Park et al. | Oct 2000 | A |
6134459 | Roberts et al. | Oct 2000 | A |
6157857 | Dimpfel | Dec 2000 | A |
6165143 | Van Lummel | Dec 2000 | A |
6216537 | Henschel et al. | Apr 2001 | B1 |
6259948 | Florio et al. | Jul 2001 | B1 |
6280409 | Stone et al. | Aug 2001 | B1 |
6296606 | Goldberg et al. | Oct 2001 | B1 |
6308098 | Meyer | Oct 2001 | B1 |
6308099 | Fox et al. | Oct 2001 | B1 |
6315740 | Singh | Nov 2001 | B1 |
6327501 | Levine et al. | Dec 2001 | B1 |
6341236 | Osorio et al. | Jan 2002 | B1 |
6351672 | Park et al. | Feb 2002 | B1 |
6368284 | Bardy | Apr 2002 | B1 |
6381496 | Meadows et al. | Apr 2002 | B1 |
6393325 | Mann et al. | May 2002 | B1 |
6438408 | Mulligan et al. | Aug 2002 | B1 |
6440090 | Schallhorn | Aug 2002 | B1 |
6449508 | Sheldon et al. | Sep 2002 | B1 |
6459934 | Kadhiresan | Oct 2002 | B1 |
6466821 | Pianca et al. | Oct 2002 | B1 |
6468234 | Van der Loos et al. | Oct 2002 | B1 |
6507757 | Swain et al. | Jan 2003 | B1 |
6514218 | Yamamoto | Feb 2003 | B2 |
6516749 | Salasidis | Feb 2003 | B1 |
6539249 | Kadhiresan et al. | Mar 2003 | B1 |
6547755 | Lippe et al. | Apr 2003 | B1 |
6572557 | Tchou et al. | Jun 2003 | B2 |
6574507 | Bonnet | Jun 2003 | B1 |
6605038 | Teller et al. | Aug 2003 | B1 |
6609031 | Law et al. | Aug 2003 | B1 |
6611783 | Kelly, Jr. et al. | Aug 2003 | B2 |
6620151 | Blischak et al. | Sep 2003 | B2 |
6625493 | Kroll et al. | Sep 2003 | B2 |
6635048 | Ullestad et al. | Oct 2003 | B1 |
6641542 | Cho et al. | Nov 2003 | B2 |
6658292 | Kroll et al. | Dec 2003 | B2 |
6659968 | McClure | Dec 2003 | B1 |
6662047 | Sorensen | Dec 2003 | B2 |
6665558 | Kalgren et al. | Dec 2003 | B2 |
6668188 | Sun et al. | Dec 2003 | B2 |
6687538 | Hrdlicka et al. | Feb 2004 | B1 |
6731984 | Cho et al. | May 2004 | B2 |
6740075 | Lebel et al. | May 2004 | B2 |
6748276 | Daignault, Jr. et al. | Jun 2004 | B1 |
6752766 | Kowallik et al. | Jun 2004 | B2 |
6773404 | Poezevera et al. | Aug 2004 | B2 |
6782315 | Lu et al. | Aug 2004 | B2 |
6817979 | Nihtilä | Nov 2004 | B2 |
6820025 | Bachmann et al. | Nov 2004 | B2 |
6829507 | Lidman et al. | Dec 2004 | B1 |
6832113 | Belalcazar | Dec 2004 | B2 |
6834436 | Townsend | Dec 2004 | B2 |
6853863 | Carter et al. | Feb 2005 | B2 |
6878121 | Krausman et al. | Apr 2005 | B2 |
6884596 | Civelli et al. | Apr 2005 | B2 |
6890306 | Poezevera | May 2005 | B2 |
6895341 | Barrey et al. | May 2005 | B2 |
6922587 | Weinberg | Jul 2005 | B2 |
6923784 | Stein | Aug 2005 | B2 |
6928324 | Park et al. | Aug 2005 | B2 |
6937899 | Sheldon et al. | Aug 2005 | B2 |
6937900 | Pianca et al. | Aug 2005 | B1 |
6945934 | Bardy | Sep 2005 | B2 |
6964641 | Cho et al. | Nov 2005 | B2 |
6975904 | Sloman | Dec 2005 | B1 |
6997882 | Parker et al. | Feb 2006 | B1 |
6999817 | Park et al. | Feb 2006 | B2 |
7016730 | Ternes | Mar 2006 | B2 |
7031772 | Condie | Apr 2006 | B2 |
7043305 | KenKnight et al. | May 2006 | B2 |
7054687 | Andersen | May 2006 | B1 |
7066910 | Bauhahn et al. | Jun 2006 | B2 |
7082333 | Bauhahn | Jul 2006 | B1 |
7092759 | Nehls et al. | Aug 2006 | B2 |
7095424 | Satoh et al. | Aug 2006 | B2 |
7110820 | Tcheng et al. | Sep 2006 | B2 |
7117036 | Florio | Oct 2006 | B2 |
7123967 | Weinberg | Oct 2006 | B2 |
7130681 | Gebhardt et al. | Oct 2006 | B2 |
7130689 | Turcott | Oct 2006 | B1 |
7141026 | Aminian et al. | Nov 2006 | B2 |
7142921 | Mattes et al. | Nov 2006 | B2 |
7149579 | Koh et al. | Dec 2006 | B1 |
7149584 | Koh et al. | Dec 2006 | B1 |
7151961 | Whitehurst et al. | Dec 2006 | B1 |
7155279 | Whitehurst et al. | Dec 2006 | B2 |
7160252 | Cho et al. | Jan 2007 | B2 |
7162304 | Bradley | Jan 2007 | B1 |
7167743 | Heruth et al. | Jan 2007 | B2 |
7167751 | Whitehurst et al. | Jan 2007 | B1 |
7181281 | Kroll | Feb 2007 | B1 |
7189204 | Ni et al. | Mar 2007 | B2 |
7207947 | Koh et al. | Apr 2007 | B2 |
7210240 | Townsend et al. | May 2007 | B2 |
7212862 | Park et al. | May 2007 | B2 |
7214197 | Prass | May 2007 | B2 |
7218964 | Hill et al. | May 2007 | B2 |
7218968 | Condie et al. | May 2007 | B2 |
7221979 | Zhou et al. | May 2007 | B2 |
7231254 | DiLorenzo | Jun 2007 | B2 |
7242983 | Frei et al. | Jul 2007 | B2 |
7252640 | Ni et al. | Aug 2007 | B2 |
7266412 | Stypulkowski | Sep 2007 | B2 |
7308311 | Sorensen et al. | Dec 2007 | B2 |
7313440 | Miesel | Dec 2007 | B2 |
7317948 | King et al. | Jan 2008 | B1 |
7330760 | Heruth et al. | Feb 2008 | B2 |
7366569 | Belalcazar | Apr 2008 | B2 |
7366572 | Heruth et al. | Apr 2008 | B2 |
7387610 | Stahmann | Jun 2008 | B2 |
7389147 | Wahlstrand et al. | Jun 2008 | B2 |
7395113 | Heruth | Jul 2008 | B2 |
7403820 | DiLorenzo | Jul 2008 | B2 |
7406351 | Wesselink | Jul 2008 | B2 |
7415308 | Gerber et al. | Aug 2008 | B2 |
7447545 | Heruth et al. | Nov 2008 | B2 |
7471290 | Wang et al. | Dec 2008 | B2 |
7471980 | Koshiol | Dec 2008 | B2 |
7489970 | Lee et al. | Feb 2009 | B2 |
7491181 | Heruth et al. | Feb 2009 | B2 |
7505815 | Lee et al. | Mar 2009 | B2 |
7519431 | Goetz et al. | Apr 2009 | B2 |
7542803 | Heruth et al. | Jun 2009 | B2 |
7548786 | Lee et al. | Jun 2009 | B2 |
7559901 | Maile | Jul 2009 | B2 |
7572225 | Stahmann | Aug 2009 | B2 |
7577479 | Hartley et al. | Aug 2009 | B2 |
7580752 | Gerber et al. | Aug 2009 | B2 |
7584808 | Dolgin et al. | Sep 2009 | B2 |
7590453 | Heruth | Sep 2009 | B2 |
7590455 | Heruth et al. | Sep 2009 | B2 |
7590481 | Lu et al. | Sep 2009 | B2 |
7591265 | Lee et al. | Sep 2009 | B2 |
7603170 | Hatlestad et al. | Oct 2009 | B2 |
7623919 | Goetz et al. | Nov 2009 | B2 |
7634379 | Noble | Dec 2009 | B2 |
7664546 | Hartley et al. | Feb 2010 | B2 |
7672806 | Tronconi | Mar 2010 | B2 |
7717848 | Heruth et al. | May 2010 | B2 |
7769464 | Gerber et al. | Aug 2010 | B2 |
7792583 | Miesel et al. | Sep 2010 | B2 |
7853322 | Bourget et al. | Dec 2010 | B2 |
7957797 | Bourget et al. | Jun 2011 | B2 |
7957809 | Bourget et al. | Jun 2011 | B2 |
8396565 | Singhal et al. | Mar 2013 | B2 |
20020038137 | Stein | Mar 2002 | A1 |
20020091308 | Kipshidze et al. | Jul 2002 | A1 |
20020107553 | Hill et al. | Aug 2002 | A1 |
20020115939 | Mulligan et al. | Aug 2002 | A1 |
20020165586 | Hill et al. | Nov 2002 | A1 |
20020169485 | Pless | Nov 2002 | A1 |
20020170193 | Townsend et al. | Nov 2002 | A1 |
20030004423 | Lavie et al. | Jan 2003 | A1 |
20030036783 | Bauhahn et al. | Feb 2003 | A1 |
20030045910 | Sorensen et al. | Mar 2003 | A1 |
20030065370 | Lebel et al. | Apr 2003 | A1 |
20030088185 | Prass | May 2003 | A1 |
20030149457 | Tcheng et al. | Aug 2003 | A1 |
20030171791 | KenKnight et al. | Sep 2003 | A1 |
20030181960 | Carter et al. | Sep 2003 | A1 |
20030204211 | Condie et al. | Oct 2003 | A1 |
20040015103 | Aminian et al. | Jan 2004 | A1 |
20040049132 | Barron et al. | Mar 2004 | A1 |
20040088020 | Condie et al. | May 2004 | A1 |
20040102814 | Sorensen et al. | May 2004 | A1 |
20040133248 | Frei et al. | Jul 2004 | A1 |
20040138716 | Kon et al. | Jul 2004 | A1 |
20040147975 | Popovic et al. | Jul 2004 | A1 |
20040199215 | Lee et al. | Oct 2004 | A1 |
20040199216 | Lee et al. | Oct 2004 | A1 |
20040199217 | Lee et al. | Oct 2004 | A1 |
20040199218 | Lee et al. | Oct 2004 | A1 |
20040215286 | Stypulkowski | Oct 2004 | A1 |
20040220621 | Zhou et al. | Nov 2004 | A1 |
20040225332 | Gebhardt et al. | Nov 2004 | A1 |
20040257693 | Ehrlich | Dec 2004 | A1 |
20050042589 | Hatlestad et al. | Feb 2005 | A1 |
20050043767 | Belalcazar | Feb 2005 | A1 |
20050043772 | Stahmann | Feb 2005 | A1 |
20050060001 | Singhal et al. | Mar 2005 | A1 |
20050061320 | Lee et al. | Mar 2005 | A1 |
20050113710 | Stahmann et al. | May 2005 | A1 |
20050113887 | Bauhahn | May 2005 | A1 |
20050126026 | Townsend et al. | Jun 2005 | A1 |
20050137627 | Koshiol et al. | Jun 2005 | A1 |
20050145246 | Hartley et al. | Jul 2005 | A1 |
20050172311 | Hjelt et al. | Aug 2005 | A1 |
20050177192 | Rezai et al. | Aug 2005 | A1 |
20050209511 | Heruth et al. | Sep 2005 | A1 |
20050209512 | Heruth et al. | Sep 2005 | A1 |
20050209513 | Heruth et al. | Sep 2005 | A1 |
20050209643 | Heruth et al. | Sep 2005 | A1 |
20050209644 | Heruth et al. | Sep 2005 | A1 |
20050209645 | Heruth et al. | Sep 2005 | A1 |
20050215847 | Heruth et al. | Sep 2005 | A1 |
20050215947 | Heruth et al. | Sep 2005 | A1 |
20050216064 | Heruth et al. | Sep 2005 | A1 |
20050222522 | Heruth et al. | Oct 2005 | A1 |
20050222638 | Foley et al. | Oct 2005 | A1 |
20050228455 | Kramer et al. | Oct 2005 | A1 |
20050234514 | Heruth et al. | Oct 2005 | A1 |
20050234518 | Heruth et al. | Oct 2005 | A1 |
20050240242 | DiLorenzo | Oct 2005 | A1 |
20050245988 | Miesel | Nov 2005 | A1 |
20050283210 | Blischak et al. | Dec 2005 | A1 |
20060190049 | Gerber et al. | Aug 2006 | A1 |
20060190050 | Gerber et al. | Aug 2006 | A1 |
20060190051 | Gerber et al. | Aug 2006 | A1 |
20060195051 | Schnapp et al. | Aug 2006 | A1 |
20060206167 | Flaherty et al. | Sep 2006 | A1 |
20060212080 | Hartley et al. | Sep 2006 | A1 |
20060213267 | Tronconi et al. | Sep 2006 | A1 |
20060235289 | Wesselink et al. | Oct 2006 | A1 |
20060235472 | Goetz et al. | Oct 2006 | A1 |
20060241513 | Hatlestad et al. | Oct 2006 | A1 |
20060247732 | Wesselink | Nov 2006 | A1 |
20060247739 | Wahlstrand et al. | Nov 2006 | A1 |
20060259099 | Goetz et al. | Nov 2006 | A1 |
20060262120 | Rosenberg | Nov 2006 | A1 |
20060265025 | Goetz et al. | Nov 2006 | A1 |
20060287686 | Cullen et al. | Dec 2006 | A1 |
20070015976 | Miesel et al. | Jan 2007 | A1 |
20070038265 | Tcheng et al. | Feb 2007 | A1 |
20070050715 | Behar | Mar 2007 | A1 |
20070073355 | DiLorenzo et al. | Mar 2007 | A1 |
20070115277 | Wang et al. | May 2007 | A1 |
20070118056 | Wang et al. | May 2007 | A1 |
20070123758 | Miesel et al. | May 2007 | A1 |
20070129622 | Bourget et al. | Jun 2007 | A1 |
20070129641 | Sweeney | Jun 2007 | A1 |
20070129769 | Bourget et al. | Jun 2007 | A1 |
20070129774 | Bourget et al. | Jun 2007 | A1 |
20070150026 | Bourget et al. | Jun 2007 | A1 |
20070150029 | Bourget et al. | Jun 2007 | A1 |
20070213789 | Nolan et al. | Sep 2007 | A1 |
20070233201 | Lovett et al. | Oct 2007 | A1 |
20070249968 | Miesel et al. | Oct 2007 | A1 |
20070250121 | Miesel et al. | Oct 2007 | A1 |
20070250134 | Miesel et al. | Oct 2007 | A1 |
20070255118 | Miesel et al. | Nov 2007 | A1 |
20070255154 | Lu et al. | Nov 2007 | A1 |
20070265664 | Gerber et al. | Nov 2007 | A1 |
20070265681 | Gerber et al. | Nov 2007 | A1 |
20070276439 | Miesel et al. | Nov 2007 | A1 |
20070293737 | Heruth et al. | Dec 2007 | A1 |
20070293917 | Thompson | Dec 2007 | A1 |
20080071150 | Miesel et al. | Mar 2008 | A1 |
20080071324 | Miesel et al. | Mar 2008 | A1 |
20080071326 | Heruth et al. | Mar 2008 | A1 |
20080071327 | Miesel et al. | Mar 2008 | A1 |
20080079444 | Denison | Apr 2008 | A1 |
20080081958 | Denison et al. | Apr 2008 | A1 |
20080114219 | Zhang et al. | May 2008 | A1 |
20080164979 | Otto | Jul 2008 | A1 |
20080177355 | Miesel et al. | Jul 2008 | A1 |
20080188901 | Sanghera et al. | Aug 2008 | A1 |
20080188909 | Bradley | Aug 2008 | A1 |
20080194998 | Holmstrom et al. | Aug 2008 | A1 |
20080204255 | Flexer et al. | Aug 2008 | A1 |
20080269812 | Gerber et al. | Oct 2008 | A1 |
20080269843 | Gerber | Oct 2008 | A1 |
20080281376 | Gerber et al. | Nov 2008 | A1 |
20080281379 | Wesselink | Nov 2008 | A1 |
20080281381 | Gerber et al. | Nov 2008 | A1 |
20080288200 | Noble | Nov 2008 | A1 |
20080300449 | Gerber et al. | Dec 2008 | A1 |
20080300470 | Gerber et al. | Dec 2008 | A1 |
20090030263 | Heruth et al. | Jan 2009 | A1 |
20090036951 | Heruth et al. | Feb 2009 | A1 |
20090046056 | Rosenberg et al. | Feb 2009 | A1 |
20090076343 | Kristofer et al. | Mar 2009 | A1 |
20090082829 | Panken et al. | Mar 2009 | A1 |
20090099627 | Molnar et al. | Apr 2009 | A1 |
20090105785 | Wei et al. | Apr 2009 | A1 |
20090118599 | Heruth et al. | May 2009 | A1 |
20090228841 | Hildreth | Sep 2009 | A1 |
20090233770 | Vincent et al. | Sep 2009 | A1 |
20090259216 | Drew et al. | Oct 2009 | A1 |
20090264789 | Molnar et al. | Oct 2009 | A1 |
20090306740 | Heruth et al. | Dec 2009 | A1 |
20100010380 | Panken et al. | Jan 2010 | A1 |
20100010381 | Skelton et al. | Jan 2010 | A1 |
20100010382 | Panken et al. | Jan 2010 | A1 |
20100010383 | Skelton et al. | Jan 2010 | A1 |
20100010384 | Panken et al. | Jan 2010 | A1 |
20100010385 | Skelton et al. | Jan 2010 | A1 |
20100010386 | Skelton et al. | Jan 2010 | A1 |
20100010387 | Skelton et al. | Jan 2010 | A1 |
20100010388 | Panken et al. | Jan 2010 | A1 |
20100010389 | Davis et al. | Jan 2010 | A1 |
20100010390 | Skelton et al. | Jan 2010 | A1 |
20100010391 | Skelton et al. | Jan 2010 | A1 |
20100010392 | Skelton et al. | Jan 2010 | A1 |
20100010432 | Skelton et al. | Jan 2010 | A1 |
20100010571 | Skelton et al. | Jan 2010 | A1 |
20100010572 | Skelton et al. | Jan 2010 | A1 |
20100010573 | Skelton et al. | Jan 2010 | A1 |
20100010574 | Skelton et al. | Jan 2010 | A1 |
20100010575 | Skelton et al. | Jan 2010 | A1 |
20100010576 | Skelton et al. | Jan 2010 | A1 |
20100010577 | Skelton et al. | Jan 2010 | A1 |
20100010578 | Skelton et al. | Jan 2010 | A1 |
20100010579 | Skelton et al. | Jan 2010 | A1 |
20100010580 | Skelton et al. | Jan 2010 | A1 |
20100010583 | Panken et al. | Jan 2010 | A1 |
20100010584 | Skelton et al. | Jan 2010 | A1 |
20100010585 | Davis et al. | Jan 2010 | A1 |
20100010586 | Skelton et al. | Jan 2010 | A1 |
20100010587 | Skelton et al. | Jan 2010 | A1 |
20100010588 | Skelton et al. | Jan 2010 | A1 |
20100010589 | Skelton et al. | Jan 2010 | A1 |
20100030286 | Goetz et al. | Feb 2010 | A1 |
20100121415 | Skelton et al. | May 2010 | A1 |
20100174155 | Heruth et al. | Jul 2010 | A1 |
20110082522 | Bourget et al. | Apr 2011 | A1 |
20110238130 | Bourget et al. | Sep 2011 | A1 |
20110238136 | Bourget et al. | Sep 2011 | A1 |
Number | Date | Country |
---|---|---|
19831109 | Jan 2000 | DE |
10024103 | Nov 2001 | DE |
0564803 | Oct 1993 | EP |
0845240 | Jun 1998 | EP |
0849715 | Jun 1998 | EP |
0613390 | Oct 2000 | EP |
1195139 | Apr 2002 | EP |
1291036 | Mar 2003 | EP |
1308182 | May 2003 | EP |
1391846 | Feb 2004 | EP |
1437159 | Jul 2004 | EP |
1731088 | Dec 2006 | EP |
1870128 | Dec 2007 | EP |
1938862 | Jul 2008 | EP |
2330912 | May 1999 | GB |
2408342 | May 2005 | GB |
2447647 | Sep 2008 | GB |
9405371 | Mar 1994 | WO |
9629007 | Sep 1996 | WO |
9704705 | Feb 1997 | WO |
9749455 | Dec 1997 | WO |
9800197 | Jan 1998 | WO |
9956820 | Nov 1999 | WO |
0137930 | May 2001 | WO |
0228282 | Apr 2002 | WO |
0241771 | May 2002 | WO |
0287433 | Nov 2002 | WO |
0296512 | Dec 2002 | WO |
02100267 | Dec 2002 | WO |
0351356 | Jun 2003 | WO |
0365891 | Aug 2003 | WO |
0528029 | Mar 2005 | WO |
0535050 | Apr 2005 | WO |
0579487 | Sep 2005 | WO |
0589646 | Sep 2005 | WO |
0589647 | Sep 2005 | WO |
0589860 | Sep 2005 | WO |
05102499 | Nov 2005 | WO |
05120348 | Dec 2005 | WO |
0709088 | Jan 2007 | WO |
0751196 | May 2007 | WO |
0764682 | Jun 2007 | WO |
0764936 | Jun 2007 | WO |
0826970 | Mar 2008 | WO |
Entry |
---|
Office Action from U.S. Appl. No. 12/966,827 dated Dec. 4, 2013, 10 pp. |
Office Action from U.S. Appl. No. 13/154,303 dated Dec. 5, 2013, 7 pp. |
“Analysis of heart rate dynamics by methods derived from non-linear mathematics: Clinical applicability and prognostic significance,” http://herkules.oulu.fi.isbn9514250133/html, 4 pp., 2004. |
“Design Competition: Runners-Up for the Best Three Designs,” EPN, vol. 26, No. 1, 1 pg., 2002. |
“IBM and Citizen Watch develop Linux-Based WatchPad,” http:/wwwlinuxdevices.com.news/NS6580187845.html, 5 pp., 2006. |
“MiniMitter® Physiological and Behavioral Monitoring for Humans and Animals,” http://www.minimitter.com/Products/Actiwatch, 3 pp., 2006. |
“Watch,” Wikipedia, 6 pp., http://en.wikipedia.org/wiki/Watch, 2006. |
Aminian et al., “Physical Activity Monitoring Based on Accelerometry: Validation and Comparison with Video Observation,” Medical & Biological Engineering and Computing, vol. 37, No. 2, pp. 304-308,1999. |
Amzica, “Physiology of Sleep and Wakefulness as it Relates to the Physiology of Epilepsy,” Journal of Clinical Neurophysiology, American Clinical Neurophysiology Society, 19(6)1, pp. 488-503, 2002. |
Ang et al., “Physical model of a MEMS accelerometer for low-g motion tracking applications,” 2004 IEEE International Conference on Robotics and Automation, vol. 2, pp. 1345-1351, 2004. |
Buchser et al., “Improved Physical Activity in Patients Treated for Chronic Pain by Spinal Cord Stimulation,” Neuromodulation, vol. 8, Issue 1, pp. 40-48, Mar. 2005. |
Crago et al., “An Elbow Extension Neuroprosthesis for Individuals with Tetraplegia,” IEEE Transactions on Rehabilitation Engineering, vol. 6, No. 1, pp. 1-6, Mar. 1998. |
Dejnabadi et al., “Estimation and Visualization of Sagittal Kinematics of Lower Limbs Orientation Using Body-Fixed Sensors,” IEEE Transactions on Biomedical Engineering, vol. 53, No. 7, pp. 1385-1393, Jul. 2006. |
Dinner, “Effect of Sleep on Epilepsy,” Journal of Clinical Neurophysiology, American Clinical Neurophysiology Society, 19(6), pp. 504-513, 2002. |
Foerster et al., “Motion Pattern and Posture: Correctly Assessed by Calibrated Accelerometers,” Forschungsgrupe Psychophysiologie, Universität Freiburg, Germany, Mar. 2000, 28 pp. |
Foldvary-Schaefer, “Sleep Complaints and Epilepsy: The Role of Seizures, Antiepileptic Drugs and Sleep Disorders,” Journal of Clinical Neurophysiology, American Clinical Neurophysiology Society, 19(6), pp. 514-521, 2002. |
Fourcade et al., “Modeling Phase Transitions in Human Posture,” Studies in Perception and Action VII, Sheena Rogers & Judith Effken (eds), Lawrence Erlbaum Associated, Inc., pp. 99-103, 2003. |
Giansanti et al., “The development and test of a device for the reconstruction of 3-D position and orientation by means of a kinematic sensor assembly with rate gyroscopes and accelerometers,” IEEE Transactions on Biomedical Engineering, v. 52, No. 7, pp. 1271-1277, Jul. 2005. |
Goodrich et al., “The Prediction of Pain Using Measures of Sleep Quality,” Pain Digest, 8:23-25, 1998. |
Heinz et al., “Using Wearable Sensors for Real-time Recognition Tasks in Games of Martial Arts—An Initial Experiment,” Institute for Computer Systems and Networks (CSN), UMIT—University of Health Systems, Medical Informatics and Technology Hall in Tyrol, Austria, 2006, 5 pp., http://eis.comp.lancs.ac.uk/fileadmin/relate/publication/2006-WearableSensors.pdf. |
Hendelman et al., “Validity of Accelerometry for the Assessment of Moderate Intensity Physical Activity in the Field,” Medicine & Science in Sports & Exercise, pp. S442-S449, 2000. |
Hinckley, K., Pierce, J., Sinclair, M., Horvitz, E., Sensing Techniques for Mobile Interaction, ACM UIST 2000 Symposium on User Interface Software & Technology, CHI Letters 2 (2), pp. 91-100. |
Husak, “Model of Tilt Sensor Systems,” ICECS 2002, 9th IEEE International Conference on Electronics, Circuits and Systems, vol. 1, pp. 227-230, 2002. |
Karantonis et al., “Implementation of a Real-Time Human Movement Classifier Using a Triaxial Accelerometer for Ambulatory Monitoring,” IEEE Transactions on Information Technology in Biomedicine, vol. 10, No. 1, pp. 156-167, Jan. 2006. |
Kassam, “2005 EDP Topic “MK4”: Tremor Data-Logger for Parkinson's Disease Patients,” http://www.ee.ryerson.ca/˜courses/edp2005/MK4.html, 3 pp., 2005. |
Kerr et al., “Analysis of the sit-stand-sit movement cycle in normal subjects,” Clinical Biomechanics, vol. 12, No. 4, pp. 236-245, 1977. |
Kiani et al., “Computerized Analysis of Daily Life Motor Activity for Ambulatory Monitoring,” Technology and Health Care 5, pp. 307-318, 1997. |
Kitchin et al., “Compensating for the 0 g Offset Drift of the ADXL50 Accelerometer,” Analog Devices Application Note AN-380, 2 pp. |
Lau, “Strategies for Generating Prolonged Functional Standing Using Intramuscular Stimulation or Intraspinal Microstimulation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 15 No. 2, pp. 273-285, Jun. 2007. |
Leiper et al., “Sensory Feedback for Head Control in Cerebral Palsy,” Physical Therapy, vol. 61, No. 4, pp. 512-518, Apr. 1981. |
Lorussi, “Wearable, Redundant Fabric-Based Sensor Arrays for Reconstruction of Body Segment Posture,” IEEE Sensors Journal, vol. 4, No. 6, pp. 808-817, Dec. 2004. |
Mathie et al., “A Pilot Study of Long-Term Monitoring of Human Movements in the Home Using Accelerometer,” Journal of Telemedicine and Telecare10:144-151, Jun. 2007. |
Mathie et al., “Determining Activity Using a Triaxial Accelerometer,” Proceedings of the Second Joint EMBS/BMES Conference, Houston, TX, pp. 2481-2482, Oct. 23-26, 2002. |
Mattmann et al., “Recognizing Upper Body Postures Using Textile Strain Sensors,” Proceedings Eleventh IEEE International Symposium on Wearable Computers, ISWC, pp. 29-36, 2007. |
Mendez et al., “Interactions Between Sleep and Epilepsy,” Journal of Clinical Neurophysiology, American Clinical Neurophysiology Society, 18(2), pp. 106-127, 2001. |
Paraschiv-Ionescu et al., “Ambulatory System for the Quantitative and Qualitative Analysis of Patients Treated with Spinal Cord Stimulation,” Gait and Posture, vol. 20, Issue 2, pp. 113-125, Oct. 2004. |
Slyper et al., “Action Capture with Accelerometers,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation, Carnegie Mellon University, 7 pp., 2008. |
Smith et al., “How do sleep disturbance and chronic pain inter-relate? Insights from the longitudinal and cognitive-behavioral clinical trials literature,” Sleep Medicine Reviews, YSMRV 286, pp. 1-14, 2003. |
Smith et al., “Presleep cognitions in Patients with Insomnia Secondary to Chronic Pain,” Journal of Behavioral Medicine, vol. 24, No. 1, pp. 93-114, 2001. |
Emmanuel Munguia Tapia, “Activity Recognition from Accelerometer Data for Videogame Applications,” http://alumni.media.mit.edu/˜emunguia/html/videogames.htm, 7 pp., Dec. 2, 2003, printed Oct. 1, 2009. |
Trolier-Mckinstry et al., “Thin Film Piezoelectrics for MEMS,” Journal of Electroceramics, v. 12, No. 1-2, pp. 7-17, Jan./Mar. 2004. |
Tuck, “Implementing Auto-Zero Calibration Technique for Accelerometers,” Freescale Semiconductor Application Note AN3447, 5 pp., Mar. 2007. |
Tuisku, “Motor Activity Measured by Actometry in Neuropsychiatric Disorders,” Department of Psychiatry, University of Helsinki, Helsinki, Finland, 115 pp., 2002. |
Vega-Gonzalez, “Continuous Monitoring of Upper Limb Activity in a Free-Living Environment,” Arch Phys Med Rehabil, vol. 86, pp. 541-548, Mar. 2005. |
Leung et al., “An Integrated Dual Sensor System Automatically Optimized by Target Rate Histogram,” Pacing and Clinical Electrophysiology, vol. 21, No. 8, 7 pp. Aug. 8, 1998. |
Saoudi et al., “How Smart Should Pacemakers Be?,” American Journal of Cardiology, vol. 83, No. 5, 6 pp., Mar. 5, 1999. |
Velten et al., “A New Three-Axis Accelerometer,” Sensor '99-9th Int'l Trade Fair and Conference for Sensors/Transducers & Systems, Nurnberg, Germany, May 18-20, 1999, Sensor '99 Proceedings II, 1999, A 5.2, 6 pp. |
International Preliminary Report on Patentability for PCT Application PCT/US2004/002113, dated Sep. 19, 2005, 5 pp. |
European Office Action dated Nov. 13, 2008 for Application No. 06844740.8, 2 pp. |
European Office Action dated Nov. 13, 2008 for Application No. 06844725.9, 2 pp. |
Canadian Office Action dated Mar. 12, 2012 for Canadian Application No. 2,538,356, 3pp. |
Prosecution History from U.S. Pat. No. 8,396,565 from Feb. 28, 2006 through Jan. 11, 2013, 263 pp. |
Prosecution History from U.S. Pat. No. 7,853,322 from Jul. 23, 2008 through Sep. 15, 2010, 139 pp. |
Prosecution History from U.S. Pat. No. 7,957,809 from Mar. 9, 2010 through Jan. 31, 2011, 37 pp. |
Prosecution History from U.S. Pat. No. 7,957,797 from Mar. 9, 2010 through Jan. 31, 2011, 58 pp. |
Prosecution History from U.S. Appl. No. 12/966,827, filed Jul. 10, 2012 through Nov. 15, 2013, 48 pp. |
Prosecution History from U.S. Appl. No. 13/154,303, filed Aug. 16, 2013 through Nov. 15, 2013, 14 pp. |
Prosecution History from U.S. Appl. No. 13/154,309, filed Nov. 23, 2012 through Nov. 1, 2013, 41 pp. |
Notice of Allowance from U.S. Appl. No. 13/154,309, dated Jan. 8, 2014, 7 pp. |
Response to Office Action dated Dec. 5, 2013 from U.S. Appl. No. 13/154,303, filed Mar. 5, 2014, 8 pp. |
Office Action from U.S. Appl. No. 13/154,303, dated Jul. 7, 2014, 7 pp. |
Notice of Allowance from U.S. Appl. No. 12/966,827, dated Jul. 18, 2014, 5 pp. |
Response to Office Action dated Jul. 7, 2014, from U.S. Appl. No. 13/154,303, filed Oct. 7, 2014, 8 pp. |
Final Office Action from U.S. Appl. No. 13/154,303, dated Dec. 11, 2014, 8 pp. |
Response to Final Office Action dated Dec. 11, 2014, from U.S. Appl. No. 13/154,303, filed Feb. 11, 2015, 4 pp. |
Examiners Answer from U.S. Appl. No. 13/154,303, dated Nov. 9, 2015, 9 pp. |
Response to Decision on Appeal dated Oct. 2, 2017, from U.S. Appl. No. 13/154,303, filed Dec. 4, 2017, 9 pp. |
Decision on Appeal from U.S. Appl. No. 13/154,303, dated Oct. 2, 2017, 16 pp. |
Written Opinion from International Application No. PCT/US2004/002113, dated Jun. 21, 2004, 5 pp. |
Response to Examiner's second report from counterpart Australian Patent Application No. 2004279285, filed on Aug. 10, 2010, 2 pp. |
Examiners Report from counterpart Canadian Patent Application No. 2538356, dated Mar. 21, 2013, 3 pp. |
Response to Examiner's Report dated Mar. 12, 2012, from counterpart Canadian Patent Application No. 2538356, filed on Sep. 11, 2012, 16 pp. |
Response to Examiner's Report dated Mar. 21, 2013, from counterpart Canadian Patent Application No. 2538356, filed on Jul. 8, 2013, 10 pp. |
Examiners Report from counterpart Canadian Patent Application No. 2538356, dated Feb. 3, 2011, 2 pp. |
Response to Examiner's Report dated Feb. 3, 2011, from counterpart Canadian Patent Application No. 2538356, filed on Jun. 21, 2011, 9 pp. |
Office Action from US. Appl. No. 13/154,303, dated Jan. 12, 2018, 9 pp. |
Response to Office Action dated Jan. 12, 2018, from U.S. Appl. No. 13/154,303, filed Apr. 12, 2018, 6 pp. |
Office Action from U.S. Appl. No. 13/154,303, dated Aug. 16, 2018, 9 pp. |
Number | Date | Country | |
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20130150921 A1 | Jun 2013 | US |
Number | Date | Country | |
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60503218 | Sep 2003 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 10691917 | Oct 2003 | US |
Child | 13764054 | US |