Detecting neural activity in the brain (or any other turbid medium) is useful for medical diagnostics, imaging, neuroengineering, brain-computer interfacing, and a variety of other diagnostic and consumer-related applications. For example, it may be desirable to detect neural activity in the brain of a user to determine if a particular region of the brain has been impacted by reduced blood irrigation, a hemorrhage, or any other type of damage. As another example, it may be desirable to detect neural activity in the brain of a user and computationally decode the detected neural activity into commands that can be used to control various types of consumer electronics (e.g., by controlling a cursor on a computer screen, changing channels on a television, turning lights on, etc.).
Neural activity and other attributes of the brain may be determined or inferred by measuring responses of tissue within the brain to light pulses. One technique to measure such responses is time-correlated single-photon counting (TCSPC). Time-correlated single-photon counting detects single photons and measures a time of arrival of the photons with respect to a reference signal (e.g., a light source). By repeating the light pulses, TCSPC may accumulate a sufficient number of photon events to statistically determine a histogram representing the distribution of detected photons. Based on the histogram of photon distribution, the response of tissue to light pulses may be determined in order to study the detected neural activity and/or other attributes of the brain.
A photodetector capable of detecting a single photon (i.e., a single particle of optical energy) is an example of a non-invasive detector that can be used in an optical measurement system to detect neural activity within the brain. An exemplary photodetector is implemented by a semiconductor-based single-photon avalanche diode (SPAD), which is capable of capturing individual photons with very high time-of-arrival resolution (a few tens of picoseconds).
The accompanying drawings illustrate various embodiments and are a part of the specification. The illustrated embodiments are merely examples and do not limit the scope of the disclosure. Throughout the drawings, identical or similar reference numbers designate identical or similar elements.
In accordance with the systems, circuits, and methods described herein, an optical measurement system may include a control circuit that applies a bias voltage and a current to photodetectors of the optical measurement system to provide a consistent overvoltage to the photodetectors. The bias voltage may be applied to a first terminal of each photodetector and the current to a second terminal of each photodetector. The current may be applied for a predetermined amount of time to deliver or draw a predetermined amount of charge such that a voltage difference across each photodetector is a consistent voltage amount. The consistent voltage difference may be configured to be set to the overvoltage, so that the photodetectors may have a consistent sensitivity.
Achieving a consistent sensitivity across photodetectors of the optical measurement system may allow the optical measurement system to generate more accurate histograms that combine outputs of the photodetectors. These and other advantages and benefits of the present systems, circuits, and methods are described more fully herein.
In some examples, optical measurement operations performed by optical measurement system 100 are associated with a time domain-based optical measurement technique. Example time domain-based optical measurement techniques include, but are not limited to, TCSPC, time domain near infrared spectroscopy (TD-NIRS), time domain diffusive correlation spectroscopy (TD-DCS), and time domain Digital Optical Tomography (TD-DOT).
As shown, optical measurement system 100 includes a detector 104 that includes a plurality of individual photodetectors (e.g., photodetector 106), a processor 108 coupled to detector 104, a light source 110, a controller 112, and optical conduits 114 and 116 (e.g., light pipes). However, one or more of these components may not, in certain embodiments, be considered to be a part of optical measurement system 100. For example, in implementations where optical measurement system 100 is wearable by a user, processor 108 and/or controller 112 may in some embodiments be separate from optical measurement system 100 and not configured to be worn by the user.
Detector 104 may include any number of photodetectors 106 as may serve a particular implementation, such as 2n photodetectors (e.g., 256, 512, . . . , 16384, etc.), where n is an integer greater than or equal to one (e.g., 4, 5, 8, 10, 11, 14, etc.). Photodetectors 106 may be arranged in any suitable manner.
Photodetectors 106 may each be implemented by any suitable circuit configured to detect individual photons of light incident upon photodetectors 106. For example, each photodetector 106 may be implemented by a single photon avalanche diode (SPAD) circuit and/or other circuitry as may serve a particular implementation.
Processor 108 may be implemented by one or more physical processing (e.g., computing) devices. In some examples, processor 108 may execute instructions (e.g., software) configured to perform one or more of the operations described herein.
Light source 110 may be implemented by any suitable component configured to generate and emit light. For example, light source 110 may be implemented by one or more laser diodes, distributed feedback (DFB) lasers, super luminescent diodes (SLDs), light emitting diodes (LEDs), diode-pumped solid-state (DPSS) lasers, super luminescent light emitting diodes (sLEDs), vertical-cavity surface-emitting lasers (VCSELs), titanium sapphire lasers, micro light emitting diodes (mLEDs), and/or any other suitable laser or light source. In some examples, the light emitted by light source 110 is high coherence light (e.g., light that has a coherence length of at least 5 centimeters) at a predetermined center wavelength.
Light source 110 is controlled by controller 112, which may be implemented by any suitable computing device (e.g., processor 108), integrated circuit, and/or combination of hardware and/or software as may serve a particular implementation. In some examples, controller 112 is configured to control light source 110 by turning light source 110 on and off and/or setting an intensity of light generated by light source 110. Controller 112 may be manually operated by a user, or may be programmed to control light source 110 automatically.
Light emitted by light source 110 may travel via an optical conduit 114 (e.g., a light pipe, a light guide, a waveguide, a single-mode optical fiber, and/or or a multi-mode optical fiber) to body 102 of a subject. In cases where optical conduit 114 is implemented by a light guide, the light guide may be spring loaded and/or have a cantilever mechanism to allow for conformably pressing the light guide firmly against body 102.
Body 102 may include any suitable turbid medium. For example, in some implementations, body 102 is a head or any other body part of a human or other animal. Alternatively, body 102 may be a non-living object. For illustrative purposes, it will be assumed in the examples provided herein that body 102 is a human head.
As indicated by arrow 120, the light emitted by light source 110 enters body 102 at a first location 122 on body 102. Accordingly, a distal end of optical conduit 114 may be positioned at (e.g., right above, in physical contact with, or physically attached to) first location 122 (e.g., to a scalp of the subject). In some examples, the light may emerge from optical conduit 114 and spread out to a certain spot size on body 102 to fall under a predetermined safety limit. At least a portion of the light indicated by arrow 120 may be scattered within body 102.
As used herein, “distal” means nearer, along the optical path of the light emitted by light source 110 or the light received by detector 104, to the target (e.g., within body 102) than to light source 110 or detector 104. Thus, the distal end of optical conduit 114 is nearer to body 102 than to light source 110, and the distal end of optical conduit 116 is nearer to body 102 than to detector 104. Additionally, as used herein, “proximal” means nearer, along the optical path of the light emitted by light source 110 or the light received by detector 104, to light source 110 or detector 104 than to body 102. Thus, the proximal end of optical conduit 114 is nearer to light source 110 than to body 102, and the proximal end of optical conduit 116 is nearer to detector 104 than to body 102.
As shown, the distal end of optical conduit 116 (e.g., a light pipe, a light guide, a waveguide, a single-mode optical fiber, and/or a multi-mode optical fiber) is positioned at (e.g., right above, in physical contact with, or physically attached to) output location 126 on body 102. In this manner, optical conduit 116 may collect at least a portion of the scattered light (indicated as light 124) as it exits body 102 at location 126 and carry light 124 to detector 104. Light 124 may pass through one or more lenses and/or other optical elements (not shown) that direct light 124 onto each of the photodetectors 106 included in detector 104.
Photodetectors 106 may be connected in parallel in detector 104. An output of each of photodetectors 106 may be accumulated to generate an accumulated output of detector 104. Processor 108 may receive the accumulated output and determine, based on the accumulated output, a temporal distribution of photons detected by photodetectors 106. Processor 108 may then generate, based on the temporal distribution, a histogram representing a light pulse response of a target (e.g., brain tissue, blood flow, etc.) in body 102. Example embodiments of accumulated outputs are described herein.
In some examples, SPAD circuit 202 may include a SPAD and a fast gating circuit configured to operate together to detect a photon incident upon the SPAD. As described herein, SPAD circuit 202 may generate an output when SPAD circuit 202 detects a photon.
The fast gating circuit included in SPAD circuit 202 may be implemented in any suitable manner. For example, the fast gating circuit may be implemented by an active voltage source, a capacitor that is pre-charged with a bias voltage before a command is provided to arm the SPAD, and/or in any other suitable manner.
In some alternative configurations, SPAD circuit 202 does not include a fast gating circuit. In these configurations, the SPAD included in SPAD circuit 202 may be gated in any suitable manner or be configured to operate in a free running mode with passive quenching.
Control circuit 204 may be implemented by an application specific integrated circuit (ASIC) or any other suitable circuit configured to control an operation of various components within SPAD circuit 202. For example, control circuit 204 may output control logic that puts the SPAD included in SPAD circuit 202 in either an armed or a disarmed state.
In some examples, control circuit 204 may control an arming and a disarming of a SPAD included in SPAD circuit 202. Control circuit 204 may also control a programmable gate width, which specifies how long the SPAD is kept in an armed state before being disarmed.
Control circuit 204 is further configured to control signal processing circuit 208. For example, control circuit 204 may provide histogram parameters (e.g., time bins, number of light pulses, type of histogram, etc.) to signal processing circuit 208. Signal processing circuit 208 may generate histogram data in accordance with the histogram parameters. In some examples, control circuit 204 is at least partially implemented by controller 112.
TDC 206 is configured to measure a time difference between an occurrence of an output pulse generated by SPAD circuit 202 and an occurrence of a light pulse. To this end, TDC 206 may also receive the same light pulse timing information that control circuit 204 receives. TDC 206 may be implemented by any suitable circuitry as may serve a particular implementation.
Signal processing circuit 208 is configured to perform one or more signal processing operations on data output by TDC 206. For example, signal processing circuit 208 may generate histogram data based on the data output by TDC 206 and in accordance with histogram parameters provided by control circuit 204. To illustrate, signal processing circuit 208 may generate, store, transmit, compress, analyze, decode, and/or otherwise process histograms based on the data output by TDC 206. In some examples, signal processing circuit 208 may provide processed data to control circuit 204, which may use the processed data in any suitable manner. In some examples, signal processing circuit 208 is at least partially implemented by processor 108.
In some examples, each photodetector 106 (e.g., SPAD circuit 202) may have a dedicated TDC 206 associated therewith. For example, for an array of N photodetectors 106, there may be a corresponding array of N TDCs 206. Likewise, a single control circuit 204 and a single signal processing circuit 208 may be provided for a one or more photodetectors 106 and/or TDCs 206.
For example, timing diagram 300 shows a sequence of light pulses 302 (e.g., light pulses 302-1 and 302-2) that may be applied to the target (e.g., tissue within a brain of a user, blood flow, a fluorescent material used as a probe in a body of a user, etc.). Timing diagram 300 also shows a pulse wave 304 representing predetermined gated time windows (also referred as gated time periods) during which photodetectors 106 are gated ON (i.e., armed) to detect photons. Referring to light pulse 302-1, light pulse 302-1 is applied at a time t0. At a time t1, a first instance of the predetermined gated time window begins. Photodetectors 106 may be armed at time t1, enabling photodetectors 106 to detect photons scattered by the target during the predetermined gated time window. In this example, time t1 is set to be at a certain time after time t0, which may minimize photons detected directly from the laser pulse, before the laser pulse reaches the target. However, in some alternative examples, time t1 is set to be equal to time t0.
At a time t2, the predetermined gated time window ends. In some examples, photodetectors 106 may be disarmed at time t2. In other examples, photodetectors 106 may be reset (e.g., disarmed and re-armed) at time t2 or at a time subsequent to time t2. During the predetermined gated time window, photodetectors 106 may detect photons scattered by the target. Photodetectors 106 may be configured to remain armed during the predetermined gated time window such that photodetectors 106 maintain an output upon detecting a photon during the predetermined gated time window. For example, a photodetector 106 may detect a photon at a time t3, which is during the predetermined gated time window between times t1 and t2. The photodetector 106 may be configured to provide an output indicating that the photodetector 106 has detected a photon. The photodetector 106 may be configured to continue providing the output until time t2, when the photodetector may be disarmed and/or reset. Optical measurement system 100 may generate an accumulated output from the plurality of photodetectors. Optical measurement system 100 may sample the accumulated output to determine times at which photons are detected by photodetectors 106 to generate a TPSF.
As described herein, the systems, circuits, and methods described herein may obviate the need for the gated time windows described in connection with
As mentioned, in some alternative examples, photodetector 106 may be configured to operate in a free-running mode such that photodetector 106 is not actively armed and disarmed (e.g., at the end of each predetermined gated time window represented by pulse wave 304). In contrast, while operating in the free-running mode, photodetector 106 may be configured to reset within a configurable time period after an occurrence of a photon detection event (i.e., after photodetector 106 detects a photon) and immediately begin detecting new photons. However, only photons detected within a desired time window (e.g., during each gated time window represented by pulse wave 304) may be included in the TPSF.
Optical measurement system 100 may be implemented by or included in any suitable device. For example, optical measurement system 100 may be included, in whole or in part, in a non-invasive wearable device (e.g., a headpiece) that a user may wear to perform one or more diagnostic, imaging, analytical, and/or consumer-related operations. The non-invasive wearable device may be placed on a user's head or other part of the user to detect neural activity. In some examples, such neural activity may be used to make behavioral and mental state analysis, awareness and predictions for the user.
Mental state described herein refers to the measured neural activity related to physiological brain states and/or mental brain states, e.g., joy, excitement, relaxation, surprise, fear, stress, anxiety, sadness, anger, disgust, contempt, contentment, calmness, focus, attention, approval, creativity, positive or negative reflections/attitude on experiences or the use of objects, etc. Further details on the methods and systems related to a predicted brain state, behavior, preferences, or attitude of the user, and the creation, training, and use of neuromes can be found in U.S. Provisional Patent Application No. 63/047,991, filed Jul. 3, 2020. Exemplary measurement systems and methods using biofeedback for awareness and modulation of mental state are described in more detail in U.S. patent application Ser. No. 16/364,338, filed Mar. 26, 2019, published as US2020/0196932A1. Exemplary measurement systems and methods used for detecting and modulating the mental state of a user using entertainment selections, e.g., music, film/video, are described in more detail in U.S. patent application Ser. No. 16/835,972, filed Mar. 31, 2020, published as US2020/0315510A1. Exemplary measurement systems and methods used for detecting and modulating the mental state of a user using product formulation from, e.g., beverages, food, selective food/drink ingredients, fragrances, and assessment based on product-elicited brain state measurements are described in more detail in U.S. patent application Ser. No. 16/853,614, filed Apr. 20, 2020, published as US2020/0337624A1. Exemplary measurement systems and methods used for detecting and modulating the mental state of a user through awareness of priming effects are described in more detail in U.S. patent application Ser. No. 16/885,596, filed May 28, 2020, published as US2020/0390358A1. These applications and corresponding U.S. publications are incorporated herein by reference in their entirety.
Head-mountable component 502 includes a plurality of detectors 504, which may implement or be similar to detector 104, and a plurality of light sources 506, which may be implemented by or be similar to light source 110. It will be recognized that in some alternative embodiments, head-mountable component 502 may include a single detector 504 and/or a single light source 506.
Brain interface system 500 may be used for controlling an optical path to the brain and for transforming photodetector measurements into an intensity value that represents an optical property of a target within the brain. Brain interface system 500 allows optical detection of deep anatomical locations beyond skin and bone (e.g., skull) by extracting data from photons originating from light source 506 and emitted to a target location within the user's brain, in contrast to conventional imaging systems and methods (e.g., optical coherence tomography (OCT)), which only image superficial tissue structures or through optically transparent structures.
Brain interface system 500 may further include a processor 508 configured to communicate with (e.g., control and/or receive signals from) detectors 504 and light sources 506 by way of a communication link 510. Communication link 510 may include any suitable wired and/or wireless communication link. Processor 508 may include any suitable housing and may be located on the user's scalp, neck, shoulders, chest, or arm, as may be desirable. In some variations, processor 508 may be integrated in the same assembly housing as detectors 504 and light sources 506.
As shown, brain interface system 500 may optionally include a remote processor 512 in communication with processor 508. For example, remote processor 512 may store measured data from detectors 504 and/or processor 508 from previous detection sessions and/or from multiple brain interface systems (not shown). Power for detectors 504, light sources 506, and/or processor 508 may be provided via a wearable battery (not shown). In some examples, processor 508 and the battery may be enclosed in a single housing, and wires carrying power signals from processor 508 and the battery may extend to detectors 504 and light sources 506. Alternatively, power may be provided wirelessly (e.g., by induction).
In some alternative embodiments, head mountable component 502 does not include individual light sources. Instead, a light source configured to generate the light that is detected by detector 504 may be included elsewhere in brain interface system 500. For example, a light source may be included in processor 508 and coupled to head mountable component 502 through optical connections.
Optical measurement system 100 may alternatively be included in a non-wearable device (e.g., a medical device and/or consumer device that is placed near the head or other body part of a user to perform one or more diagnostic, imaging, and/or consumer-related operations). Optical measurement system 100 may alternatively be included in a sub-assembly enclosure of a wearable invasive device (e.g., an implantable medical device for brain recording and imaging).
Light sources 604 are each configured to emit light (e.g., a sequence of light pulses) and may be implemented by any of the light sources described herein. Detectors 606 may each be configured to detect arrival times for photons of the light emitted by one or more light sources 604 after the light is scattered by the target. For example, a detector 606 may include a photodetector configured to generate a photodetector output pulse in response to detecting a photon of the light and a TDC configured to record a timestamp symbol in response to an occurrence of the photodetector output pulse, the timestamp symbol representative of an arrival time for the photon (i.e., when the photon is detected by the photodetector).
Wearable assembly 602 may be implemented by any of the wearable devices, modular assemblies, and/or wearable units described herein. For example, wearable assembly 602 may be implemented by a wearable device (e.g., headgear) configured to be worn on a user's head. Wearable assembly 602 may additionally or alternatively be configured to be worn on any other part of a user's body.
Optical measurement system 600 may be modular in that one or more components of optical measurement system 600 may be removed, changed out, or otherwise modified as may serve a particular implementation. As such, optical measurement system 600 may be configured to conform to three-dimensional surface geometries, such as a user's head. Exemplary modular multimodal measurement systems are described in more detail in U.S. patent application Ser. No. 17/176,460, filed Feb. 16, 2021, U.S. patent application Ser. No. 17/176,470, filed Feb. 16, 2021, U.S. patent application Ser. No. 17/176,487, filed Feb. 16, 2021, U.S. Provisional Patent Application No. 63/038,481, filed Jun. 12, 2020, and U.S. patent application Ser. No. 17/176,560, filed Feb. 16, 2021, which applications are incorporated herein by reference in their respective entireties.
As shown, modular assembly 700 includes a plurality of modules 702 (e.g., modules 702-1 through 702-3). While three modules 702 are shown to be included in modular assembly 700, in alternative configurations, any number of modules 702 (e.g., a single module up to sixteen or more modules) may be included in modular assembly 700.
Each module 702 includes a light source (e.g., light source 704-1 of module 702-1 and light source 704-2 of module 702-2) and a plurality of detectors (e.g., detectors 706-1 through 706-6 of module 702-1). In the particular implementation shown in
Each light source depicted in
Each light source depicted in
Each detector depicted in
The detectors of a module may be distributed around the light source of the module. For example, detectors 706 of module 702-1 are distributed around light source 704-1 on surface 708 of module 702-1. In this configuration, detectors 706 may be configured to detect photon arrival times for photons included in light pulses emitted by light source 704-1. In some examples, one or more detectors 706 may be close enough to other light sources to detect photon arrival times for photons included in light pulses emitted by the other light sources. For example, because detector 706-3 is adjacent to module 702-2, detector 706-3 may be configured to detect photon arrival times for photons included in light pulses emitted by light source 704-2 (in addition to detecting photon arrival times for photons included in light pulses emitted by light source 704-1).
In some examples, the detectors of a module may all be equidistant from the light source of the same module. In other words, the spacing between a light source (i.e., a distal end portion of a light source optical conduit) and the detectors (i.e., distal end portions of optical conduits for each detector) are maintained at the same fixed distance on each module to ensure homogeneous coverage over specific areas and to facilitate processing of the detected signals. The fixed spacing also provides consistent spatial (lateral and depth) resolution across the target area of interest, e.g., brain tissue. Moreover, maintaining a known distance between the light source, e.g., light emitter, and the detector allows subsequent processing of the detected signals to infer spatial (e.g., depth localization, inverse modeling) information about the detected signals. Detectors of a module may be alternatively disposed on the module as may serve a particular implementation.
In
Wearable assembly 804 may implement wearable assembly 602 and may be configured as headgear and/or any other type of device configured to be worn by a user.
As shown in
Each of the modules described herein may be inserted into appropriately shaped slots or cutouts of a wearable assembly, as described in connection with
As shown in
Control circuit 902 may be configured to output, to photodetector 904, a bias voltage 912 to arm photodetector 904 to detect photons. Bias voltage 912 may be configured to have a voltage level that is a predetermined voltage level higher than a breakdown voltage of photodetector 904. The difference between bias voltage 912 and the breakdown voltage may define an overvoltage for photodetector 904. The overvoltage may affect the sensitivity of photodetector 904, as setting bias voltage 912 to be higher than the breakdown voltage by a particular overvoltage allows for an electric field that is primed for an avalanche to occur in response to detecting a single photon. However, due to process variations, the breakdown voltage of photodetectors 904 may vary. As a result, while bias voltage 912 may be set to a voltage level that is configured to be a particular overvoltage higher than the breakdown voltage, an actual overvoltage may vary among photodetectors 904. The varying overvoltage may result in varying sensitivity (e.g., photon detection probability) among photodetectors 904. Such varying sensitivity may affect histograms generated based on combining outputs from photodetectors 904.
Control circuit 902 may compensate for such variations among photodetectors 904 by providing a current 914 along with bias voltage 912 to photodetectors 904. Control circuit 902 may be configured to provide bias voltage 912 to a first terminal of each photodetector 904 and current 914 to a second terminal of each photodetector 904. For example, control circuit 902 may provide bias voltage 912 to a cathode of each photodetector 904 and current 914 to an anode of each photodetector 904. Current 914 may be configured to discharge the second terminal (e.g., the anode) of each photodetector 904 a fixed amount so that a voltage across each photodetector 904 may be a consistent predetermined overvoltage level for photodetectors 904.
Additionally or alternatively, control circuit 902 may provide bias voltage 912 to the anode of each photodetector 904 and current 914 to the cathode of each photodetector 904. In this configuration, current 914 may be configured to charge the second terminal (e.g., the cathode) of photodetector 904 a fixed amount so that the voltage across photodetector 904 may be the consistent predetermined overvoltage level for photodetectors 904.
In either configuration, the consistent overvoltage for photodetectors 904 may allow optical measurement system 900 to maintain a consistent sensitivity across photodetectors 904, which may allow for accurate histograms generated based on outputs of photodetectors 904 and/or provide other advantages and benefits described herein.
Circuit 1000 further includes a first transistor 1008, which may be configured to act as a switch to selectively couple current source 1006 to anode 1004 of photodetector 904 via a second transistor 1010 and a third transistor 1012. Second transistor 1010 and third transistor 1012 may together be configured to act as a current mirror so that anode 1004 may be discharged toward ground when transistor 1008 is on and current source 1006 is coupled to anode 1004.
Current source 1006 may be configured to deliver charge for a predetermined period of time so that a voltage level of anode 1004 is drawn toward ground a predetermined voltage amount by way of the current mirror. The predetermined period of time may be set so that the predetermined voltage amount that the voltage level of anode 1004 drops equals the overvoltage for photodetector 904. In this manner, a consistent overvoltage may be maintained for photodetector 904.
At time t0, photodetector 904 may detect a photon. As a result, photodetector 904 may avalanche and charge anode 1004 to raise the voltage level of anode 1004 to equal a voltage level of a bias voltage (e.g., bias voltage 912) applied to photodetector 904 minus a breakdown voltage of photodetector 904. A voltage level 1106 may represent this voltage level (bias voltage 912 minus the breakdown voltage of photodetector 904). At time t1, a current (e.g., current 914) is applied to anode 1004 for a predetermined amount of time, shown as a duration 1108 between time t1 and time t2. For instance, transistor 1008 may be turned on for duration 1108 so that current source 1006 may be coupled to a current mirror (e.g., transistors 1010 and 1012) coupled to anode 1004. The current may be applied to anode 1004 for duration 1108 via the current mirror, so that anode 1004 is discharged to draw the voltage level of anode 1004 down a predetermined voltage amount. A voltage level 1110 may represent the voltage level of anode 1004 after current 914 is applied for duration 1108. A difference between voltage level 1106 and voltage level 1110 is shown by a voltage difference 1112, which may represent the predetermined voltage amount, which may be an overvoltage for photodetector 904.
As described, the breakdown voltage of photodetectors 904 may vary from photodetector to photodetector. Consequently, voltage level 1106 may vary among photodetectors 904, as voltage level 1106 is defined by bias voltage 912 (which may be uniform or substantially uniform across photodetectors 904) minus the breakdown voltage (which may vary). However, as current 914 may be a uniform or substantially uniform current applied for a uniform predetermined amount of time, anode 1004 may be discharged a uniform amount, resulting in a consistent overvoltage across photodetectors 904.
Circuit 1200 further includes first transistor 1206, configured to act as a switch to selectively couple current source 1006 to cathode 1002 of photodetector 904 via second transistor 1010 and third transistor 1012. Second transistor 1010 and third transistor 1012 may together be configured to act as a current mirror so that cathode may be charged a predetermined amount when transistor 1008 is on and current source 1006 is coupled to cathode 1002.
Current source 1006 may be configured to deliver charge for a predetermined period of time so that a voltage level of cathode is raised a predetermined voltage amount by way of the current mirror. The predetermined period of time may be set so that the predetermined voltage amount that the voltage level of cathode is raised equals the overvoltage for photodetector 904. In this manner, a consistent overvoltage may be maintained for photodetector 904.
In some examples, the current applied by current source 1006 may be configured to be substantially uniform across photodetectors 904 by using a current source that is shared by the array of photodetectors 904 (or a subset of the array of photodetectors 904). Further, transistor 1008 and/or transistor 1010 may also be implemented using shared transistors for the array of photodetectors 904. By using a shared current source 1006 and a shared transistor 1008, the current may be applied to the second terminals of the array of photodetectors 904 at a same current level for a same period of time to each of photodetectors 904 in the array. Transistor 1012, on the other hand, may be implemented as a separate transistor for each of photodetectors 904. Alternatively, transistor 1012 may also be implemented as a shared transistor. In other examples, current source 1006, transistor 1008, and/or transistor 1010 may be implemented as separate components for each of photodetectors 904.
In some examples, a non-transitory computer-readable medium storing computer-readable instructions may be provided in accordance with the principles described herein. The instructions, when executed by a processor of a computing device, may direct the processor and/or computing device to perform one or more operations, including one or more of the operations described herein. Such instructions may be stored and/or transmitted using any of a variety of known computer-readable media.
A non-transitory computer-readable medium as referred to herein may include any non-transitory storage medium that participates in providing data (e.g., instructions) that may be read and/or executed by a computing device (e.g., by a processor of a computing device). For example, a non-transitory computer-readable medium may include, but is not limited to, any combination of non-volatile storage media and/or volatile storage media. Exemplary non-volatile storage media include, but are not limited to, read-only memory, flash memory, a solid-state drive, a magnetic storage device (e.g. a hard disk, a floppy disk, magnetic tape, etc.), ferroelectric random-access memory (“RAM”), and an optical disc (e.g., a compact disc, a digital video disc, a Blu-ray disc, etc.). Exemplary volatile storage media include, but are not limited to, RAM (e.g., dynamic RAM).
As shown in
Communication interface 1902 may be configured to communicate with one or more computing devices. Examples of communication interface 1902 include, without limitation, a wired network interface (such as a network interface card), a wireless network interface (such as a wireless network interface card), a modem, an audio/video connection, and any other suitable interface.
Processor 1904 generally represents any type or form of processing unit capable of processing data and/or interpreting, executing, and/or directing execution of one or more of the instructions, processes, and/or operations described herein. Processor 1904 may perform operations by executing computer-executable instructions 1912 (e.g., an application, software, code, and/or other executable data instance) stored in storage device 1906.
Storage device 1906 may include one or more data storage media, devices, or configurations and may employ any type, form, and combination of data storage media and/or device. For example, storage device 1906 may include, but is not limited to, any combination of the non-volatile media and/or volatile media described herein. Electronic data, including data described herein, may be temporarily and/or permanently stored in storage device 1906. For example, data representative of computer-executable instructions 1912 configured to direct processor 1904 to perform any of the operations described herein may be stored within storage device 1906. In some examples, data may be arranged in one or more databases residing within storage device 1906.
I/O module 1908 may include one or more I/O modules configured to receive user input and provide user output. I/O module 1908 may include any hardware, firmware, software, or combination thereof supportive of input and output capabilities. For example, I/O module 1908 may include hardware and/or software for capturing user input, including, but not limited to, a keyboard or keypad, a touchscreen component (e.g., touchscreen display), a receiver (e.g., an RF or infrared receiver), motion sensors, and/or one or more input buttons.
I/O module 1908 may include one or more devices for presenting output to a user, including, but not limited to, a graphics engine, a display (e.g., a display screen), one or more output drivers (e.g., display drivers), one or more audio speakers, and one or more audio drivers. In certain embodiments, I/O module 1908 is configured to provide graphical data to a display for presentation to a user. The graphical data may be representative of one or more graphical user interfaces and/or any other graphical content as may serve a particular implementation.
In operation 2002, a control circuit of an optical measurement system applies a bias voltage to a first terminal of a photodetector configured to detect photons from a light pulse after the light pulse reflects off a target, e.g., body of a user.
In operation 2004, the control circuit applies, for a predetermined amount of time using a current source, a current to a second terminal of the photodetector to produce a predetermined voltage difference across the photodetector.
An illustrative optical measurement system includes a light source configured to emit light directed at a target. The optical measurement system further includes a photodetector configured to detect a photon of the light after the light is scattered by the target. The optical measurement system further includes a control circuit configured to arm the photodetector by applying a bias voltage to a first terminal of the photodetector and applying, for a predetermined amount of time using a current source, a current to a second terminal of the photodetector to produce a predetermined voltage difference across the photodetector.
Another illustrative optical measurement system includes a wearable system for use by a user. The wearable system includes a head-mountable component configured to be attached to a head of the user, the head-mountable component including a photodetector configured to detect photons from a light pulse after the light pulse reflects off a target within the head. The wearable system further includes a control circuit configured to arm the photodetector by applying a bias voltage to a first terminal of the photodetector and applying, for a predetermined amount of time using a current source, a current to a second terminal of the photodetector to produce a predetermined voltage difference across the photodetector.
An exemplary method includes applying, by a control circuit, a bias voltage to a first terminal of a photodetector configured to detect photons from a light pulse after the light pulse reflects off a target. The method further includes applying, by the control circuit for a predetermined amount of time using a current source, a current to a second terminal of the photodetector to produce a predetermined voltage difference across the photodetector.
In the preceding description, various exemplary embodiments have been described with reference to the accompanying drawings. It will, however, be evident that various modifications and changes may be made thereto, and additional embodiments may be implemented, without departing from the scope of the invention as set forth in the claims that follow. For example, certain features of one embodiment described herein may be combined with or substituted for features of another embodiment described herein. The description and drawings are accordingly to be regarded in an illustrative rather than a restrictive sense.
The present application claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 62/992,529, filed on Mar. 20, 2020, and to U.S. Provisional Patent Application No. 63/074,721, filed on Sep. 4, 2020. These applications are incorporated herein by reference in their respective entireties.
Number | Name | Date | Kind |
---|---|---|---|
4018534 | Thorn et al. | Apr 1977 | A |
4207892 | Binder | Jun 1980 | A |
4281645 | Jobsis | Aug 1981 | A |
4321930 | Jobsis | Mar 1982 | A |
4515165 | Carroll | May 1985 | A |
4655225 | Dahne et al. | Apr 1987 | A |
4928248 | Takahashi et al. | May 1990 | A |
4963727 | Cova | Oct 1990 | A |
4995044 | Blazo | Feb 1991 | A |
5088493 | Giannini | Feb 1992 | A |
5090415 | Yamashita | Feb 1992 | A |
5218962 | Mannheimer et al. | Jun 1993 | A |
5309458 | Carl | May 1994 | A |
5386827 | Chance et al. | Feb 1995 | A |
5528365 | Gonatas et al. | Jun 1996 | A |
5625458 | Alfano et al. | Apr 1997 | A |
5761230 | Oono et al. | Jun 1998 | A |
5853370 | Chance et al. | Dec 1998 | A |
5895984 | Renz | Apr 1999 | A |
5924982 | Chin | Jul 1999 | A |
5929982 | Anderson | Jul 1999 | A |
5983120 | Groner et al. | Nov 1999 | A |
5987045 | Albares et al. | Nov 1999 | A |
6163715 | Larsen et al. | Dec 2000 | A |
6195580 | Grable | Feb 2001 | B1 |
6240309 | Yamashita et al. | May 2001 | B1 |
6291824 | Battarbee et al. | Sep 2001 | B1 |
6291842 | Nakayama | Sep 2001 | B1 |
6384663 | Cova et al. | May 2002 | B2 |
6541752 | Zappa et al. | Apr 2003 | B2 |
6542763 | Yamashita et al. | Apr 2003 | B1 |
6618614 | Chance | Sep 2003 | B1 |
6640133 | Yamashita | Oct 2003 | B2 |
6683294 | Herbert et al. | Jan 2004 | B1 |
6748254 | O′Neil | Jun 2004 | B2 |
6992772 | Block | Jan 2006 | B2 |
7095491 | Forstner et al. | Aug 2006 | B2 |
7356365 | Schurman | Apr 2008 | B2 |
7507596 | Yaung et al. | Mar 2009 | B2 |
7547872 | Niclass et al. | Jun 2009 | B2 |
7613504 | Rowe | Nov 2009 | B2 |
7667400 | Goushcha | Feb 2010 | B1 |
7705284 | Inoue et al. | Apr 2010 | B2 |
7714292 | Agarwal et al. | May 2010 | B2 |
7774047 | Yamashita et al. | Aug 2010 | B2 |
7888973 | Rezzi et al. | Feb 2011 | B1 |
7899506 | Xu et al. | Mar 2011 | B2 |
8026471 | Itzler | Sep 2011 | B2 |
8078250 | Chen et al. | Dec 2011 | B2 |
8082015 | Yodh et al. | Dec 2011 | B2 |
8115170 | Stellari et al. | Feb 2012 | B2 |
8168934 | Niclass et al. | May 2012 | B2 |
8269563 | Ballantyne | Sep 2012 | B2 |
8352012 | Besio | Jan 2013 | B2 |
8633431 | Kim | Jan 2014 | B2 |
8637875 | Finkelstein et al. | Jan 2014 | B2 |
8754378 | Prescher et al. | Jun 2014 | B2 |
8817257 | Herve | Aug 2014 | B2 |
8937509 | Xu et al. | Jan 2015 | B2 |
8986207 | Li | Mar 2015 | B2 |
9012860 | Nyman et al. | Apr 2015 | B2 |
9041136 | Chia | May 2015 | B2 |
9058081 | Baxter | Jun 2015 | B2 |
9076707 | Harmon | Jul 2015 | B2 |
9101279 | Ritchey et al. | Aug 2015 | B2 |
9131861 | Ince et al. | Sep 2015 | B2 |
9157858 | Claps | Oct 2015 | B2 |
9160949 | Zhang et al. | Oct 2015 | B2 |
9176241 | Frach | Nov 2015 | B2 |
9178100 | Webster et al. | Nov 2015 | B2 |
9190552 | Brunel et al. | Nov 2015 | B2 |
9201138 | Eisele et al. | Dec 2015 | B2 |
9209320 | Webster | Dec 2015 | B1 |
9257523 | Schneider et al. | Feb 2016 | B2 |
9257589 | Niclass et al. | Feb 2016 | B2 |
9299732 | Webster et al. | Mar 2016 | B2 |
9299873 | Mazzillo et al. | Mar 2016 | B2 |
9312401 | Webster | Apr 2016 | B2 |
9316735 | Baxter | Apr 2016 | B2 |
9331116 | Webster | May 2016 | B2 |
9368487 | Su et al. | Jun 2016 | B1 |
9401448 | Bienfang et al. | Jul 2016 | B2 |
9407796 | Dinten et al. | Aug 2016 | B2 |
9419635 | Kumar et al. | Aug 2016 | B2 |
9431439 | Soga et al. | Aug 2016 | B2 |
9442201 | Schmand et al. | Sep 2016 | B2 |
9449377 | Sarkar et al. | Sep 2016 | B2 |
9450007 | Motta et al. | Sep 2016 | B1 |
9466631 | Fallica et al. | Oct 2016 | B2 |
9476979 | Drader et al. | Oct 2016 | B2 |
9478579 | Dai et al. | Oct 2016 | B2 |
9529079 | Droz | Dec 2016 | B1 |
9535157 | Caley et al. | Jan 2017 | B2 |
9554738 | Gulati et al. | Jan 2017 | B1 |
9574936 | Heinonen | Feb 2017 | B2 |
9625580 | Kotelnikov et al. | Apr 2017 | B2 |
9627569 | Harmon | Apr 2017 | B2 |
9634826 | Park | Apr 2017 | B1 |
9639063 | Dutton et al. | May 2017 | B2 |
9640704 | Frey et al. | May 2017 | B2 |
9658158 | Renna et al. | May 2017 | B2 |
9659980 | McGarvey et al. | May 2017 | B2 |
9671284 | Dandin | Jun 2017 | B1 |
9681844 | Xu et al. | Jun 2017 | B2 |
9685576 | Webster | Jun 2017 | B2 |
9702758 | Nouri | Jul 2017 | B2 |
9728659 | Hirigoyen et al. | Aug 2017 | B2 |
9741879 | Frey et al. | Aug 2017 | B2 |
9753351 | Eldada | Sep 2017 | B2 |
9767246 | Dolinsky et al. | Sep 2017 | B2 |
9768211 | Harmon | Sep 2017 | B2 |
9773930 | Motta et al. | Sep 2017 | B2 |
9804092 | Zeng et al. | Oct 2017 | B2 |
9812438 | Schneider et al. | Nov 2017 | B2 |
9831283 | Shepard et al. | Nov 2017 | B2 |
9851302 | Mattioli Della Rocca et al. | Dec 2017 | B2 |
9867250 | Powers et al. | Jan 2018 | B1 |
9869753 | Eldada | Jan 2018 | B2 |
9881963 | Chen et al. | Jan 2018 | B1 |
9882003 | Aharoni | Jan 2018 | B1 |
9886095 | Pothier | Feb 2018 | B2 |
9899544 | Mazzillo et al. | Feb 2018 | B1 |
9899557 | Muscara' et al. | Feb 2018 | B2 |
9939316 | Scott et al. | Apr 2018 | B2 |
9939536 | O′Neill et al. | Apr 2018 | B2 |
9946344 | Ayaz et al. | Apr 2018 | B2 |
D817553 | Aaskov et al. | May 2018 | S |
9983670 | Coleman | May 2018 | B2 |
9997551 | Mandai | Jun 2018 | B2 |
10016137 | Yang et al. | Jul 2018 | B1 |
D825112 | Saez | Aug 2018 | S |
10056415 | Na et al. | Aug 2018 | B2 |
10103513 | Zhang et al. | Oct 2018 | B1 |
10141458 | Zhang et al. | Nov 2018 | B2 |
10154815 | Al-Ali et al. | Dec 2018 | B2 |
10157954 | Na et al. | Dec 2018 | B2 |
10158038 | Do Valle et al. | Dec 2018 | B1 |
10219700 | Yang et al. | Mar 2019 | B1 |
10256264 | Na et al. | Apr 2019 | B2 |
10340408 | Katnani | Jul 2019 | B1 |
10424683 | Do Valle | Sep 2019 | B1 |
10483125 | Inoue | Nov 2019 | B2 |
10515993 | Field et al. | Dec 2019 | B2 |
10533893 | Leonardo | Jan 2020 | B2 |
10541660 | McKisson | Jan 2020 | B2 |
10558171 | Kondo | Feb 2020 | B2 |
10594306 | Dandin | Mar 2020 | B2 |
10627460 | Alford et al. | Apr 2020 | B2 |
10695167 | Van Heugten et al. | Jun 2020 | B2 |
10697829 | Delic | Jun 2020 | B2 |
10772561 | Donaldson | Sep 2020 | B2 |
10809796 | Armstrong-Muntner | Oct 2020 | B2 |
10825847 | Furukawa | Nov 2020 | B2 |
10912504 | Nakaji | Feb 2021 | B2 |
10976386 | Alford | Apr 2021 | B2 |
10983177 | Jiménez-Martínez | Apr 2021 | B2 |
10996293 | Mohseni | May 2021 | B2 |
11006876 | Johnson | May 2021 | B2 |
11006878 | Johnson | May 2021 | B2 |
11137283 | Balamurugan et al. | Oct 2021 | B2 |
11213245 | Horstmeyer et al. | Jan 2022 | B2 |
11630310 | Seidman et al. | Apr 2023 | B2 |
20020033454 | Cheng et al. | Mar 2002 | A1 |
20020195545 | Nishimura | Dec 2002 | A1 |
20040057478 | Saito | Mar 2004 | A1 |
20040064052 | Chance et al. | Apr 2004 | A1 |
20040078216 | Toto | Apr 2004 | A1 |
20040160996 | Giorgi et al. | Aug 2004 | A1 |
20050038344 | Chance | Feb 2005 | A1 |
20050059869 | Scharf et al. | Mar 2005 | A1 |
20050061986 | Kardynal et al. | Mar 2005 | A1 |
20050124863 | Cook | Jun 2005 | A1 |
20050228291 | Chance | Oct 2005 | A1 |
20060171845 | Martin | Aug 2006 | A1 |
20060197452 | Zhang | Sep 2006 | A1 |
20060264722 | Hannula et al. | Nov 2006 | A1 |
20070038116 | Yamanaka | Feb 2007 | A1 |
20070083097 | Fujiwara | Apr 2007 | A1 |
20080021341 | Harris et al. | Jan 2008 | A1 |
20090012402 | Mintz | Jan 2009 | A1 |
20090054789 | Kiguchi et al. | Feb 2009 | A1 |
20090163775 | Barrett | Jun 2009 | A1 |
20090313048 | Kahn et al. | Dec 2009 | A1 |
20100007413 | Herleikson et al. | Jan 2010 | A1 |
20100188649 | Prahl et al. | Jul 2010 | A1 |
20100210952 | Taira et al. | Aug 2010 | A1 |
20100249557 | Besko et al. | Sep 2010 | A1 |
20100301194 | Patel | Dec 2010 | A1 |
20110208675 | Shoureshi et al. | Aug 2011 | A1 |
20110248175 | Frach | Oct 2011 | A1 |
20120016635 | Brodsky et al. | Jan 2012 | A1 |
20120029304 | Medina et al. | Feb 2012 | A1 |
20120083673 | Al-Ali et al. | Apr 2012 | A1 |
20120101838 | Lingard et al. | Apr 2012 | A1 |
20130015331 | Birk | Jan 2013 | A1 |
20130030267 | Lisogurski | Jan 2013 | A1 |
20130030270 | Chiou et al. | Jan 2013 | A1 |
20130032713 | Barbi et al. | Feb 2013 | A1 |
20130090541 | MacFarlane et al. | Apr 2013 | A1 |
20130144644 | Simpson | Jun 2013 | A1 |
20130153754 | Drader et al. | Jun 2013 | A1 |
20130221221 | Bouzid et al. | Aug 2013 | A1 |
20130225953 | Oliviero et al. | Aug 2013 | A1 |
20130300838 | Borowski et al. | Nov 2013 | A1 |
20130342835 | Blacksberg | Dec 2013 | A1 |
20140027607 | Mordarski et al. | Jan 2014 | A1 |
20140028211 | Imam | Jan 2014 | A1 |
20140055181 | Chavpas | Feb 2014 | A1 |
20140066783 | Kiani | Mar 2014 | A1 |
20140171757 | Kawato et al. | Jun 2014 | A1 |
20140185643 | McComb et al. | Jul 2014 | A1 |
20140191115 | Webster et al. | Jul 2014 | A1 |
20140211194 | Pacala et al. | Jul 2014 | A1 |
20140217264 | Shepard | Aug 2014 | A1 |
20140275891 | Muehlemann et al. | Sep 2014 | A1 |
20140289001 | Shelton | Sep 2014 | A1 |
20140291481 | Zhang et al. | Oct 2014 | A1 |
20150011848 | Ruchti et al. | Jan 2015 | A1 |
20150038811 | Asaka | Feb 2015 | A1 |
20150038812 | Ayaz et al. | Feb 2015 | A1 |
20150041625 | Dutton | Feb 2015 | A1 |
20150041627 | Webster | Feb 2015 | A1 |
20150054111 | Niclass et al. | Feb 2015 | A1 |
20150057511 | Basu | Feb 2015 | A1 |
20150077279 | Song | Mar 2015 | A1 |
20150094552 | Golda | Apr 2015 | A1 |
20150150505 | Kaskoun et al. | Jun 2015 | A1 |
20150157262 | Schuessler | Jun 2015 | A1 |
20150157435 | Chasins et al. | Jun 2015 | A1 |
20150182136 | Durduran et al. | Jul 2015 | A1 |
20150192677 | Yu et al. | Jul 2015 | A1 |
20150200222 | Webster | Jul 2015 | A1 |
20150201841 | Ishikawa et al. | Jul 2015 | A1 |
20150293224 | Eldada et al. | Oct 2015 | A1 |
20150327777 | Kostic et al. | Nov 2015 | A1 |
20150333095 | Fallica et al. | Nov 2015 | A1 |
20150355019 | Nouri et al. | Dec 2015 | A1 |
20150364635 | Bodlovic et al. | Dec 2015 | A1 |
20160049765 | Eldada | Feb 2016 | A1 |
20160099371 | Webster | Apr 2016 | A1 |
20160119983 | Moore | Apr 2016 | A1 |
20160150963 | Roukes et al. | Jun 2016 | A1 |
20160161600 | Eldada et al. | Jun 2016 | A1 |
20160181302 | McGarvey et al. | Jun 2016 | A1 |
20160182902 | Guo | Jun 2016 | A1 |
20160218236 | Dhulla et al. | Jul 2016 | A1 |
20160247301 | Fang | Aug 2016 | A1 |
20160278715 | Yu et al. | Sep 2016 | A1 |
20160287107 | Szabados | Oct 2016 | A1 |
20160296168 | Abreu | Oct 2016 | A1 |
20160341656 | Liu et al. | Nov 2016 | A1 |
20160345880 | Nakaji et al. | Dec 2016 | A1 |
20160349368 | Stutz et al. | Dec 2016 | A1 |
20160356718 | Yoon et al. | Dec 2016 | A1 |
20160357260 | Raynor et al. | Dec 2016 | A1 |
20170030769 | Clemens et al. | Feb 2017 | A1 |
20170047372 | McGarvey et al. | Feb 2017 | A1 |
20170052065 | Sharma et al. | Feb 2017 | A1 |
20170085547 | De Aguiar et al. | Mar 2017 | A1 |
20170118423 | Zhou et al. | Apr 2017 | A1 |
20170124713 | Jurgenson et al. | May 2017 | A1 |
20170131143 | Andreou et al. | May 2017 | A1 |
20170139041 | Drader et al. | May 2017 | A1 |
20170141100 | Tseng et al. | May 2017 | A1 |
20170164857 | Soulet De Brugiere | Jun 2017 | A1 |
20170172447 | Mitra et al. | Jun 2017 | A1 |
20170176579 | Niclass et al. | Jun 2017 | A1 |
20170176596 | Shpunt et al. | Jun 2017 | A1 |
20170179173 | Mandai et al. | Jun 2017 | A1 |
20170186798 | Yang et al. | Jun 2017 | A1 |
20170202518 | Furman et al. | Jul 2017 | A1 |
20170265822 | Du | Sep 2017 | A1 |
20170276545 | Henriksson | Sep 2017 | A1 |
20170281086 | Donaldson | Oct 2017 | A1 |
20170299700 | Pacala et al. | Oct 2017 | A1 |
20170303789 | Tichauer et al. | Oct 2017 | A1 |
20170314989 | Mazzillo et al. | Nov 2017 | A1 |
20170338969 | Paul | Nov 2017 | A1 |
20170363467 | Clemens et al. | Dec 2017 | A1 |
20170367650 | Wallois | Dec 2017 | A1 |
20180003821 | Imai | Jan 2018 | A1 |
20180014741 | Chou | Jan 2018 | A1 |
20180019268 | Zhang et al. | Jan 2018 | A1 |
20180020960 | Sarussi | Jan 2018 | A1 |
20180026147 | Zhang et al. | Jan 2018 | A1 |
20180027196 | Yang et al. | Jan 2018 | A1 |
20180033895 | Mazzillo et al. | Feb 2018 | A1 |
20180039053 | Kremer et al. | Feb 2018 | A1 |
20180045816 | Jarosinski et al. | Feb 2018 | A1 |
20180062345 | Bills et al. | Mar 2018 | A1 |
20180066986 | Kasai et al. | Mar 2018 | A1 |
20180069043 | Pan et al. | Mar 2018 | A1 |
20180070830 | Sutin et al. | Mar 2018 | A1 |
20180070831 | Sutin et al. | Mar 2018 | A1 |
20180081061 | Mandai et al. | Mar 2018 | A1 |
20180089531 | Geva et al. | Mar 2018 | A1 |
20180089848 | Yang et al. | Mar 2018 | A1 |
20180090526 | Mandal et al. | Mar 2018 | A1 |
20180090536 | Mandai et al. | Mar 2018 | A1 |
20180102442 | Wang et al. | Apr 2018 | A1 |
20180103528 | Moore | Apr 2018 | A1 |
20180103861 | Sutin et al. | Apr 2018 | A1 |
20180117331 | Kuzniecky | May 2018 | A1 |
20180120152 | Leonardo | May 2018 | A1 |
20180122560 | Okuda | May 2018 | A1 |
20180156660 | Turgeon | Jun 2018 | A1 |
20180167606 | Cazaux et al. | Jun 2018 | A1 |
20180175230 | Droz et al. | Jun 2018 | A1 |
20180180473 | Clemens et al. | Jun 2018 | A1 |
20180185667 | Huang | Jul 2018 | A1 |
20180192931 | Linden et al. | Jul 2018 | A1 |
20180217261 | Wang | Aug 2018 | A1 |
20180296094 | Nakamura | Oct 2018 | A1 |
20180366342 | Inque et al. | Dec 2018 | A1 |
20190006399 | Otake et al. | Jan 2019 | A1 |
20190025406 | Krelboim et al. | Jan 2019 | A1 |
20190026849 | Demeyer | Jan 2019 | A1 |
20190088697 | Furukawa et al. | Mar 2019 | A1 |
20190091483 | Deckert | Mar 2019 | A1 |
20190113385 | Fukuchi | Apr 2019 | A1 |
20190120975 | Ouvrier-Buffet | Apr 2019 | A1 |
20190167211 | Everman et al. | Jun 2019 | A1 |
20190175068 | Everdell | Jun 2019 | A1 |
20190192031 | Laszlo et al. | Jun 2019 | A1 |
20190200888 | Poltorak | Jul 2019 | A1 |
20190209012 | Yoshimoto et al. | Jul 2019 | A1 |
20190239753 | Wentz | Aug 2019 | A1 |
20190261869 | Franceschini | Aug 2019 | A1 |
20190298158 | Dhaliwal | Oct 2019 | A1 |
20190343395 | Cussac | Nov 2019 | A1 |
20190355773 | Field et al. | Nov 2019 | A1 |
20190355861 | Katnani | Nov 2019 | A1 |
20190363210 | Do Valle | Nov 2019 | A1 |
20190378869 | Field et al. | Dec 2019 | A1 |
20190388018 | Horstmeyer | Dec 2019 | A1 |
20190391213 | Alford | Dec 2019 | A1 |
20200022581 | Vanegas | Jan 2020 | A1 |
20200041727 | Yamamoto | Feb 2020 | A1 |
20200044098 | Azuma | Feb 2020 | A1 |
20200056263 | Bhattacharyya | Feb 2020 | A1 |
20200057115 | Jiménez-Martínez | Feb 2020 | A1 |
20200057116 | Zorzos et al. | Feb 2020 | A1 |
20200057146 | Steinkogler et al. | Feb 2020 | A1 |
20200060542 | Alford | Feb 2020 | A1 |
20200088811 | Mohseni | Mar 2020 | A1 |
20200109481 | Sobek | Apr 2020 | A1 |
20200123416 | Bhattacharyya | Apr 2020 | A1 |
20200136632 | Lin | Apr 2020 | A1 |
20200182692 | Lilic | Jun 2020 | A1 |
20200188030 | Kopper et al. | Jun 2020 | A1 |
20200191883 | Bhattacharyya | Jun 2020 | A1 |
20200196932 | Johnson et al. | Jun 2020 | A1 |
20200241094 | Alford | Jul 2020 | A1 |
20200253479 | Nurmikko | Aug 2020 | A1 |
20200256929 | Ledbetter et al. | Aug 2020 | A1 |
20200309873 | Ledbetter et al. | Oct 2020 | A1 |
20200315510 | Johnson | Oct 2020 | A1 |
20200334559 | Anderson | Oct 2020 | A1 |
20200337624 | Johnson | Oct 2020 | A1 |
20200341081 | Mohseni et al. | Oct 2020 | A1 |
20200348368 | Garber et al. | Nov 2020 | A1 |
20200379095 | Kappel et al. | Dec 2020 | A1 |
20200381128 | Pratt | Dec 2020 | A1 |
20200390358 | Johnson | Dec 2020 | A1 |
20200393902 | Mann et al. | Dec 2020 | A1 |
20200400763 | Pratt | Dec 2020 | A1 |
20210015385 | Katnani | Jan 2021 | A1 |
20210011094 | Bednarke | Feb 2021 | A1 |
20210041512 | Pratt | Feb 2021 | A1 |
20210063510 | Ledbetter | Mar 2021 | A1 |
20210013974 | Seidman | May 2021 | A1 |
20210139742 | Seidman | May 2021 | A1 |
20210186138 | Bartels et al. | Jun 2021 | A1 |
20210223098 | Ledvina et al. | Jul 2021 | A1 |
20210265512 | Ayel | Aug 2021 | A1 |
20210290064 | Do Valle | Sep 2021 | A1 |
20210294996 | Field | Sep 2021 | A1 |
Number | Date | Country |
---|---|---|
200950235 | Sep 2007 | CN |
107865635 | Apr 2018 | CN |
0656536 | Apr 2004 | EP |
2294973 | Mar 2011 | EP |
3419168 | Dec 2018 | EP |
3487072 | May 2019 | EP |
3011932 | Apr 2015 | FR |
2012125370 | Jan 2015 | JP |
20170087639 | Jul 2013 | KR |
8804034 | Jun 1988 | WO |
1999053577 | Oct 1999 | WO |
2008144831 | Dec 2008 | WO |
2011083563 | Jul 2011 | WO |
2012135068 | Oct 2012 | WO |
2013034770 | Mar 2013 | WO |
2013066959 | May 2013 | WO |
2015052523 | Apr 2015 | WO |
2015109005 | Jul 2015 | WO |
2016166002 | Oct 2016 | WO |
2017004663 | Jan 2017 | WO |
2017083826 | May 2017 | WO |
2017130682 | Aug 2017 | WO |
2017150146 | Sep 2017 | WO |
2017203936 | Nov 2017 | WO |
2018007829 | Jan 2018 | WO |
2018033751 | Feb 2018 | WO |
2018122560 | Jul 2018 | WO |
2019221784 | Nov 2019 | WO |
Entry |
---|
Chen, et al., “A PVT Insensitive Field Programmable Gate Array Time-to-digital Converter”, 2013 IEEE Nordic-Mediterranean Workshop on Time-To-Digital Converters. Oct. 3, 2013. |
Field, et al., “A 100-fps, Time-Correlated Single-PhotonCounting-Based Fluorescence-Lifetime Imager in 130-nm CMOS”, IEEE Journal of Solid-State Circuits, vol. 49, No. 4, Apr. 2014. |
Lebid, et al., “Multi-Timescale Measurements of Brain Responses in Visual Cortex During Functional Stimulation Using Time-Resolved Spectroscopy”, SPIE vol. 5826. Dec. 31, 2005. p. 609, last paragraph—p. 610, paragraph 1. |
Zheng, et al., “An Integrated Bias Voltage Control Method for SPAD Arrays”, Oct. 1, 2018, IEEE Service Center. |
International Search Report and Written Opinion received in International Application No. PCT/2020/027537, dated Sep. 7, 2020. |
International Search Report and Written Opinion received in International Application No. PCT/2020/028820, dated Aug. 26, 2020. |
International Search Report and Written Opinion received in International Application No. PCT/US20/34062, dated Aug. 26, 2020. |
International Search Report and Written Opinion received in International Application No. PCT/US2018/058580, dated Feb. 12, 2019. |
International Search Report and Written Opinion received in International Application No. PCT/US2018/062777, dated Feb. 13, 2019. |
International Search Report and Written Opinion received in International Application No. PCT/US2019/019317, dated May 28, 2019. |
Non-Final Office Action received in U.S. Appl. No. 16/177,351, dated Apr. 1, 2019. |
Non-Final Office Action received in U.S. Appl. No. 16/283,730, dated May 16, 2019. |
Non-Final Office Action received in U.S. Appl. No. 16/370,991, dated Feb. 10, 2020. |
Non-Final Office Action received in U.S. Appl. No. 16/537,360, dated Feb. 25, 2020. |
Non-Final Office Action received in U.S. Appl. No. 16/544,850, dated Jun. 25, 2020. |
Non-Final Office Action received in U.S. Appl. No. 16/856,524, dated Dec. 1, 2020. |
Partial Search Report received in International Application No. PCT/2020/028820, dated Jul. 1, 2020. |
Partial Search Report received in International Application No. PCT/US2020/027537, dated Jul. 17, 2020. |
Alayed, et al.,“Characterization of a Time-Resolved Diffuse Optical Spectroscopy Prototype Using Low-Cost, Compact Single Photon Avalanche Detectors for Tissue Optics Applications,” Sensors 2018, 18, 3680; doi:10.3390/s18113680. |
Bellis, et al.,“Photon counting imaging: the DigitalAPD,” Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Feb. 2006, vol. 6068, pp. 111-120. |
Blutman, et al.,“A 0.1 pJ Freeze Vernier Time-to-Digital Converter in 65nm CMOS,” 2014 International Symposium on Circuits and Systems (ISCAS), Melbourne, Australia. |
Cambie, et al.,“Every photon counts: understanding and optimizing photon paths in luminescent solar concentrator-based photomicroreactors (LSC-PMs),” React. Chem. Eng., 2017, 2, 561-566. |
Contini, et al.,“Photon migration through a turbid slab described by a model based on diffusion approximation. I. Theory,” Appl. Opt. 36(19), 4587 (1997). |
Dalla Mora, et al.,“Fast-Gated Single-Photon Avalanche Diode for Wide Dynamic Range Near Infrared Spectroscopy,” IEEE Journal of Selected Topics in Quantum Electronics, vol. 16, No. 4, Jul./Aug. 2010. |
Dalla Mora, et al.,“Memory effect in silicon time-gated single-photon avalanche diodes,” http://dx.doi.org/10.1063/1.4915332, Journal of Applied Physics 117, 114501, 2015. |
De Heyn, et al.,“A fast start-up 3GHz-10GHz digitally controlled oscillator for UWB impulse radio in 90nm CMOS,” 2007 European Solid-State Circuits Conference—(ESSCIRC), Munich, Germany, pp. 484-487. |
Di Sieno, et al.,“Probe-hosted large area silicon photomultiplier and high-throughput timing electronics for enhanced performance time-domain functional near-infrared spectroscopy,” Biomed. Opt. Express 11(11), 6389 (2020). |
Dutton, et al.,“A Time-Correlated Single-Photon-Counting Sensor with 14GS/s Histogramming Time-to-Digital Converter,” 2015 IEEE International Solid-State Circuits Conference ISSCC 2015 / Session 11 / Sensors and Imagers for Life Sciences / 11.5. |
Fishburn, et al.,“Temporal Derivative Distribution Repair (TDDR): A motion correction method for fNIRS,” Neuroimage. Jan. 1, 2019; 184: 171-179. doi:10.1016/j.neuroimage.2018.09.025. |
Fisher, et al.,“A Reconfigurable Single-Photon-Counting Integrating Receiver for Optical Communications,” IEEE Journal of Solid-State Circuits, vol. 48, No. 7, Jul. 2013, https://www.researchgate.net/publication/260626902. |
Gallivanoni, et al.,“Progress in Quenching Circuits for Single Photon Avalanche Diodes,” IEEE Transactions on Nuclear Science, vol. 57, No. 6, Dec. 2010. |
Gnecchi, et al.,“A 1×16 SIPM Array for Automotive 3D Imaging LiDAR Systems.” |
Harmon, et al.,“Compound Semiconductor SPAD Arrays,” LightSpin Technologies, http://www.lightspintech.com/publications.html. |
Henderson, et al.,“A 192 x 128 Time Correlated SPAD Image Sensor in 40-nm CMOS Technology,” IEEE Journal of Solid-State Circuits, 2019. |
Henderson, et al.,“A 256×256 40nm/90nm CMOS 3D-Stacked 120dB Dynamic-Range Reconfigurable Time-Resolved SPAD Imager,” 2019 IEEE International Solid-State Circuits Conference—(ISSCC), San Francisco, CA, USA, 2019, pp. 106-108. doi: 10.1109/ISSCC.2019.8662355. |
Huppert, et al.,“HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain,” Appl. Opt. 48(10), D280 (2009). |
Kienle, et al.,“Improved solutions of the steady-state and the time-resolved diffusion equations for reflectance from a semi-infinite turbid medium,” J. Opt. Soc. Am. A 14(1), 246 (1997). |
Konugolu, et al.,“Broadband (600-1350 nm) Time-Resolved Diffuse Optical Spectrometer for Clinical Use,” IEEE Journal of Selected Topics in Quantum Electronics, vol. 22, No. 3, May/Jun. 2016. |
Lacerenza, et al.,“Wearable and wireless time-domain near-infrared spectroscopy system for brain and muscle hemodynamic monitoring,” Biomed. Opt. Express 11 (10), 5934 (2020). |
Lange, et al.,“Clinical Brain Monitoring with Time Domain NIRS: A Review and Future Perspectives,” Applied Sciences 9(8), 1612 (2019). |
Lange, et al.,“MAESTROS: A Multiwavelength Time-Domain NIRS System to Monitor Changes in Oxygenation and Oxidation State of Cytochrome-C-Oxidase,” IEEE J. Select. Topics Quantum Electron. 25(1), 1-12 (2019). |
Lee, et al.,“High-Performance Back-Illuminated Three-Dimensional Stacked Single-Photon Avalanche Diode Implemented in 45-nm CMOS Technology,” IEEE Journal of Selected Topics in Quantum Electronics 6, 1-9 (2018). |
Mandai, et al.,“A 4 X 4 X 416 digital SIPM array with 192 TDCs for multiple high-resolution timestamp acquisition,” 2013 JINST 8 PO5024. |
Martelli, et al.,“Optimal estimation reconstruction of the optical properties of a two-layered tissue phantom from time-resolved single-distance measurements,” Journal of Biomedical Optics 20(11), 115001 (Nov. 2015). |
Maruyama, et al.,“A 1024 x 8, 700-ps Time-Gated SPAD Line Sensor for Planetary Surface Exploration With Laser Raman Spectroscopy and LIBS,” IEEE Journal of Solid-State Circuits, vol. 49, No. 1, Jan. 2014. |
Mita, et al.,“High-Speed and Compact Quenching Circuit for Single-Photon Avalanche Diodes,” IEEE Transactions on Instrumentation and Measurement, vol. 57, No. 3, Mar. 2008. pp. 543-547. |
Mora, et al.,“Fast silicon photomultiplier improves signal harvesting and reduces complexity in time-domain diffuse optics,” Opt. Express 23(11), 13937 (2015). |
Mora, et al.,“Fast-Gated Single-Photon Avalanche Diode for Wide Dynamic Range Near Infrared Spectroscopy,” IEEE Journal of Selected Topics in Quantum Electronics, vol. 16, No. 4, pp. 1023-1030, Jul./Aug. 2010. |
Parmesan, et al.,“A 256×256 SPAD array with in-pixel Time to Amplitude Conversion for Fluorescence Lifetime Imaging Microscopy,” 2015. |
Pifferi, et al.,“Performance assessment of photon migration instruments: the MEDPHOT protocol,” Applied Optics, 44(11), 2104-2114. |
Prahl, et al.,“Optical Absorption of Hemoglobin,” http://omlc.ogi.edu/spectra/hemoglobin/index.html. |
Puszka, et al.,“Time-resolved diffuse optical tomography using fast-gated single-photon avalanche diodes,” Biomedical optics express, 2013, vol. 4, No. 8, pp. 1351-1365 (Year: 2013). |
Re, et al.,“Multi-channel medical device for time domain functional near infrared spectroscopy based on wavelength space multiplexing,” Biomed. Opt. Express 4(10), 2231 (2013). |
Renna, et al.,“Eight-Wavelength, Dual Detection Channel Instrument for Near-Infrared Time-Resolved Diffuse Optical Spectroscopy,” IEEE J. Select. Topics Quantum Electron. 25(1), 1-11 (2019). |
Richardson, et al.,“A 32x32 50ps resolution 10 bit time to digital converter array in 130nm CMOS for time correlated imaging,” CICC 2009 Proceedings of the IEEE 2009 Custom Integrated Circuits Conference. IEEE Society, San Jose, U.S.A., pp. 77-80, CICC 2009, San Jose, U.S.A., Sep. 13, 2009. https://doi.org/doi:10.1109/CICC.2009.5280890. |
Takai, et al.,“Single-Photon Avalanche Diode with Enhanced NIR-Sensitivity for Automotive LIDAR Systems,” Sensors, 2016, 16(4): 459, pp. 1-9 (Year: 2016). |
Torricelli, et al.,“Time domain functional NIRS imaging for human brain mapping,” Neurolmage 85, 28-50 (2014). |
Wabnitz, et al.,“Depth-selective data analysis for time-domain fNIRS: moments vs. time windows,” Biomed. Opt. Express 11(8), 4224 (2020). |
Wabnitz, et al.,“Performance assessment of time-domain optical brain imagers, part 1: basic instrumental performance protocol,” Journal of Biomedical Optics 19(8), 086010 (Aug. 2014). |
Wabnitz, et al.,“Performance assessment of time-domain optical brain imagers, part 2: nEUROPt protocol,” Journal of Biomedical Optics 19(8), 086012 (Aug. 2014). |
Wojtkiewicz, et al.,“Self-calibrating time-resolved near infrared spectroscopy,” Biomed. Opt. Express 10(5), 2657 (2019). |
Zhang, et al.,“A CMOS SPAD Imager with Collision Detection and 128 Dynamically Reallocating TDCs for Single-Photon Counting and 3D Time-of-Flight Imaging,” Sensors (Basel, Switzerland), 18(11), 4016. doi:10.3390/s18114016. |
Zucchelli, et al.,“Method for the discrimination of superficial and deep absorption variations by time domain fNIRS,” 2013 OSA Dec. 1, 2013 | vol. 4, No. 12 | DOI:10.1364/BOE.4.002893 | Biomedical Optics Express 2893. |
“emojipedia.org”, https://emojipedia.org (accessed May 27, 2021). |
“International Search Report and Written Opinion received in International Application No. PCT/2021/018188”. |
“International Search Report and Written Opinion received in International Application No. PCT/US2021/018155”. |
“International Search Report and Written Opinion received in International Application No. PCT/US2021/018187”. |
“International Search Report and Written Opinion received in International Application No. PCT/US2021/018190”. |
“scienceofpeople.com/emojis”, https://www.scienceofpeople.com/emojis/ (accessed May 27, 2021). |
Hebert, et al.,“Spatiotemporal image correlation spectroscopy (STICS) theory, verification, and application to protein velocity mapping in living CHO cells”, Biophysical journal 88, No. 5 (2005): 3601-3614. |
Kheng, et al.,“Image Processing”, https://www.comp.nus.edu.sg/˜cs4243/lecture/imageproc.pdf, Mar. 9, 2014. |
Sneha, et al.,“Understanding Correlation”, https://www.allaboutcircuits.com/technical-articles/understanding-correlation/, Jan. 4, 2017. |
Xu, et al.,“A 655 μW Silicon Photomultiplier-Based NIRS/EEG/EIT Monitoring ASIC for Wearable Functional Brain Imaging”, IEEE Transactions on Biomedical Circuits and Systems, IEEE, US, vol. 12, No. 6, Dec. 1, 2018. |
Zucconi, et al.,“The Autocorrelation Function”, https://www.alanzucconi.com/2016/06/06/autocorrelation-function/, Jun. 6, 2016. |
Alayed, et al.,“Characterization of a Time-Resolved Diffuse Optical Spectroscopy Prototype Using Low-Cost, Compact Single Photon Avalanche Detectors for Tissue Optics Applications,” Sensors 2018, 18, 3680; doi:10.3390/s18113680, Oct. 29, 2018. |
Blutman, et al.,“A 0.1 pJ Freeze Vernier Time-to-Digital Converter in 65nm CMOS,” 2014 International Symposium on Circuits and Systems (ISCAS), Melbourne, Australia, Jun. 1-5, 2014. |
De Heyn, et al.,“A fast start-up 3GHz-10GHz digitally controlled oscillator for UWB impulse radio in 90nm CMOS,” 2007 European Solid-State Circuits Conference—(ESSCIRC), Munich, Germany, pp. 484-487, Sep. 11-13, 2007. |
Dutton, et al.,“A Time-Correlated Single-Photon-Counting Sensor with 14GS/s Histogramming Time-to-Digital Converter,” 2015 IEEE International Solid-State Circuits Conference ISSCC 2015 / Session 11 / Sensors and Imagers for Life Sciences / 11.5, Feb. 22-26, 2015. |
Gnecchi, et al.,“A 1×16 SIPM Array for Automotive 3D Imaging LiDAR Systems.”, Proceedings of the 2017 International Image Sensor Workshop (IISW), Hiroshima, Japan (2017). |
Harmon, et al.,“Compound Semiconductor SPAD Arrays,” LightSpin Technologies, http://www.lightspintech.com/publications.html (2013). |
Mandai, et al.,“A 4 X 4 X 416 digital SIPM array with 192 TDCs for multiple high-resolution timestamp acquisition,” 2013 JINST 8 PO5024, May 31, 2013. |
Mora, et al.,“Fast-Gated Single-Photon Avalanche Diode for Wide Dynamic Range Near Infrared Spectroscopy,” IEEE Joumal of Selected Topics in Quantum Electronics, vol. 16, No. 4, pp. 1023-1030, Jul./Aug. 2010. |
Parmesan, et al.,“A 256×256 SPAD array with in-pixel Time to Amplitude Conversion for Fluorescence Lifetime Imaging Microscopy,”, Memory 900.M4, 2015. |
Pifferi, et al.,“Performance assessment of photon migration instruments: the MEDPHOT protocol,” Applied Optics, 44(11), 2104-2114 (2005). |
Prahl, et al.,“Optical Absorption of Hemoglobin,” http://omlc.ogi.edu/spectra/hemoglobin/index.html (1999). |
Richardson, et al.,“A 32×32 50ps resolution 10 bit time to digital converter array in 130nm CMOS for time correlated imaging,” CICC 2009 Proceedings of the IEEE 2009 Custom Integrated Circuits Conference. IEEE Society, San Jose, U.S.A., pp. 77-80, CICC 2009, San Jose, U.S.A., Sep. 13, 2009. https://doi.org/doi:10.1109/CICC.2009.5280890. |
Torricelli, et al.,“Time domain functional NIRS imaging for human brain mapping,” NeuroImage 85, 28-50 (2014). |
Zhang, et al.,“A CMOS SPAD Imager with Collision Detection and 128 Dynamically Reallocating TDCs for Single-Photon Counting and 3D Time-of-Flight Imaging,” Sensors (Basel, Switzerland), 18(11), 4016. doi: 10.3390/s18114016 Nov. 17, 2018. |
Number | Date | Country | |
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20210290147 A1 | Sep 2021 | US |
Number | Date | Country | |
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63074721 | Sep 2020 | US | |
62992529 | Mar 2020 | US |