Techniques for acquiring and processing biosignal measurements - Patents.com

Abstract

A head-wearable sensor arrangement is provided for obtaining measurements of a user's biosignals. The disclosure also relates to a wireless portable device for providing stimuli and a computing system. The head-wearable sensor arrangement may transmit time-stamped medical data, including an indication of the measurements, to a wireless portable device that is time-synchronized with the arrangement. The wireless portable device may transmit the time-stamped medical data to a computing system. The computing system may process the time-stamped medical data to determine an indication of the user's health, well-being or performance. This processing may include decomposing the measurements and using residuals of an autoregressive model or a robust aggregation method on the decomposed measurements.

Description

[Technical Field]

[0001] Technical Field The present disclosure generally relates to transmitting and processing medical data representative of at least one measure of a user's biosignal. A wireless head-wearable sensor arrangement, a wireless handheld device, and a computing system are provided. Also provided are a method and a computer program product for obtaining an augmented measure. [Background technology]

[0002] background Biosignals of the body, such as electrical heartbeat signals or electroencephalogram signals, are important for determining or monitoring the health, well-being or performance of humans or animals.

[0003] In many cases, a biosignal measurement may have a low signal-to-noise ratio, which may be detrimental to further processing of the measurement. For example, it may be desirable to identify relatively short features (e.g., in the range of 5-20 ms) in a biosignal measurement that contains low-frequency noise (e.g., in the 10-50 Hz frequency band). In this case, a high-pass filter may be applied to the measurement to obtain an enhanced measurement with an improved signal-to-noise ratio. In some cases, such filtering may be insufficient. For example, the measurement may contain relatively short artifacts (e.g., in the range of 5-20 ms) that are not related to the feature of interest. In these cases, it may be desirable to determine an enhanced measurement in which the features can be more reliably identified, the artifacts have reduced amplitude, and / or the number of artifacts is reduced.

[0004] When other signals (e.g., user input signals, stimulation signals, etc.) are used in conjunction with a biosignal, it may be advantageous to know the temporal coordination between such other signals and the biosignal to identify characteristics and / or determine health, well-being, or performance. In some scenarios, the temporal coordination cannot be reliably predetermined. For example, it may be desirable to set or obtain the temporal coordination when using a first wireless device to acquire measurements of the biosignal and a second wireless device to acquire other signals. In some cases, once the temporal coordination is set, it may change due to relative clock drift between the first and second wireless devices.

[0005] In addition to the above, challenges arise when monitoring a user's biosignals in different environments. For example, monitoring EEG signals usually requires a clinical environment with specific test conditions. Such conditions can be cumbersome and uncomfortable for the user. On the other hand, performing such measurements in a non-clinical environment, such as the user's home, can result in other challenges, such as high signal noise, ambient artifacts, and the user's inability to carefully adhere to the operating protocol. One goal is to enhance the measurement of biosignals and enable better signal monitoring even in noisy environments such as the home. Summary of the Invention [Problem to be solved by the invention]

[0006] overview A need exists for an approach that solves one or more of the above-mentioned problems or other problems. [Means for solving the problem]

[0007] First AspectThere is provided a medical data processing method for obtaining a processed measure of a biological signal from an initial measure of the biological signal, the method being performed by a computer system and including obtaining medical data representing at least one initial measure of the biological signal in a first domain, decomposing the at least one initial measure into a joint frequency domain to obtain transformed data representing the at least one initial measure in both the first domain and the frequency domain, fitting at least one autoregressive model to the transformed data, determining at least one deviation between the at least one fitted autoregressive model and the transformed data, and obtaining a processed measure of the biological signal based on the at least one deviation.

[0008] Second Aspect There is provided a computer system comprising at least one memory and at least one processor, the at least one memory storing instructions that, when executed on the at least one processor, cause the at least one processor to perform the method according to the first aspect.

[0009] Third Aspect According to the present invention, there is provided a computer program product comprising program code portions for performing the method according to the first aspect when executed on at least one processor, the computer program product being stored on one or more computer-readable recording media.

[0010] Fourth AspectAccording to the present invention, there is provided a medical data processing method for obtaining a processed measure of a biological signal from an initial measure of the biological signal, the method being performed by a computer system and including: obtaining medical data representing at least one initial measure of the biological signal in a first domain; decomposing the at least one initial measure into a joint frequency domain to determine a separate decomposed sequence in the first domain for each of the at least one initial measure for each of a plurality of frequencies or frequency bands; determining at least one estimated point by applying a robust aggregation method to corresponding points in one or more of the decomposed sequences for the same frequency or frequency band; and recombining the at least one estimated point into the first domain to obtain a processed measure of the biological signal.

[0011] Fifth Aspect According to the present invention, there is provided a computer system comprising at least one memory and at least one processor, wherein the at least one memory stores instructions that, when executed on the at least one processor, cause the at least one processor to perform the method according to the fourth aspect. The computer system may be the computer system of the second aspect.

[0012] Sixth Aspect According to the present invention, there is provided a computer program product comprising program code portions for, when executed on at least one processor, performing the method according to the fourth aspect, which computer program product may be stored on one or more computer-readable recording media.

[0013] Seventh aspectAccording to the present invention, there is provided a wireless head-wearable sensor configuration for transmitting medical data to a wireless portable device, the wireless head-wearable sensor configuration comprising: at least one sensor configured to generate at least one measurement of a biosignal of a user wearing the wireless head-wearable sensor configuration; a first wireless interface; a first clock; and a first processor. The first processor is configured to perform a time synchronization procedure to synchronize the first clock with a second clock of a wireless portable device or to direct synchronization of the first clock with the second clock of the wireless portable device. After performing the time synchronization procedure, the first processor is configured to acquire the at least one measurement of the biosignal of the user wearing the wireless head-wearable sensor configuration from the at least one sensor, assign at least one timestamp to the acquired at least one measurement using the first clock, and transmit medical data to the wireless portable device via the first wireless interface, the medical data including a representation of the at least one measurement and the at least one timestamp assigned to the at least one measurement.

[0014] Eighth aspectAccording to the present invention, there is provided a wireless portable device for receiving medical data from a wireless head-wearable sensor arrangement. The wireless portable device comprises a second wireless interface, a second clock, and a second processor. The second processor is configured to perform a time synchronization procedure to synchronize the second clock with a first clock of the wireless head-wearable sensor arrangement or to direct synchronization of the second clock with the first clock of the wireless head-wearable sensor arrangement. After performing the time synchronization procedure, the second processor is configured to receive medical data from the wireless head-wearable sensor arrangement via the second wireless interface, the medical data including a representation of at least one measurement of a biosignal of a user wearing the wireless head-wearable sensor arrangement and at least one timestamp assigned to the at least one measurement using the first clock, and to transmit the medical data to a computer system.

[0015] Ninth aspect According to the present invention, there is provided a computer system for receiving medical data from a wireless portable device. The computer system comprises one or more processors configured to receive, from a wireless portable device using a first clock of the wireless head wearable sensor arrangement, medical data including a representation of at least one measurement of a biosignal of a user wearing the wireless head wearable sensor arrangement and at least one timestamp assigned to the at least one measurement. The one or more processors are configured to determine an indicator of health, well-being, or performance of the user of the wireless head wearable sensor arrangement based on the representation of the at least one measurement and the at least one timestamp assigned to the at least one measurement. The one or more processors may be configured to implement a method according to at least one of the first and fourth aspects.

[0016] Tenth AspectThere is provided a medical data processing system according to the seventh aspect, the medical data processing system including at least two of a wireless head-wearable sensor arrangement, a wireless portable device, and a computer system, wherein the wireless head-wearable sensor arrangement is the arrangement according to the seventh aspect, the wireless portable device is the device according to the eighth aspect, and / or the computer system is the system according to the ninth aspect.

[0017] According to the present disclosure, the at least one (e.g., initial) measurement may be one of an electrical, magnetic, optical, or acoustic (e.g., ultrasound) measurement of the user's biosignal. The at least one (e.g., initial) measurement may include a first domain (e.g., time domain) and / or frequency domain representation of the biosignal. The biosignal may be a signal generated by the user's body. The biosignal may be a signal representing the user's cognitive state. The biosignal may be a neurofunctional signal. The cognitive state may include one or more of the user's emotion, a response to a stimulus provided to the user, the user's memory performance, and the user's cognitive performance. The biosignal may be a bioelectric signal, e.g., an electroencephalogram (EEG) signal. The biosignal may be an acoustic signal, e.g., an acoustic heartbeat signal. The biosignal may be a movement signal of the user's body (e.g., an electrical muscle movement signal, or a physical movement signal detectable, for example, by an accelerometer). The term medical data is not limited to data used in a clinical sense. The user may be a human (e.g., healthy or unhealthy) or an animal. The at least one measurement may be generated and / or obtained when the user is in a non-clinical environment, for example at home. [Brief explanation of the drawings]

[0018] BRIEF DESCRIPTION OF THE DRAWINGS Further details, advantages and aspects of the present disclosure will become apparent from the following embodiments considered in conjunction with the drawings.

[0019] [Figure 1]FIG. 1 illustrates an embodiment of a wireless head-wearable sensor configuration according to the present disclosure. [Figure 2] FIG. 2 illustrates an embodiment of a wireless mobile device according to the present disclosure. [Figure 3] FIG. 3 illustrates an embodiment of a computer system according to the present disclosure. [Figure 4] FIG. 4 illustrates an embodiment of a medical data processing system according to the present disclosure. [Figure 5] FIG. 5 illustrates a first method embodiment according to the present disclosure. [Figure 6] FIG. 6 illustrates a first method embodiment according to the present disclosure. [Figure 7] FIG. 7 illustrates four exemplary time synchronization procedures according to this disclosure. [Figure 8] FIG. 8 shows multiple segments of measurands of an EEG signal. [Figure 9] FIG. 9 shows an enlarged view of one of the segments of FIG. [Figure 10] FIG. 10 shows multiple decomposition sequences for the segment of FIG. [Figure 11] FIG. 11 shows the autoregressive models fitted to each of the decomposition sequences in FIG. [Figure 12] FIG. 12 shows the residuals of the fitted autoregressive model of FIG. [Figure 13] FIG. 13 shows the segment of FIG. 9 together with the residual of FIG. 12 after recomposition. [Figure 14] Figure 14 shows the EEG signal and the resynthesized residual, each averaged over the segments shown in Figure 8. Also shown is the resynthesis result of M-estimation applied to the decomposed residual. DETAILED DESCRIPTION OF THE INVENTION

[0020] Detailed Description In the following description, exemplary embodiments of wireless head-wearable sensor configurations are described with reference to the drawings, in which the same reference numerals are used to denote the same or similar structural features.

[0021] Wireless head wearable sensor configuration Figure 1 is according to the present disclosure Wireless head-wearable sensor configuration 100 1 illustrates a first embodiment of a wireless head-wearable sensor configuration 100 configured for transmitting medical data to a wireless mobile device. The wireless head-wearable sensor configuration 100 includes at least one sensor 102 configured to generate (e.g., record) at least one measurement of a biosignal of a user wearing the wireless head-wearable sensor configuration 100, a first wireless interface 104, a first clock 106, and a first processor 108. The wireless head-wearable sensor configuration 100 may further include a memory 110 containing instructions that, when executed by the first processor 108, configure the first processor 108 as described herein. The wireless head-wearable sensor configuration 100 may be, for example, a headset, a headband, or a helmet.

[0022] The first processor 108 is configured to perform a time synchronization procedure to synchronize the first clock 106 with a second clock of the wireless portable device (e.g., based on time information received from the wireless portable device via the first wireless interface 104) or to instruct (e.g., trigger, initiate, or enable) the second clock of the wireless portable device to synchronize with the first clock 106 (e.g., by sending time information to the wireless portable device via the first wireless interface 104). After performing the time synchronization procedure, the first processor 108 is configured to acquire at least one measurement of a biosignal of a user wearing the wireless head-wearable sensor arrangement from the at least one sensor 102, assign at least one timestamp to the acquired at least one measurement (e.g., using the first clock 106), and transmit medical data to the wireless portable device via the first wireless interface 104. The medical data includes a representation of the at least one measurement and the at least one timestamp assigned to the at least one measurement.

[0023] The first processor 108 may be configured to store the medical data in memory 110 or, for example (but not limited to) in cases where the medical data cannot be transmitted to a wireless mobile device via the first wireless interface 103, in physically removable memory (e.g., a storage card, USB stick, etc.).

[0024] At least one sensor 102 may be or include an electrode (e.g., a dry electrode) and may be configured to generate a measure of a bioelectric signal. The biosignal may be an acoustic signal, e.g., an acoustic cardiac signal. At least one sensor may be or include a microphone and may be configured to generate a measure of the acoustic signal.

[0025] The first wireless interface 104 may be a wireless local area network (WLAN) interface, a WiFi interface (e.g., compliant with IEEE Standard 802.11), a Bluetooth interface, or another radio interface (e.g., a 4G interface or a 5G interface). The first wireless interface 104 may include at least one of a WLAN interface, a WiFi interface, and a Bluetooth interface. The first processor 108 may include multiple processing units. For example, the first processor 108 may be implemented as a multi-core processor or as a distributed processor. The configuration 100 may include at least one of a real-time clock (RTC), a chip, and an oscillator circuit configured as the first clock 106. The first clock 106 may be configured to provide the first processor 108 with a current time. The first processor 108 may be configured to generate a timestamp of the current time using the time provided by the first clock 106. The first clock 106 and the first processor 108 may be part of the same integrated circuit or computer chip.

[0026] The first processor 108 or the at least one sensor 102 may be configured to determine a representation of the at least one measurand based on the at least one measurand. The representation of the at least one measurand may correspond to, consist of, or include the at least one measurand. The representation of the at least one measurand may include or consist of a digitized or numerical conversion of the at least one measurand or a filtered (e.g., frequency, amplitude, and / or noise) version of the at least one measurand.

[0027] Time Synchronization Procedure The first processor 108 may be configured to perform a time synchronization procedure such that the first clock 106 operates in synchronization with the second clock (e.g., at least at the start of generation or acquisition of at least one measurement). The first processor 108 may be configured to perform a time synchronization procedure such that the first clock 106 and the second clock are synchronized with each other (e.g., at least at the start of generation or acquisition of at least one measurement). Synchronizing the first clock 106 with the second clock may include, for example, adjusting the first clock 106 to the second clock, as described in A) or C) below. Synchronizing the first clock to the second clock may include adjusting the first clock 106 so that the difference between the time provided by the first clock 106 and the time provided by the second clock at the same point in time is compensated for, eliminated, minimized (e.g., below a predetermined tolerance level, such as 1 ms, 5 ms, or 10 ms), or substantially zero (e.g., below a predetermined tolerance level, such as 1 ms, 2 ms, or 3 ms).

[0028] As used herein, the term "operating synchronously" means that the time offset or difference between the time provided by the first clock 106 and the time provided by the second clock at the same point in time is below a predetermined tolerance level, such as 1 ms, 5 ms, or 10 ms, or is substantially zero (e.g., below a predetermined tolerance level, such as 0.1 ms, 0.5 ms, or 1 ms). Instructing the second clock to synchronize with the first clock 106 may include instructing (e.g., a second processor of) the wireless mobile device to adjust the second clock to the first clock 106, for example, as described in B) or D) below. Commanding the synchronization of the second clock with the first clock 106 may include commanding (e.g., a second processor of) the wireless mobile device to adjust the second clock so that the difference between the time provided by the second clock and the time provided by the first clock 106 at the same point in time is compensated for, eliminated, minimized (e.g., below a predetermined tolerance level such as 1 ms, 5 ms, or 10 ms), or substantially zero (e.g., below a predetermined tolerance level such as 1 ms, 2 ms, or 3 ms).

[0029] timestamp The at least one timestamp may be generated or have been generated using the first clock 106, for example, based on a time provided by the first clock 106. The at least one timestamp assigned to the at least one acquired measurand may represent a start time of generation of the at least one measurand by the at least one sensor 102 and / or a start time of acquisition of the at least one measurand by the first processor 108. Alternatively, or in addition, the at least one timestamp assigned to the at least one acquired measurand may represent an end time of generation of the at least one measurand by the at least one sensor 102 and / or an end time of acquisition of the at least one measurand by the first processor 108. The at least one timestamp may be generated by the first processor 108 at regular intervals using the first clock 106. At least one timestamp may be assigned to at least one measurand by timestamping at least one measurand with at least one timestamp, by including at least one timestamp in at least one measurand, and / or by determining a temporal correlation between at least one measurand and at least one timestamp.

[0030] Packet Number The first processor 108 may divide the medical data into multiple data packets and assign a packet number to each data packet. The packet number may indicate the packet's relative position within the medical data or the at least one measurement. Each data packet may contain a portion of the at least one measurement, and the packet number may indicate which portion of the at least one measurement is included in the packet. The data packets may be transmitted separately to the wireless mobile device. The data packets may later be re-ordered based on the packet number (e.g., by a second processor of the wireless mobile device) after being received by the wireless mobile device.

[0031] Time information The time information transmitted by the first processor 108 to the wireless mobile device may include time information of the first clock 106, e.g., a timestamp generated using the first clock 106. The time information received by the first processor 108 from the wireless mobile device may include time information of a second clock, e.g., a timestamp generated using the second clock. The time information received from or transmitted by the first processor 108 to the wireless mobile device may include at least one of a time synchronization request message, a time information request message, a time information response message, a configuration message, or information contained therein, e.g., as described below with reference to examples A) to D).

[0032] Opening message The first processor 108 may be configured to receive an initiation message from the wireless portable device (e.g., via the first wireless interface 104) and to command the at least one sensor to generate at least one measurement in response to receiving the initiation message. The first processor 108 may be configured to receive an initiation message from the wireless portable device (e.g., via the first wireless interface 104) and to start acquiring the at least one measurement in response to receiving the initiation message or based on a time specified in the initiation message. The first processor 108 may be configured to start acquiring the at least one measurement in response to sending the initiation message to the wireless portable device or in response to receiving the initiation message from the wireless portable device. The initiation message may correspond to a configuration message described herein.

[0033] Repeating the time synchronization procedure The first processor 108 may be configured to repeat the time synchronization procedure at predetermined times, periodically, and / or after obtaining at least one measurement. The first processor 108 may be configured to send to the wireless device an indication of an adjustment amount of the first clock 106. The adjustment amount may be an amount of time of the first clock 106 adjusted by the first processor 108 during a (e.g., initial or repeated) time synchronization procedure.

[0034] Examples of time synchronization procedures A), B), C) and D) We now describe four examples A), B), C), and D) of how the time synchronization procedure may be performed by the first processor 108. The first processor 108 may be configured to perform time synchronization according to one of examples A) to D), and when repeating the time synchronization, perform time synchronization according to the same or another of examples A) to D). Note that the configuration 100 according to example A) described below may be configured to perform the time synchronization procedure with a device according to example a) described below with reference to FIG. 2. The configuration 100 according to example B) described below may be configured to perform the time synchronization procedure with a device according to example b) described below with reference to FIG. 2. The same applies to examples C) and c) and examples D) and d) described herein.

[0035] of the first aspect Example A) and Example B) According to the present invention, the first processor 108 may be configured to perform a time synchronization procedure by sending a time information request message to the wireless mobile device via the first wireless interface 104 and receiving a time information response message from the wireless mobile device via the first wireless interface 104. The time information request message includes a first timestamp (e.g., generated using the first clock 106) of the transmission time of the time information request message, and the time information response message includes synchronization information.

[0036] Example A)According to the present invention, the first processor 108 may be configured to synchronize the first clock 106 by adjusting the first clock 106 based at least on the synchronization information. After adjusting the first clock 106, the first processor 108 may be configured to transmit a configuration message (e.g., an initiation message) to the wireless mobile device via the first wireless interface 104. The configuration message includes at least one of a second timestamp (e.g., generated using the first clock 106) of a transmission time of the configuration message and an indication of the adjustment amount of the first clock 106.

[0037] Example B) According to the present invention, the first processor 108 may be configured to determine an adjustment amount command for the second clock based on the synchronization information and transmit a configuration message to the wireless mobile device (e.g., via the first wireless interface 104). The configuration message includes the adjustment amount command for the second clock and, optionally, a second timestamp of the transmission time of the configuration message. The adjustment amount command for the second clock may instruct the wireless mobile device to adjust the second clock by an amount of time defined by the adjustment amount command.

[0038] of the first aspect Example C) and Example D) According to the present invention, the first processor 108 may be configured to perform a time synchronization procedure by receiving a time information request message from the wireless mobile device via the first wireless interface 104, determining synchronization information based on at least information included in the time information request message, and transmitting a time information response message to the wireless mobile device via the first wireless interface 104. The time information request message includes a first timestamp (e.g., generated using a second clock) of a transmission time of the time information request message, and the time information response message includes the synchronization information.

[0039] Example C) According to the method, the first processor 108 may be configured to receive a configuration message (e.g., an initiation message) from the wireless mobile device via the first wireless interface 104 after sending the time information response message, and adjust the first clock 106 based on information included in the configuration message. The information included in the configuration message may include at least one of a second timestamp (e.g., generated using the second clock) of the transmission time of the configuration message and an adjustment amount command for the first clock 106. The adjustment amount command for the first clock 106 may be based on the synchronization information. The adjustment amount command for the first clock 106 may instruct the first processor 108 to adjust the first clock 106 by an amount of time specified by the adjustment amount command.

[0040] Example D) According to the method, the first processor 108 is configured to, after transmitting the time information response message, receive a configuration message from the wireless mobile device via the first wireless interface 104. The configuration message includes an indication of the adjustment amount of the second clock and, optionally, a second timestamp (e.g., generated using the second clock) of the transmission time of the configuration message.

[0041] Synchronization Information Example A), B), C) or D)In any one of the above, the synchronization information may depend on at least a first timestamp. The synchronization information may include an indication of a first time difference between the transmission time of the time information request message and the reception time of the time information request message indicated by the first timestamp. The synchronization information may depend on at least the first timestamp by including an indication of the first time difference. The synchronization information may include a third timestamp of the transmission time of the time information response message. The indication of the first time difference may be composed of the first timestamp and a third timestamp, or may be an indication of the time difference between the time indicated by the first timestamp and the time indicated by the third timestamp.

[0042] Synchronization Deviation Example A) or B) According to the method, the first processor 108 may be configured to determine a synchronization deviation between the first clock 106 and the second clock based on the first time difference and a second time difference between the transmission time of the time information response message and the reception time of the time information response message indicated by the third timestamp. The first processor 108 may be configured to determine a round-trip latency based on the first time difference and the second time difference, and to determine a synchronization deviation further based on the round-trip latency. The synchronization deviation may be a (e.g., instantaneous) difference between the time provided by the first clock 106 and the time provided by the second clock (e.g., at a particular point in time or during a predetermined time interval). The round-trip latency may be indicative of a propagation time of a message from the configuration to (e.g., back from) the wireless device.

[0043] Clock adjustment based on synchronization deviation Example A)According to the method, the first processor 108 may be configured to synchronize the first clock 106 by adjusting the first clock 106 so that the determined synchronization deviation is eliminated, minimized (e.g., below a predetermined tolerance level such as 1 ms, 5 ms, or 10 ms), or compensated for. The first processor 108 may be configured to perform a cycle of sending a time information request message and receiving a time information response message multiple times, determine a synchronization deviation for each pair of the time information request message and the time information response message, and adjust the first clock 106 so that the smallest of the determined synchronization deviations is eliminated, minimized, or compensated for, or so that the average of the determined synchronization deviations is eliminated, minimized, or compensated for.

[0044] Example B) According to the method, the first processor 108 may be configured to determine an adjustment command for the second clock that instructs the wireless portable device to adjust the second clock so that the determined synchronization deviation is eliminated, minimized (e.g., below a predetermined tolerance level such as 1 ms, 5 ms, or 10 ms) or compensated. The first processor 108 may be configured to perform a cycle of transmitting time information request messages and receiving time information response messages multiple times, determine a synchronization deviation for each pair of the time information request messages and the time information response messages, and determine an adjustment command for the second clock that instructs the wireless portable device to adjust the second clock so that the smallest of the determined synchronization deviations is eliminated, minimized, or compensated, or the average of the determined synchronization deviations is eliminated, minimized, or compensated.

[0045] First Modification of Synchronization Start (For example, one of examples A) to D) First ModificationIn the method, the first processor 108 may be configured to receive a time synchronization request message from the wireless mobile device via the first wireless interface 104 and begin performing a time synchronization procedure in response to (e.g., in reaction to or triggered by) receiving the time synchronization request message. The time synchronization request message may include a fourth timestamp (e.g., generated using the second clock) of a transmission time of the time synchronization request message. Prior to performing the time synchronization procedure, the first processor 108 may be configured to pre-adjust the first clock 106 based on the transmission time of the time synchronization request message indicated by the fourth timestamp. The first processor 108 may be configured to pre-adjust the first clock 106 so that its time corresponds to the time indicated by the fourth timestamp. The first processor 108 may be configured to pre-adjust the first clock 106 if the time indicated by the fourth timestamp deviates from the reception time of the time synchronization request message (e.g., determined using the first clock 106) by more than a predetermined amount (e.g., 1 second, 5 seconds, or 10 seconds).

[0046] Second Variation of Synchronization Start (For example, one of examples A) to D) Second VariantIn the embodiment, the first processor 108 may be configured to send a time synchronization request message to the wireless mobile device via the first wireless interface 104 to trigger (e.g., instruct or initiate) the wireless mobile device to begin performing a time synchronization procedure. The time synchronization request message may include a fourth timestamp (e.g., generated using the first clock 106) of a transmission time of the time synchronization request message and may instruct the wireless mobile device to pre-adjust its second clock based on the transmission time of the time synchronization request message indicated by the fourth timestamp before performing the time synchronization procedure. The time synchronization request message may instruct the wireless mobile device to pre-adjust its first clock 106 so that its time corresponds to the time indicated by the fourth timestamp. The time synchronization request message may instruct the wireless mobile device to pre-adjust its second clock if the time indicated by the fourth timestamp deviates from the reception time of the time synchronization request message (e.g., determined using the second clock) by more than a predetermined amount (e.g., 1 second, 5 seconds, or 10 seconds).

[0047] Wireless Mobile Devices Figure 2 is according to the present disclosure Wireless Mobile Device 200 2 illustrates a first embodiment of a wireless mobile device 200. The wireless mobile device 200 includes a second wireless interface 204, a second clock 206, and a second processor 208. The wireless mobile device 200 may be the wireless mobile device referred to above in the description of FIG. 1. The wireless mobile device 200 may further include a memory 209 containing instructions that, when executed by the second processor 208, configure the second processor 208 as described herein. The wireless mobile device 200 may be, for example, a tablet, a laptop, or a smartphone.

[0048] The second processor 208 is configured to perform a time synchronization procedure to synchronize the second clock 206 with a first clock (e.g., first clock 106) of the wireless head wearable sensor configuration (e.g., configuration 100) or to instruct (e.g., trigger, initiate, or enable) the first clock (e.g., first clock 106) of the wireless head wearable sensor configuration (e.g., configuration 100) to synchronize with the second clock (e.g., by sending time information to the wireless head wearable sensor configuration via the second wireless interface). After performing the time synchronization procedure, the second processor 208 is configured to receive medical data from the wireless head wearable sensor configuration via the second wireless interface 204 and transmit the medical data to the computing system. The medical data includes a representation of at least one measurement of a biosignal of a user wearing the wireless head wearable sensor configuration and at least one timestamp assigned to the at least one measurement. The second processor 208 may be configured to perform a time synchronization procedure to synchronize the second clock 206 with the first clock based on time information received from the wireless head wearable sensor configuration via the second wireless interface.

[0049] The second wireless interface 204 may be a wireless local area network (WLAN) interface, a WiFi interface (e.g., compliant with IEEE Standard 802.11), a Bluetooth interface, or another radio interface (e.g., a 4G interface or a 5G interface). The second wireless interface 204 may include at least one of a WLAN interface, a WiFi interface, and a Bluetooth interface. The second processor 208 may include multiple processing units. For example, the second processor 208 may be implemented as a multi-core processor or a distributed processor. The device 200 may include at least one of a real-time clock (RTC), a chip, and an oscillator circuit configured as the second clock 206. The second clock 206 may be configured to provide the second processor 208 with a current time. The second processor 208 may be configured to generate a timestamp of the current time using the time provided by the second clock 206. The second clock 206 and the second processor 208 may be part of the same integrated circuit or computer chip.

[0050] As discussed with reference to Figure 1, the representation of the at least one measurand may correspond to, consist of, or include the at least one measurand, or may include or consist of a digitized or numerical transform of the at least one measurand, or a filtered (e.g., frequency, amplitude, and / or noise) version of the at least one measurand.

[0051] The second processor 208 may be configured to perform a time synchronization procedure such that the second clock 206 operates in synchronization with the first clock (e.g., at least at the time when at least one measurement is generated). The second processor 208 may be configured to perform a time synchronization procedure such that the second clock 206 and the first clock are synchronized with each other (e.g., at least at the start of generation of the at least one measurement). Synchronizing the second clock 206 with the first clock may include, for example, adjusting the second clock 206 to the first clock, as described in B) or D) below. Synchronizing the second clock 206 with the first clock may include adjusting the second clock 206 so that a difference between the time provided by the second clock 206 and the time provided by the first clock at the same point in time is compensated for, eliminated, minimized (e.g., below a predetermined tolerance level, such as 1 ms, 5 ms, or 10 ms), or substantially zero (e.g., below a predetermined tolerance level, such as 1 ms, 2 ms, or 3 ms). As mentioned above, the term "operating synchronously" as used herein means that the time offset or difference between the time provided by the first clock and the time provided by the second clock 206 at the same point in time is below a predetermined tolerance level, such as 1 ms, 5 ms, or 10 ms, or is substantially zero (e.g., below a predetermined tolerance level, such as 0.1 ms, 0.5 ms, or 1 ms). Instructing the first clock to synchronize with the second clock 206 may include instructing (e.g., a first processor of) the wireless head wearable sensor configuration to adjust the first clock to the second clock 206, for example, as described in A) or C) below.Commanding the synchronization of the first clock with the second clock 206 may include commanding (e.g., a first processor of) the wireless head wearable sensor configuration to adjust the first clock so that the difference between the time provided by the first clock and the time provided by the second clock 206 at the same point in time is compensated for, eliminated, minimized (e.g., below a predetermined tolerance level such as 1 ms, 5 ms, or 10 ms), or substantially zero (e.g., below a predetermined tolerance level such as 1 ms, 2 ms, or 3 ms).

[0052] timestamp The at least one timestamp may be generated or may have been generated using the first clock, for example, based on a time provided by the first clock. The at least one timestamp assigned to the acquired at least one measurement may represent a start time of generation of the at least one measurement by at least one sensor (e.g., at least one sensor 102) included in the wireless head wearable sensor configuration and / or a start time of acquisition of the at least one measurement from the at least one sensor by a first processor (e.g., first processor 108) of the wireless head wearable sensor configuration. Alternatively, or in addition, the at least one timestamp assigned to the acquired at least one measurement may represent an end time of generation of the at least one measurement and / or an end time of acquisition of the at least one measurement. The at least one timestamp may be generated at regular intervals using the first clock. At least one timestamp may be assigned to at least one measurand by timestamping at least one measurand with at least one timestamp, by including at least one timestamp in at least one measurand, and / or by determining a temporal correlation between at least one measurand and at least one timestamp.

[0053] Packet Number The received medical data may be divided into multiple data packets (e.g., by a wireless head-wearable sensor configuration), and a packet number may be assigned to each data packet. The packet number may indicate the packet's relative position within the medical data or at least one measurement. Each data packet may include a portion of at least one measurement, and the packet number may indicate which portion of the at least one measurement is included in that packet. The data packets may be received separately by the wireless mobile device 200. After being received by the wireless mobile device 200, the data packets may be reordered based on the packet number (e.g., by the second processor 208 of the wireless mobile device) to obtain the medical data in the correct form. That is, the second processor 208 may reorder the received data packets so that the order follows the packet number. This may ensure that the portions of the at least one measurement included in the packets are combined in the correct order.

[0054] The second processor 208 may transmit the medical data to the computer system in the form of one or more packets. The packets have packet numbers (e.g., unique or ascending) and each packet contains a portion of at least one measurement. The data packets received by the wireless device 208 may be identical to the data packets transmitted to the computer system. Alternatively, the second processor 208 may be configured to divide the medical data into different packets.

[0055] Time information The time information transmitted by the second processor 208 to the wireless head wearable sensor configuration may include time information of the second clock 206, e.g., a timestamp generated using the second clock 206. The time information received by the second processor 208 from the wireless head wearable sensor configuration may include time information of the first clock, e.g., a timestamp generated using the first clock. The time information received from or transmitted by the second processor 208 to the wireless head wearable sensor configuration may include at least one of a time synchronization request message, a time information request message, a time information response message, a configuration message, or information contained therein, e.g., as described below with reference to examples a) through d).

[0056] Opening message The second processor 208 may be configured to send an initiation message to the wireless head-wearable sensor configuration (e.g., via the second wireless interface 204) instructing the wireless head-wearable sensor configuration to begin generating or acquiring at least one measurement. The initiation message may correspond to a configuration message described herein.

[0057] Examples of time synchronization procedures a), b), c) and d) We now describe four examples a), b), c), and d) of how the time synchronization procedure may be performed by the second processor 208. The second processor 208 may be configured to perform time synchronization according to one of examples a) to d), and, when repeating the time synchronization, perform time synchronization according to the same or another of examples a) to d). Note that the device 200 according to example a) described below may be configured to perform the time synchronization procedure using the configuration according to example A) described above with reference to FIG. 1. The device 200 according to example B) described below may be configured to perform the time synchronization procedure using the configuration according to example B) described above with reference to FIG. 1. The same applies to examples c) and C) and examples d) and D) described herein.

[0058] Example a) and Example b) In the wireless head wearable sensor configuration, the second processor 208 is configured to receive a time information request message from the wireless head wearable sensor configuration via the second wireless interface, determine synchronization information based at least on information included in the time information request message, and transmit a time information response message to the wireless head wearable sensor configuration via the second wireless interface. The time information request message includes a first timestamp (e.g., generated using the first clock) of a transmission time of the time information request message, and the time information response message includes the synchronization information.

[0059] example a) In the example, the second processor 208 may be configured to, after transmitting the time information response message, receive a configuration message (e.g., an initiation message) from the wireless head-wearable sensor configuration via the second wireless interface 204. The configuration message includes an indication of the adjustment amount of the first clock and, optionally, a second timestamp (e.g., generated using the first clock) of the transmission time of the configuration message.

[0060] exampleb) In the method, the second processor 208 may be configured to receive a configuration message from the wireless head-wearable sensor configuration via the second wireless interface after transmitting the time information response message and adjust the second clock based on information included in the configuration message. The information included in the configuration message may include at least one of a second timestamp (e.g., generated using the first clock) of a transmission time of the configuration message and an adjustment amount command for the second clock. The adjustment amount command for the second clock may be based on the synchronization information. The adjustment amount command may instruct the second processor 208 to adjust the second clock 206 by an adjustment amount specified by the adjustment amount command.

[0061] Example of the second embodiment c) and examples d) In the example, the second processor 208 may be configured to send a time information request message to the wireless head wearable sensor configuration via the second wireless interface and receive a time information response message from the wireless head wearable sensor configuration via the second wireless interface, where the time information request message includes a first timestamp (e.g., generated using the second clock 206) of a transmission time of the time information request message, and the time information response message includes synchronization information.

[0062] example c) In the method, the second processor 208 may be configured to determine an adjustment amount command for the first clock based on the synchronization information and send a configuration message to the wireless head wearable sensor configuration. The configuration message includes the adjustment amount command for the first clock and, optionally, a second timestamp of the transmission time of the configuration message. The adjustment amount command for the first clock may instruct the wireless head wearable sensor configuration to adjust the first clock by an amount of time specified by the adjustment amount command.

[0063] example d) In the method, the second processor 208 may be configured to synchronize the second clock by adjusting the second clock based at least on the synchronization information. After adjusting the second clock, the second processor 208 may be configured to send a configuration message to the wireless head-wearable sensor configuration via the second wireless interface. The configuration message includes at least one of a second timestamp of a transmission time of the configuration message and an indication of an adjustment amount of the second clock.

[0064] example a), b), c) or d) In any one of the above, the synchronization information may depend on at least a first timestamp. The synchronization information may include an indication of a first time difference between the transmission time of the time information request message and the reception time of the time information request message indicated by the first timestamp. The synchronization information may depend on at least the first timestamp by including an indication of the first time difference. The synchronization information may include a third timestamp of the transmission time of the time information response message. The indication of the first time difference may be composed of the first timestamp and a third timestamp, or may be an indication of the time difference between the time indicated by the first timestamp and the time indicated by the third timestamp.

[0065] Synchronization Deviation Example c) or Example d)In the method, the second processor 208 may be configured to determine a synchronization deviation between the first clock and the second clock based on the first time difference and a second time difference between the transmission time of the time information response message and the reception time of the time information response message indicated by the third timestamp. The second processor 208 may be configured to determine a round-trip latency based on the first time difference and the second time difference, and to determine a synchronization deviation further based on the round-trip latency. The synchronization deviation may be a (e.g., instantaneous) difference between the time provided by the first clock and the time provided by the second clock (e.g., at a particular point in time or during a predetermined time interval). The round-trip latency may be indicative of a propagation time of a message from the configuration to (e.g., back from) the wireless head-wearable sensor configuration.

[0066] Clock adjustment based on synchronization deviation Example c) In the method, the second processor 208 may be configured to determine an adjustment command for the first clock that instructs the wireless head wearable sensor configuration to adjust the first clock so that the determined synchronization deviation is eliminated, minimized (e.g., below a predetermined tolerance level such as 1 ms, 5 ms, or 10 ms) or compensated. The second processor 208 may be configured to perform a cycle of sending time information request messages and receiving time information response messages multiple times, determine a synchronization deviation for each pair of the time information request messages and the time information response messages, and determine an adjustment command for the first clock that instructs the wireless head wearable sensor configuration to adjust the first clock so that the smallest of the determined synchronization deviations is eliminated, minimized, or compensated, or the average of the determined synchronization deviations is eliminated, minimized, or compensated.

[0067] Example d)In the method, the second processor 208 may be configured to synchronize the second clock by adjusting the second clock so that the determined synchronization deviation is eliminated, minimized (e.g., below a predetermined tolerance level, such as 1 ms, 5 ms, or 10 ms), or compensated for. The second processor 208 may be configured to perform a cycle of sending time information request messages and receiving time information response messages multiple times, determine a synchronization deviation for each pair of the time information request messages and the time information response messages, and adjust the second clock so that the smallest of the determined synchronization deviations is eliminated, minimized, or compensated for, or so that the average of the determined synchronization deviations is eliminated, minimized, or compensated for.

[0068] First variant of the initiation of the time synchronization procedure (For example, any one of examples a), b), c) and d)) First Modification In the wireless head-wearable sensor arrangement, the second processor 208 may be configured to receive a time synchronization request message via the second wireless interface from the wireless head-wearable sensor arrangement and begin performing a time synchronization procedure in response to (e.g., in reaction to or triggered by) receiving the time synchronization request message. The time synchronization request message may include a fourth timestamp (e.g., generated using the first clock) of a transmission time of the time synchronization request message. The second processor 208 may be configured to pre-adjust the second clock based on the transmission time of the time synchronization request message indicated by the fourth timestamp before performing the time synchronization procedure. The second processor 208 may be configured to pre-adjust the second clock if the time indicated by the fourth timestamp deviates from the reception time of the time synchronization request message (e.g., determined using the second clock 206) by more than a predetermined amount (e.g., 1 second, 5 seconds, or 10 seconds).

[0069] Second variant of the initiation of the time synchronization procedure (For example, any one of examples a), b), c) and d)) Second VariantIn the example, the second processor 208 may be configured to send a time synchronization request message to the wireless head wearable sensor configuration via the second wireless interface to trigger (e.g., instruct or initiate) the wireless head wearable sensor configuration to begin performing a time synchronization procedure. The time synchronization request message may include a fourth timestamp (e.g., generated using the second clock 206) of a transmission time of the time synchronization request message and instruct the head wearable sensor configuration to pre-adjust its first clock based on the transmission time of the time synchronization request message indicated by the fourth timestamp before performing the time synchronization procedure. The time synchronization request message may instruct the wireless head wearable sensor configuration to pre-adjust its first clock if the time indicated by the fourth timestamp deviates from the reception time of the time synchronization request message (e.g., determined using the first clock) by more than a predetermined amount (e.g., 1 second, 5 seconds, or 10 seconds).

[0070] Sending data to a computer system The second processor 208 may be configured to transmit a fifth timestamp (e.g., generated by the second clock 206) of the transmission time of the medical data to the computer system. The second processor 208 may be configured to transmit at least one of an indication of the adjustment amount of the first clock, an indication of the adjustment amount of the second clock 206, an adjustment amount command for the first clock, and an adjustment amount command for the second clock to the computer system. In other words, the second processor 208 may be configured to notify the computer system of the time discrepancy between the first clock and the second clock that has been compensated for in the time synchronization procedure.

[0071] Repeating the time synchronization procedure The second processor 208 may be configured to repeat the time synchronization procedure (e.g., at one or more predetermined points in time, periodically, after at least one measurement is generated or acquired, and / or after the second processor 208 receives medical data from the wireless head-wearable sensor configuration). The second processor 208 may be configured to send to the computing system at least one of an indication of the amount of time by which the first clock will be adjusted during a repeated (e.g., second or subsequent) time synchronization procedure, an adjustment amount command for the first clock used during the repeated time synchronization procedure, an indication of the amount of time by which the second clock 206 will be adjusted during the repeated time synchronization procedure, and an adjustment amount command for the second clock 206 used during the repeated time synchronization procedure. The second processor 208 may be configured to send to the computing system an indication of the amount of time by which the first clock will be adjusted during a repeated time synchronization procedure or an indication of the amount of time by which the second clock 206 will be adjusted during a repeated time synchronization procedure. In other words, the second processor 208 may be configured to inform the computing system (e.g., by sending information to the computing system) about the time discrepancy between the first clock and the second clock that has been compensated for in the repeated time synchronization procedure.

[0072] The second processor 208 may be configured to transmit to the computer system an indication of a temporal linkage between the adjustment amount or adjustment amount command and the at least one measured quantity, i.e., to transmit to the computer system an indication of a temporal linkage between the time when the adjustment amount is used to adjust the first or second clock and (e.g., a start or end of) the at least one measured quantity, or to transmit to the computer system an indication of a temporal linkage between the time when the adjustment amount command is used to adjust the first or second clock and (e.g., a start or end of) the at least one measured quantity.

[0073] stimulation The device 200 may further comprise a stimulus interface 210 (e.g., a display or speaker) configured to present at least one stimulus to a user of the wireless handheld device. The second processor 208 may optionally be configured to control the stimulus interface 210 to present at least one stimulus to the user at one or more stimulus time points for which a time synchronization procedure is not performed. In a second variation (e.g., any one of examples a), b), c), and d), the second processor 208 may be configured to send a time synchronization request message to the wireless head-wearable sensor arrangement at a time point different from the one or more stimulus time points.

[0074] The stimulation interface 210 may include or be at least one of a (e.g., touch) display, a speaker, an audio output interface connectable to a speaker, a tactile vibration interface, electrical stimulation electrodes, and an odor emission unit.

[0075] Time lag at the start of the measurement The second processor 208 may be configured to transmit a sixth timestamp (e.g., generated using the second clock 206) of the time at which generation of the at least one measurand is initiated (e.g., indicated) to the computer system. The at least one timestamp assigned to the at least one measurand may be indicative of the time provided by the first clock at which generation of the at least one measurand is initiated. The sixth timestamp may be indicative of the time provided by the second clock at which generation of the at least one measurand is initiated. That is, a deviation between the time indicated by the at least one timestamp and the sixth timestamp may represent a time offset between the first clock and the second clock at the time at which generation of the at least one measurand is initiated. The second processor 208 may be configured to transmit an indication of this time offset to the computer system.

[0076] Time lag during measurement The second processor 208 may be configured to transmit a ninth timestamp (e.g., generated using the second clock 206) to the computer system at a (e.g., predetermined) time point during which the generation of the at least one measurand is in progress. The at least one timestamp assigned to the at least one measurand may be indicative of a time provided by a first clock during which the generation of the at least one measurand is in progress. The ninth timestamp may be indicative of a time provided by a second clock during which the generation of the at least one measurand is in progress. That is, a deviation between the time indicated by the at least one timestamp and the ninth timestamp may represent a time offset between the first clock and the second clock at the time during which the generation of the at least one measurand is in progress. The second processor 208 may be configured to transmit an indication of this time offset to the computer system.

[0077] Time lag at the end of the measurement The at least one timestamp assigned to the at least one measurement may indicate a time, provided by the first clock, when generation of the at least one measurement was completed. The second processor 208 may be configured to transmit a seventh timestamp (e.g., generated using the second clock 206) to the computer system when the medical data was received by the device 200. The seventh timestamp may be corrected by the second processor 208 (e.g., based on round-trip latency) to obtain a theoretical time, provided by the second clock, when the medical data was transmitted to the device in the above configuration. The second processor 208 may be configured to transmit the seventh timestamp and / or an eighth timestamp indicating this theoretical time to the computer system. That is, a deviation between the time indicated by the at least one timestamp and the seventh or eighth timestamp may represent a time offset between the first clock and the second clock at the time when generation of the at least one measurement was completed. The second processor 208 may be configured to transmit an indication of this time offset to the computer system.

[0078] Stimulus and Initiation Message The second processor 208 may be configured to, in response to receiving the initiation message or at a time specified by the initiation message, send an initiation message to the wireless head-wearable sensor configuration instructing the wireless head-wearable sensor configuration to begin generating at least one measurement. The second processor 208 may be configured to determine the time specified by the initiation message and / or send the initiation message at a time when at least one measurement between at least one or more stimulation time points has been generated.

[0079] Alternatively, the second processor 208 may be configured to begin applying the at least one stimulus in response to receiving an initiation message from the wireless head-wearable sensor arrangement.

[0080] The initiation message may correspond to the configuration message described above.

[0081] The second processor 208 can be configured to transmit an indication of the one or more stimulation time points to the computer system. The indication of the one or more stimulation time points can include a temporal linkage between the one or more stimulation time points and the at least one measured quantity.

[0082] The at least one stimulus may be one or more of a visual stimulus, an auditory stimulus, a tactile stimulus, and an olfactory stimulus. The at least one stimulus may evoke a response in the biosignal. The at least one stimulus may trigger a physical reaction in the user that is observable or manifested in the biosignal. The at least one stimulus may influence the user such that the biosignal exhibits at least one characteristic (e.g., characteristic) associated with the at least one stimulus.

[0083] User Interface The device 200 may further include a user interface 212 configured to receive user input. The second processor 208 may be further configured to transmit user data representing the user input to the computing system. The user data may include a temporal linkage between one or more time points of the received user input and at least one measured quantity. The user interface 212 may include at least one of a touchscreen (e.g., also used as the stimulus interface 210), a computer mouse, a joystick, and a microphone.

[0084] The type of wireless device and configuration sent to the computer system The second processor 208 of the device of the second embodiment may be configured to send an indication of the type of device 200 or wireless head wearable sensor configuration (e.g., at least one of the device name, manufacturer name, model number, and version number) to the computing system. The computing system described herein with reference to Figure 2 may be the computing system described below with reference to Figure 3.

[0085] Computer System Figure 3 is according to the present disclosure Computer System 300 3 illustrates a first embodiment of a computer system 300. The computer system 300 includes one or more processors 302 and may include one or more memories 304. The one or more memories 304 may contain instructions that, when executed by the one or more processors 302, configure the processors as described herein. The computer system 300 may include an interface 306 for receiving and transmitting data.

[0086] The one or more processors 302 are configured to receive medical data from the wireless portable device, the medical data including a representation of at least one measurement of a biosignal of a user wearing the wireless head wearable sensor configuration and at least one timestamp assigned (e.g., assigned) to the at least one measurement. The at least one timestamp may be assigned to the at least one measurement by the wireless head wearable sensor configuration, for example, using a first clock of the wireless head wearable sensor configuration. The one or more processors may be configured to determine an indicator of the health, well-being, or performance of a user of the wireless head wearable sensor configuration based on the at least one measurement and the at least one timestamp assigned to the at least one measurement. The wireless head wearable sensor configuration may be configuration 100. The wireless portable device may be device 200. The medical data received by the one or more processors 302 may be medical data transmitted by device 200 as described with reference to FIG. 2.

[0087] The computer system 300 may be a cloud-based processing system. One or more processors 302 may be distributed across different racks or geographic locations. One or more processors 302 may be implemented as virtual resources (VR) of virtual machines (VMs). The computer system 300 may be configured to receive medical data from wireless mobile devices over a network such as the Internet.

[0088] The representation of the at least one measurand may correspond to, consist of, or include the at least one measurand, may include or consist of a digitized or numerical transformation of the at least one measurand, or a filtered (e.g., frequency, amplitude, and / or noise) version of the at least one measurand.

[0089] The at least one timestamp may have been assigned to the at least one measurement (e.g., by the wireless head wearable sensor arrangement) using a first clock (e.g., first clock 106) operating synchronously with a second clock (e.g., second clock 206) of the wireless handheld device (e.g., at least at the start of acquisition of the at least one measurement by at least one sensor (e.g., at least one sensor 102) included in the wireless head wearable sensor arrangement). As mentioned above, the term "operating synchronously" as used herein means that the time offset or difference between the time provided by the first clock and the time provided by the second clock at the same point in time is below a predetermined tolerance level, such as 1 ms, 5 ms, or 10 ms, or is substantially zero (e.g., below a predetermined tolerance level, such as 0.1 ms, 0.5 ms, or 1 ms).

[0090] Packet Number The received medical data may be divided into multiple data packets (e.g., by a wireless head-wearable sensor configuration or a wireless mobile device), and a packet number may be assigned to each data packet. The packet number may indicate the packet's relative position within the medical data or at least one measurement. Each data packet may include a portion of at least one measurement, and the packet number may indicate which portion of the at least one measurement is included in that packet. The data packets may be separately received by the computer system 300 from the wireless mobile device 200. After being received by the computer system 300, the data packets may be re-sorted by the one or more processors 302 based on the packet numbers to obtain the medical data in the correct form. That is, the one or more processors 302 may re-order the received data packets so that the order follows the packet numbers. This may ensure that the portions of the at least one measurement included in the packets are combined in the correct order.

[0091] Time lag at the start of the measurement The one or more processors 302 may be configured to receive from the wireless handheld device to the computing system a sixth timestamp (e.g., generated using a second clock) of a time at which generation of at least one measurement by at least one sensor of the wireless head-wearable sensor configuration is initiated (e.g., indicated as such). The at least one timestamp assigned to the at least one measurement may be indicative of a time provided by a first clock at which generation of the at least one measurement is initiated. The sixth timestamp may be indicative of a time provided by a second clock at which generation of the at least one measurement is initiated. That is, a deviation between the time indicated by the at least one timestamp and the sixth timestamp may represent a time offset between the first clock and the second clock at the time at which generation of the at least one measurement is initiated. The one or more processors 302 may be configured to receive an indication of this time offset from the wireless handheld device.

[0092] Time lag during measurement The one or more processors 302 may be configured to receive from the wireless handheld device a ninth timestamp (e.g., generated using the second clock 206) at a (e.g., predetermined) time point when the generation of the at least one measurement is in progress. The at least one timestamp assigned to the at least one measurement may be indicative of a time provided by the first clock when the generation of the at least one measurement is in progress. The ninth timestamp may be indicative of a (e.g., corresponding to) a time provided by the second clock when the generation of the at least one measurement is in progress. That is, a deviation between the time indicated by the at least one timestamp and the ninth timestamp may represent a time offset between the first clock and the second clock at the (e.g., predetermined) time point when the generation of the at least one measurement is in progress. The one or more processors 302 may be configured to receive an indication of this time offset from the wireless handheld device.

[0093] Time lag at the end of the measurement The at least one timestamp assigned to the at least one measurement may indicate a time, provided by the first clock, at which generation of the at least one measurement was completed. The one or more processors 302 may be configured to receive from the wireless portable device a seventh timestamp (e.g., generated using the second clock 206) at which the medical data was received by the wireless portable device. The seventh timestamp may be corrected by the wireless portable device (e.g., based on round-trip latency) to obtain a theoretical time, provided by the second clock, at which the medical data was transmitted by the wireless head-wearable sensor arrangement to the wireless portable device. The one or more processors 302 may be configured to receive from the wireless portable device the seventh timestamp and / or an eighth timestamp indicative of this theoretical time. That is, a deviation between the time indicated by the at least one timestamp and the seventh or eighth timestamp may represent a time offset between the first clock and the second clock at the time at which generation of the at least one measurement was completed. The one or more processors 302 may be configured to receive an indication of this time offset from the wireless portable device.

[0094] Determining indicators Based on the representation of the at least one measured quantity and the at least one timestamp assigned to the at least one measured quantity, an indicator of the user's health, well-being, or performance may be determined. The one or more processors 302 may be configured to use the at least one timestamp to identify a temporal characteristic of the representation of the at least one measured quantity (e.g., frequency of a characteristic pattern, shape of the representation in the time domain, etc.). The temporal characteristic may be a feature associated with one of a predefined set of indicators of the user's health, well-being, or performance. The one or more processors 302 may be configured to select one of the set of indicators based on the temporal characteristic.

[0095] The one or more processors may be configured to receive a fifth timestamp (e.g., generated by a first clock) from the wireless portable device of the time of transmission of the medical data, and further to determine an indicator of the user's health, well-being, or performance based on the fifth timestamp.

[0096] Use of the adjustment amount indication The one or more processors 302 may be configured to receive from a wireless portable device (e.g., the wireless portable device 200) an indication of an adjustment amount of either the first clock or the second clock to be used to synchronize the first clock or the second clock (e.g., before or after the at least one measurement is taken, e.g., by the wireless device and / or the wireless head-wearable sensor arrangement). The adjustment amount may have been determined or received by the wireless portable device 200 during an (e.g., initial or first) time synchronization procedure or a repeated (e.g., second or subsequent) time synchronization procedure described above with reference to Figures 1 and 2. Alternatively, or additionally, the one or more processors 302 may be configured to receive from the wireless portable device an adjustment amount instruction to be used to synchronize the first clock or the second clock (e.g., before or after the at least one measurement is taken, e.g., by the wireless device and / or the wireless head-wearable sensor arrangement). The adjustment amount command may have been determined or received by the wireless mobile device 200 during the (e.g., initial or first) time synchronization procedure or during a repeated (e.g., second or subsequent) time synchronization procedure described above with reference to Figures 1 and 2. The one or more processors 302 may be configured to determine an indicator of the user's health, well-being, or performance further based on the indication of the adjustment amount or the adjustment amount command.

[0097] Use of time linkage between adjustment quantity and measurement The one or more processors 302 may be configured to receive a temporal correlation between the adjustment amount and the at least one measured amount or between the adjustment amount command and the at least one measured amount from the wireless mobile device. The one or more processors 302 may be configured to determine an indicator of the user's health, well-being, or performance further based on the temporal correlation. The temporal correlation may be a temporal correlation between at least one timestamp and a point in time when the adjustment amount was used to synchronize the first clock or the second clock, or a temporal correlation between at least one timestamp and a point in time when the adjustment amount command was used to synchronize the first clock or the second clock.

[0098] Clock Drift The one or more processors 302 may be configured to determine a clock drift between the first clock and the second clock based on the adjustment amount and based on a temporal correlation between at least one timestamp and a point in time when the adjustment amount was used to synchronize the first clock or the second clock (e.g., in the repeated time synchronization procedure described above). The one or more processors 302 may be configured to determine a clock drift between the first clock and the second clock based on the received adjustment amount command and based on a temporal correlation between at least one timestamp and a point in time when the adjustment amount command was used to synchronize the first clock or the second clock (e.g., in the repeated time synchronization procedure described above).

[0099] For example, the at least one timestamp may indicate a time when the wireless head-wearable sensor configuration started generating at least one measurement and the first clock or the second clock was adjusted by an adjustment amount in the repeated time synchronization procedure described above after the at least one measurement was generated or while the at least one measurement was generated. In this example, the clock drift (e.g., a change over time in the difference between the times provided by the first clock and the second clock) may be determined as an adjustment amount per period of time. The period of time corresponds to the temporal alignment (e.g., relative time difference) between the time indicated by the at least one timestamp and the time when the first clock or the second clock was adjusted by the adjustment amount. The one or more processors 302 may be configured to determine an indicator of the user's health, well-being, or performance further based on the clock drift.

[0100] Use of stimulation time points The one or more processors 302 may be configured to receive from the wireless mobile device an indication of one or more stimulation times at which at least one stimulation is to be provided to the user, and to determine an indicator of the user's health, well-being, or performance further based on the indication of the one or more stimulation times.

[0101] The representation of the one or more stimulation time points may include a temporal correlation between the one or more stimulation time points and at least one measured quantity and / or at least one timestamp. The representation of the one or more stimulation time points may be used to divide the at least one measured quantity (e.g., the representation) into a plurality of segments. Each of the segments may correspond to an epoch of the biological signal. Each segment may be identified as a predetermined time slot with reference to one or more of the stimulation time points. For example, each segment may be a time slot starting 50 ms before the stimulation time point and ending 450 ms after the stimulation time point. The one or more processors 302 may be configured to analyze the plurality of segments to identify characteristics present in a predetermined number of segments, most segments, or all segments. An indicator of the user's health, well-being, or performance may be determined based on the identified characteristics.

[0102] Use of User Data The one or more processors 302 may be configured to receive user data from the wireless mobile device representing user input received via a user interface of the wireless mobile device, and the one or more processors 302 may be configured to determine an indicator of the user's health, well-being, or performance further based on the user data.

[0103] The user data may include a temporal correlation between one or more time points of received user input and at least one measured quantity. The user data may include a temporal correlation between one or more time points of received user input and one or more time points of stimulation. The user data may include a selection of a predetermined set of alternatives, provided to the user, for example, via a user interface or a stimulation interface. The one or more processors may be configured to determine an indicator of the user's health, well-being, or performance based on the identified characteristics and the user data. For example, the type or nature of the characteristic (e.g., of interest) identified by the one or more processors 302 may be selected from a predetermined set of types or characteristics based on the user data by the one or more processors 302.

[0104] Use of an indication of the type of wireless device or configuration The one or more processors 302 may be configured to receive an indication of a type of wireless portable device or wireless head wearable sensor configuration from the wireless portable device, obtain predetermined information regarding a time delay associated with the type of wireless portable device or wireless head wearable sensor configuration, and determine an indicator of the user's health, well-being, or performance further based on the time delay.

[0105] The predetermined information regarding time delay may be information regarding the time delay between a stimulus time point provided by a processor of the wireless mobile device and the actual time at which the stimulus is output. The one or more processors 302 may be configured to adjust one or more stimulus time points defined by a received indication of one or more stimulus time points based on the predetermined information regarding time delay. For example, an indication of the type of wireless device may identify that the wireless device is manufactured by a company such as Samsung®. The predetermined information regarding time delay may identify that one or more stimulus time points provided by the displayed Samsung® wireless device are actually 30 ms earlier than the actual time at which stimuli are output via a stimulus interface (e.g., visual stimuli output on a display, auditory stimuli output via a speaker or audio output interface, or tactile stimuli output via a tactile vibration interface). Thus, the one or more processors 302 may time adjust one or more stimulus time points as defined in the indication of the received one or more stimulus time points (e.g., in the above example of a Samsung® wireless device, by adding 30 ms to each of the one or more stimulus time points).

[0106] The temporal coordination between one or more stimulation time points and at least one measured quantity may vary based on predetermined information regarding time delays, in which case the one or more processors 302 may use one or more time-adjusted stimulation time points as described above for the (e.g., unadjusted) one or more stimulation time points.

[0107] Different types of wireless mobile devices may introduce different delays between a user's response and a response registered by the wireless mobile device via a user interface (e.g., user input received via a microphone, touchscreen, accelerometer, etc.) The one or more processors 302 may be configured to adjust one or more time points of the received user input and / or a temporal coordination between the one or more time points of the received user input and at least one measured quantity based on predetermined information regarding the time delay.

[0108] Adjustment of measured quantities The one or more processors 302 determine at least one time-adjusted measurement by temporally adjusting at least a portion of a representation of the at least one measurement based at least in part on information received from the wireless portable device, and determine an indicator of the health, well-being, or performance of a user of the wireless head-wearable sensor configuration based on the at least one time-adjusted measurement. In other words, the representation may be stretched, compressed, or scaled (e.g., in the time domain) based at least in part on information received from the wireless portable device, such as an indication of one or more stimulus time points, an indication of an adjustment amount, or an indication of an adjustment amount command. At least a portion of the at least one measurement may be temporally adjusted by scaling such that at least one timestamp corresponds to or matches one or more stimulus time points. At least a portion of the at least one measurement may be temporally adjusted (e.g., linearly scaled) to compensate for clock drift between the first clock and the second clock determined as described above. In this sense, it should be noted that the compensated clock drift may be assumed to be constant, one or more stimulus time points may be defined using a second clock, and at least one measured quantity may be time-stamped with at least one time-stamp defined using a first clock.

[0109] Adjusting the timestamp The one or more processors 302 may be configured to determine at least one time-adjusted timestamp by temporally adjusting at least one timestamp assigned to at least one measured quantity based on (e.g., all or at least a portion of) information received from the wireless mobile device (e.g., based on one or more of the adjustment amount, adjustment amount command, time offset, at least one timestamp, sixth timestamp, seventh timestamp, eighth timestamp, and ninth timestamp), and to determine an indicator of the health, well-being, or performance of a user of the wireless head-wearable sensor configuration further based on the at least one time-adjusted timestamp. The at least one timestamp may be adjusted based on predetermined information regarding the time delay described above. The at least one timestamp may be adjusted to have a predetermined relative temporal position with respect to one or more of the stimulation time points. Adjusting the at least one timestamp may scale a portion of a display of the at least one measured quantity associated with the at least one timestamp.

[0110] Adjusting the temporal coordination of stimulus timing The one or more processors 302 may be configured to determine time-adjusted stimulation data by adjusting a temporal linkage between one or more stimulation time points and the at least one measurement quantity (e.g., at least one timestamp assigned thereto) based on at least a portion of the information received from the wireless mobile device (e.g., one or more of the time offset, the adjustment amount, the adjustment amount command, the temporal linkage between the adjustment amount and the at least one measurement quantity, or the adjustment amount command and the at least one measurement quantity), and to determine an indicator of the health, well-being, or performance of a user of the wireless head-wearable sensor configuration further based on the time-adjusted stimulation data. The temporal linkage between the one or more stimulation time points and the at least one measurement quantity may be adjusted (e.g., linearly) to compensate for a (e.g., constant) clock drift between the first clock and the second clock, determined as described above.

[0111] Adjusting the time alignment of user input points The one or more processors 302 may be configured to determine time-adjusted user data by adjusting a temporal correlation between a time point of receipt of one or more user inputs and the at least one measurement quantity based on at least a portion of the information received from the wireless mobile device (e.g., one or more of the time offset, the adjustment amount, the adjustment amount command, and the temporal correlation between the adjustment amount and the at least one measurement quantity or between the adjustment amount command and the at least one measurement quantity), and to determine an indicator of the health, well-being, or performance of a user of the wireless head-wearable sensor arrangement further based on the time-adjusted user data. The temporal correlation between the time point of receipt of the one or more user inputs and the at least one measurement quantity may be adjusted to compensate for a (e.g., a certain) clock drift between the first clock and the second clock, determined as described above. In this sense, it should be noted that the time point of receipt of the one or more user inputs may be defined using the second clock, and the at least one measurement quantity may be time-stamped with at least one timestamp defined using the first clock.

[0112] Identifying Features The one or more processors 302 may be configured to identify at least one feature indicative of the user's brain health in the at least one measurement and / or at least one time-corrected (e.g., time-adjusted or scaled) measurement based on at least a portion of the information received from the wireless mobile device (e.g., medical data, time offset, indication of adjustment amount, adjustment amount command, indication of type of wireless device or wireless head wearable sensor configuration, indication of one or more stimulation time points and / or user data), and determine an indicator of the health, well-being or performance of the user of the wireless head wearable sensor configuration based on the identified at least one feature.

[0113] The at least one feature indicative of the user's brain health may be any of the above-mentioned features having predetermined (eg, spatial, temporal and / or frequency) characteristics.

[0114] The one or more processors 302 may be configured to identify at least one feature indicative of the user's brain health using a machine learning classifier and / or determine an indicator of the user's health, well-being or performance based on the at least one feature identified using the machine learning classifier. Examples of such machine learning classifiers include logistic regression, random forests and other decision tree-based methods, support vector machines, (deep) neural networks and variations thereof.

[0115] The one or more processors 302 may be configured to identify at least one feature using at least one of frequency analysis and connectivity analysis such as power spectral density estimation, event-related time-frequency spectral changes, Granger causality, inter-trial phase coherence, phase synchrony, low-resolution electrical tomography or variations thereof, beamforming, brain potential source analysis, and the like.

[0116] If the biological signal is an EEG signal, the at least one feature may include at least one of evoked potentials, EPs, and event-related potentials, ERPs, spectral measures such as changes in event-related time-frequency spectra, power spectral density, measures of connectivity, and measures of complexity and entropy.

[0117] Visual output of processing results The one or more processors 302 may be configured to determine a visual representation of an indicator of the user's health, well-being, or performance and output the visual representation to a display (e.g., to a display of a user terminal connected to the computing system 300, to a stimulation interface of the wireless device 200, or to a user input interface of the wireless device 200).

[0118] Processing System Figure 4 is according to the present disclosure Medical Data Processing System 10001 illustrates an embodiment of a medical data processing system 1000. The medical data processing system 1000 may include a wireless head-wearable sensor configuration 100, a wireless portable device 200, and a computing system 300. The first wireless interface 104 of the wireless head-wearable sensor configuration 100 may be communicatively coupled to the second wireless interface 204 of the wireless portable device 200. The wireless portable device 200 may be communicatively coupled to the computing system 300 (e.g., via the second wireless interface 204), for example, via a wired or wireless connection.

[0119] First medical data processing method Figure 5 is according to the present disclosure First medical data processing method 1 shows an embodiment of the present invention.

[0120] The method is a medical data processing method for obtaining a processed measure of the biological signal from an initial measure of the biological signal. The method is performed by a computer system (e.g., computer system 300). The method includes obtaining 500 medical data representing at least one initial measure of the biological signal in a first domain (e.g., at least one measure described above). The method includes decomposing 500 the at least one initial measure into a joint frequency domain to obtain transformed data representing the at least one initial measure in both the first domain and the frequency domain. The method includes fitting 504 at least one autoregressive model to the transformed data. The method includes determining 506 at least one deviation between the at least one fitted autoregressive model and the transformed data. The method includes obtaining 508 the processed measure of the biological signal based on the at least one deviation.

[0121] Processed Data The processed measurement is called "processed" because it is determined by a computer system based on at least one initial measurement and can be considered a result of processing the initial measurement by the computer system. The processed measurement can be an augmented measurement. The processed measurement can have an improved signal-to-noise ratio relative to the initial measurement. The biological signal can have multiple epochs. The processed measurement of the biological signal can have a lower standard deviation over the epochs compared to the initial measurement.

[0122] The processed measurements may be augmented (e.g., using a machine learning classifier) ​​to more reliably identify features therein, to reduce the amplitude of artifacts therein, and / or to reduce the number of artifacts therein, which may be indicative of the health, well-being, or performance of a human or animal whose body provides the biosignal.

[0123] Medical Data The medical data may be obtained from a wireless mobile device as described herein (e.g., wireless mobile device 200). The medical data may represent the at least one initial measurement by including the at least one initial measurement, by including a (e.g., numeric or digital) representation of the at least one initial measurement, or by including a (e.g., high-pass, band-pass, or low-pass) filtered version of the at least one initial measurement.

[0124] Transformed Data The term "transformed data" may relate to the fact that the data represents a "transform" (e.g., decomposition) of at least one initial measurement. The transformed data may include or consist of a decomposition of at least one initial measurement. The decomposition of at least one initial measurement may represent at least one measurement in the joint domain. The transformed data may include a representation of at least one initial measurement in the joint domain. The transformed data may include a representation of at least one initial measurement in both the first domain and the frequency domain.

[0125] Autoregressive Model The at least one (e.g., two or more) autoregressive models may be autoregressive models AR(p) of order p, where p may be 1 or more. In other examples, p may be 2 or 3. The at least one autoregressive model may be fitted to the transformed data (e.g., representations of the at least one initial measurement in both the first domain and the frequency domain) so as to minimize an error measure, such as a maximum deviation, an average deviation, or a mean deviation, between the at least one autoregressive model and the transformed data. The at least one autoregressive model may be fitted to the transformed data by estimating or adapting one or more parameters of the at least one autoregressive model. The one or more parameters may be estimated based on a least-squares method or a moment method based on the Yule-Walker equation. Other possibilities for fitting an AR model to data may be known to those skilled in the art and are applicable here. One method for fitting an autoregressive model to a segment contained in the transformed data is further described below.

[0126] Obtaining the processed measure may include using the at least one deviation as the processed measure or determining the processed measure based on the at least one deviation, wherein the at least one deviation may be determined in the combined region.

[0127] Recomposition and lossless conversion Determining the processed measure may include recombining the at least one deviation into the first domain. Recombining the at least one deviation may transform the at least one deviation from the combined domain to the first domain.

[0128] At least one initial measurement may be decomposed into a joint frequency domain by applying a reversible transform, e.g., a bijective function. At least one deviation may be recombined into the first domain by applying an inverse of the reversible transform. An interpolating or approximating function may be fitted to the at least one deviation over the first domain. The fitted function may be recombined into the (e.g., original, pre-decomposed, or single) first domain to obtain a processed measurement.

[0129] residual The at least one deviation may include or consist of one or more residuals of the at least one fitted autoregressive model. The at least one deviation may include all residuals of the at least one fitted autoregressive model. The commonly known definition of the term "residual" as used consistently in the field of autoregressive models applies. Alternatively, or in addition, the residual may be the deviation between the fitted autoregressive model and the fitted data.

[0130] Disassembly Sequence At least one initial measurement quantity (e.g., corresponding to at least one measurement quantity described above) may be decomposed into a joint frequency domain to determine a separate decomposed sequence for each of the at least one initial measurement quantity for each of a plurality of frequencies or frequency bands. The transformed data includes the determined decomposed sequences. Each decomposed sequence may define a portion of the at least one initial measurement quantity at a predetermined frequency or frequency band. The at least one initial measurement quantity may be decomposed into a plurality of decomposed sequences, each associated with a different frequency or frequency band. Each decomposed sequence may represent a (e.g., frequency) resolved portion of the at least one initial measurement quantity in a first domain. Each decomposed sequence may have an amplitude corresponding to the magnitude of a coefficient obtained by a transform used to decompose the at least one initial measurement quantity.

[0131] Fitting an autoregressive model to a segment At least one autoregressive model may be fitted to the transformed data over or within the first region. At least one autoregressive model may be fitted to at least one segment of one of the decomposed sequences (e.g., over the first region of the at least one segment).

[0132] At least one autoregressive model may be a vector autoregressive model (VAR) and may be fitted to one or more (e.g., segments thereof) of the decomposed sequence. The VAR model may be fitted to all segments that include a predetermined point in the first region or a point adjacent to a predetermined point in the first region. The predetermined point may be a point (e.g., a time or location) in the first region where a stimulus that produces a biological signal (e.g., a response therein) is applied to a human or animal. The fitted VAR model may include parameters adaptable to a signal type such that the fitted VAR model can be adapted to a signal type of interest by adapting the parameters. Different signal types may represent different characteristics (e.g., brain health). The parameters may be exogenous factors that indicate additional information about the stimulus, such as the type of stimulus, stimulus intensity, or the time or space of the stimulus. In this case, the AR model may be an autoregressive linear mixed-effects model.

[0133] At least one autoregressive model may be fitted to at least one segment of two or more different decomposed sequences for the same frequency or frequency band.

[0134] At least one segment can be defined as an interval in the first region, the interval can have a predetermined length, which can be longer than a length of a feature of interest identified in the processed measurements.

[0135] At least one segment may correspond to a single epoch of the biological signal. An epoch may be a segment of data that corresponds to or is expected to include a feature of interest recorded in the biological signal (e.g., due to a given stimulus, command, or other event that affects the biological signal and is precisely time-locked). An epoch may be a portion of the biological signal that includes at least one feature of interest. An epoch may also be referred to as a trial. An epoch may be a time window having a predetermined length, which may be longer than the length of the feature of interest identified in the processed measure.

[0136] Identifying segments The method may further include identifying (eg, defining) at least one segment in the at least one initial measurement or in one or more decomposition sequences.

[0137] At least one segment can be defined relative to a first point (e.g., a stimulation point) within the first region, the first point being associated with a stimulus that produces or affects a biological signal. The first point can be a time point referred to herein as a stimulation time point.

[0138] Alternatively, at least one segment may be identified by matching a first point (e.g., a stimulation point) in a first region to a second point (e.g., in the first region) in at least one initial measurement or one or more decomposed sequences. The first point is associated with a stimulation that produces or affects a biological signal. The matching may be based on a first region association between the first point and the at least one initial measurement or a first region association between the first point and one or more decomposed sequences. The first point may correspond to a second point in the first region. At least one segment may be defined relative to the second point.

[0139] The method may include obtaining a representation of the first point from a wireless mobile device, such as the wireless mobile device 200 .

[0140] The method may include obtaining a representation of one or more stimulation time points including a temporal link between the one or more stimulation time points and at least one initial measurement. Based on the temporal link between the one or more stimulation time points and the at least one initial measurement, a relative position of the stimulation time point with respect to the at least one initial measurement may be determined. This relative position may be used to divide the at least one initial measurement (e.g., a representation thereof) into segments. Each segment may be identified as a predetermined time slot with reference to one or more of the stimulation time points. For example, each segment may be a time slot starting a first predetermined amount of time (e.g., 50 ms) before the stimulation time point and ending a second predetermined amount of time (e.g., 450 ms) after the stimulation time point.

[0141] The stimulus may be one or more of an auditory, visual, tactile or olfactory stimulus applied to a human or animal having a body that provides a biosignal.

[0142] Segment Decomposition Each of the at least one identified segment of the at least one initial measurand may be individually decomposed into a joint frequency domain to obtain at least one segment of one or more decomposed sequences.

[0143] Overlapping initial measurements The at least one initial measurement may include a first initial measurement of the biological signal in a first portion of the first region and a second initial measurement of the biological signal in the first portion of the first region. The first initial measurement may overlap with the second initial measurement in the first region. For example, multiple measurements may be taken simultaneously to generate the first initial measurement and the second initial measurement of the biological signal in the time domain.

[0144] (Wavelet) Transform At least one initial measurement may be decomposed into a joint frequency domain by applying a transform with varying resolution in a first domain (e.g., varying first domain resolution). The varying resolution may vary across frequencies. At least one initial measurement may be decomposed into a joint frequency domain by applying a wavelet transform. The wavelet transform may be a discrete wavelet transform (DWT). The wavelet transform may use wavelets from the Debauchies-4, Symlet-5, or Coiflet-2 mother wavelet families. Furthermore, the wavelet form is or may become apparent to those skilled in the art of wavelet transforms. Each of the decomposition sequences may have an amplitude corresponding to the magnitude of the approximation or detail coefficients obtained by the DWT.

[0145] First Region and Combined Frequency Region The combined frequency domain may be a combined (e.g., combined) domain of the first domain and the frequency domain. In a first variant, the first domain may be the time domain and the combined frequency domain may be the time-frequency domain, and the at least one initial measurement quantity may optionally be a time-varying measured amplitude. In a second variant, the first domain may be the spatial domain and the combined frequency domain may be the spatial-frequency domain, and the at least one initial measurement quantity may optionally be a space-varying measured amplitude.

[0146] Computer system and computer program product for first medical data processing method The present disclosure also provides a computing system comprising at least one memory and at least one processor, the at least one memory storing instructions that, when executed on the at least one processor, cause the at least one processor to perform a method according to the fifth aspect. The computing system may be system 300 as described herein. The at least one processor corresponds to one or more processors 302, and the at least one memory corresponds to one or more memories 304.

[0147] The present disclosure also provides a computer program product including program code portions for performing a first medical data processing method when executed on at least one processor (e.g., one or more processors 302). The computer program product may be stored on one or more computer-readable recording media (e.g., one or more memories 304).

[0148] Second medical data processing method Figure 6 is according to the present disclosure Second medical data processing method 1 shows an embodiment of the present invention.

[0149] The second medical data processing method is a medical data processing method for obtaining a processed measurement of a biological signal from an initial measurement of the biological signal. The method is performed by a computer system (e.g., computer system 300). The method includes obtaining 600 medical data representing at least one initial measurement of the biological signal in a first domain (e.g., at least one measurement described above). The method includes decomposing the at least one initial measurement into a joint frequency domain to determine 602 a separate decomposed sequence in the first domain for each of the at least one initial measurement for each of a plurality of frequencies or frequency bands. The method includes determining 604 at least one estimated point by applying a robust aggregation method to multiple corresponding points in one or more of the decomposed sequences for the same frequency or frequency band. The method includes recombining 606 the at least one estimated point into the first domain to obtain a processed measurement of the biological signal.

[0150] Processed Data A processed measurement is determined by a computer system based on at least one initial measurement and is referred to as "processed" because it can be considered the result of processing the initial measurement by the computer system. A processed measurement can be an augmented measurement. A processed measurement can have an improved signal-to-noise ratio relative to the initial measurement. The biosignal can have multiple epochs. A processed measurement of a biosignal can have a lower standard deviation over epochs compared to the initial measurement. A processed measurement can be augmented to reduce the amplitude of artifacts therein and / or to reduce the number of artifacts therein so that features therein can be more reliably identified (e.g., using a machine learning classifier). The features can be indicative of the health, well-being, or performance of a human or animal whose body provides the biosignal.

[0151] Medical Data The medical data may be obtained from a wireless mobile device as described herein (e.g., wireless mobile device 200). The medical data may represent the at least one initial measurement by including the at least one initial measurement, by including a (e.g., numeric or digital) representation of the at least one initial measurement, or by including a (e.g., high-pass, band-pass, or low-pass) filtered version of the at least one initial measurement.

[0152] Disassembly Sequence Each decomposition sequence may define a portion of the at least one initial measurement at a predetermined frequency or frequency band. The at least one initial measurement may be decomposed into multiple decomposition sequences, each associated with a different frequency or frequency band. Each decomposition sequence may represent a (e.g., frequency) resolved portion of the at least one initial measurement in a first domain. Each decomposition sequence may have an amplitude corresponding to the magnitude of a coefficient obtained by a transform used to decompose the at least one initial measurement.

[0153] Estimated point The at least one estimate point may be an output or result of the robust aggregation method. The at least one estimate point may be determined in the combined region. The at least one estimate point may be recombined from the combined region to the original or pre-decomposed region. An interpolation or approximation function may be fitted to the at least one estimate point over the first region. The fitted function may be recombined to the first region (e.g., original, pre-decomposed, or single) to obtain the at least one recombined estimate point. The at least one estimate point may have a value determined by the robust aggregation method from the amplitude of the decomposed measure at the corresponding point. The at least one estimate point may have a (pre-)determined location in the first region, and is therefore referred to as an estimate "point."

[0154] Application of robust aggregation methods Applying the robust aggregation method to the plurality of corresponding points may include applying the robust aggregation method to amplitude values ​​of the plurality of corresponding points represented in the joint region. Applying the robust aggregation method may include aggregating the amplitude values ​​of the plurality of corresponding points. Applying the robust aggregation method may consist of or include determining a statistical measure or value representing a parameter of a hypothetical (e.g., predetermined) underlying distribution (e.g., normal or gamma distribution) or family of distributions (e.g., symmetric, bimodal, or heavy-tailed) of the plurality of corresponding points (e.g., their amplitude values).

[0155] Robust Aggregation Methods A robust aggregation method may be a robust statistical method for obtaining a measure of a virtual underlying distribution of multiple corresponding points (e.g., their amplitude values). Such a measure of the virtual underlying distribution may include values ​​of parameters of the virtual underlying distribution, such as location, spread, or skewness. A robust aggregation method may provide a measure for (e.g., even or only for) data that does not fit the virtual underlying distribution. A robust aggregation method may be resistant to outliers and / or incorrect assumptions about the distribution. A robust aggregation method may satisfy at least one of the following criteria: (i) Robust, insensitive, and / or resistant statistical methods. (ii) have a bounded influence function; (iii) has a break point of 0.5 or a break point between 0.4 and 0.5;

[0156] Applying the robust aggregation method may include or consist of estimating values ​​of parameters of the virtual underlying distribution using weights applied to the plurality of corresponding points. The weighting may include zero weighting (e.g., to create a subset of the data). Applying the robust aggregation method may include or consist of determining at least one of a median, a trimmed mean, or an M-estimate of the plurality of corresponding points. A trimmed mean may also be referred to as a truncated mean. A trimmed mean may be an interquartile mean. At least one estimated point may have a value (e.g., amplitude) corresponding to a parameter of the virtual underlying distribution, such as the median, trimmed mean, or M-estimate of the corresponding points.

[0157] The virtual basis distribution may be predetermined or selected from a set of distributions based on the type of biosignal and / or based on features of interest within the biosignal.

[0158] Corresponding points and segments Each of the corresponding points may have a position (e.g., first-domain) that is similar (e.g., "corresponding") to the position of the estimated point. Each of the multiple corresponding points may have the same or similar position within a segment of the decomposed sequence that includes the corresponding point. The same position may be a first-domain position. Each segment of the determined decomposed sequence may include only one corresponding point.

[0159] A segment may be defined as an interval in the first region, which may have a predetermined length, which may be longer than the length of a feature of interest identified in the processed measurement.

[0160] At least one segment may correspond to an epoch of the biological signal. An epoch may be a segment of data that corresponds to or is expected to include a feature of interest recorded in the biological signal (e.g., due to a given stimulus, command, or other event that affects the biological signal and is precisely time-locked). An epoch may be a portion of the biological signal that includes at least one feature of interest. An epoch may also be referred to as a trial. An epoch may be a time window having a predetermined length. This predetermined length may be longer than the length of the feature of interest identified in the processed measure.

[0161] array of estimated points The at least one estimated point may include a set of estimated points determined by aggregating (e.g., applying a robust aggregation method to) all corresponding points within respective segments of one or more different decomposed sequences for the same frequency or frequency band.

[0162] Identifying segments The method may further include identifying (eg, defining) at least one segment in the at least one initial measurement or in one or more decomposition sequences.

[0163] At least one segment can be defined relative to a first point (e.g., a stimulation point) within the first region, the first point being associated with a stimulus that produces or affects a biological signal. The first point can be a time point referred to herein as a stimulation time point.

[0164] Alternatively, at least one segment may be identified by matching a first point (e.g., a stimulation point) in a first region to a second point (e.g., in the first region) in at least one initial measurement or one or more decomposed sequences. The first point is associated with a stimulation that produces or affects a biological signal. The matching may be based on a first region association between the first point and the at least one initial measurement or a first region association between the first point and one or more decomposed sequences. The first point may correspond to a second point in the first region. At least one segment may be defined relative to the second point.

[0165] The method may include obtaining a representation of the first point from a wireless mobile device, such as the wireless mobile device 200 .

[0166] The method may include obtaining a representation of one or more stimulation time points including a temporal link between the one or more stimulation time points and at least one initial measurement. Based on the temporal link between the one or more stimulation time points and the at least one initial measurement, a relative position of the stimulation time point with respect to the at least one initial measurement may be determined. This relative position may be used to divide the at least one initial measurement (e.g., a representation thereof) into segments. Each segment may be identified as a predetermined time slot with reference to one or more of the stimulation time points. For example, each segment may be a time slot starting a first predetermined amount of time (e.g., 50 ms) before the stimulation time point and ending a second predetermined amount of time (e.g., 450 ms) after the stimulation time point.

[0167] The stimulus may be one or more of an auditory, visual, tactile or olfactory stimulus applied to a human or animal having a body that provides a biosignal.

[0168] Decomposing a segment Each of the identified segments of the at least one initial measure may be individually decomposed into a joint frequency domain to obtain segments of the decomposed sequence containing corresponding points.

[0169] Overlapping measures The at least one initial measurement may include a first initial measurement of the biological signal in a first portion of the first region and a second initial measurement of the biological signal in the first portion of the first region, and the first initial measurement may overlap with the second initial measurement in the first region.

[0170] (Wavelet) Transform The at least one initial measurement may be decomposed into a joint frequency domain by applying a transform with varying resolution in a first domain (e.g., varying first domain resolution). The varying resolution may vary across frequencies. The at least one initial measurement may be decomposed into a joint frequency domain by applying a wavelet transform. The wavelet transform may be a discrete wavelet transform (DWT). The wavelet transform may use wavelets from the Debauchies-4, Symlet-5, or Coiflet-2 mother wavelet families. Each of the decomposition sequences may have an amplitude corresponding to the magnitude of the approximation or detail coefficients obtained by the DWT.

[0171] join area In a first variant, the first domain may be the time domain, the combined frequency domain may be the time-frequency domain, and the at least one initial measurement quantity may optionally be a time-varying measured amplitude. In a second variant, the first domain may be the spatial domain, the combined frequency domain may be the spatial-frequency domain, and the at least one initial measurement quantity may optionally be a space-varying measured amplitude.

[0172] Combination of the first and second medical data processing methods The method of the fourth aspect can be combined with the method of the first aspect, or vice versa. For example, at least one deviation obtained by the method of the first aspect can be used as a corresponding point in the method of the second aspect. A robust aggregation method can be applied to the at least one deviation to determine at least one estimated point. Alternatively, at least one autoregressive model can be fitted to the at least one estimated point, fitted function, or set of estimated points.

[0173] Use of processed measures of the first or second medical data processing method for characterization The processed measurements of the first medical data processing method or the processed measurements of the second medical data processing method may be used to identify at least one feature indicative of the user's brain health (e.g., as described above with reference to Figure 3). The first medical data processing method and / or the second medical data processing method may further comprise identifying, in the processed measurements, at least one feature indicative of the user's brain health.

[0174] The first medical data processing method and / or the second medical data processing method may further include determining an indicator of the health, well-being, or performance of a human or animal based on the identified at least one feature. The human or animal has a body that generates a biological signal. The human or animal may be a user of a wireless head-wearable sensor configuration (e.g., configuration 100) including at least one sensor (e.g., sensor 102) for generating at least one initial measurement. The at least one feature indicative of the user's brain health may be a feature described above with reference to FIG. 3. The at least one feature indicative of the user's brain health may have predetermined (e.g., spatial, temporal, and / or frequency) characteristics.

[0175] At least one feature indicative of the user's brain health may be identified using a machine learning classifier (e.g., by one or more processors 302). An indicator of the user's health, well-being, or performance may be determined based on the at least one feature identified using the machine learning classifier.

[0176] Combination of the first medical data processing method and / or the second medical data processing method with time correction The first medical data processing method and / or the second medical data processing method may include one or more steps performed by one or more processors 302 described above with reference to Figure 3. The first medical data processing method and / or the second medical data processing method may include obtaining an indication of at least one measurement quantity, at least one timestamp assigned to the at least one measurement quantity, and one or more stimulation time points, and may further include adjusting a temporal alignment between the one or more stimulation time points and the at least one timestamp or between the one or more stimulation time points and the at least one measurement quantity before identifying or determining a segment. Alternatively, or in addition, the processed measurement quantities may be time-corrected (e.g., as described above with reference to Figure 3) before a segment is determined based on the time-corrected measurement quantities.

[0177] The processed measurements of the first medical data processing method and / or the second medical data processing method may correspond to the "at least one measurement" used to determine an indicator of health, well-being, or performance as described above with reference to FIG. 3. In other words, the one or more processors 302 may be configured to determine the processed measurements by the first medical data processing method and / or the second medical data processing method, and determine the indicator of health, well-being, or performance based on the processed measurements (e.g., by identifying at least one feature indicative of the user's brain health in the processed measurements). The initial measurements of the first medical data processing method and / or the second medical data processing method may be time-corrected before decomposition, as described above with reference to FIG. 3. In this case, the initial measurements may correspond to the "at least one measurement" referred to in the description of FIG. 3.

[0178] The processed measurements of the first medical data processing method and / or the second medical data processing method may be averaged over all segments contained therein, and the resulting average data may then be used to identify at least one feature.

[0179] Flowchart of time synchronization example Figure 7 7 shows four example diagrams of how a time synchronization procedure may be performed between a wireless head-wearable sensor configuration (e.g., configuration 100) and a wireless mobile device (e.g., device 200). The top left diagram represents an embodiment of examples A) and a) described above with reference to FIGS. 1 and 2. The bottom left diagram represents an embodiment of examples B) and b) described above with reference to FIGS. 1 and 2. The top right diagram represents an embodiment of examples C) and c) described above with reference to FIGS. 1 and 2. The bottom right diagram represents an embodiment of examples D) and d) described above with reference to FIGS. 1 and 2. As can be seen, a time information request message "Time Information Request" is sent from the wireless head-wearable sensor device to the wireless mobile device or vice versa. Therefore, the following description of FIG. 7 uses the same terminology as used in the description of FIGS. 1 and 2.

[0180] The time information request message in the example of Figure 7 includes a first timestamp "TS1". A time information response message "Time Information Response" is sent in the opposite direction to the time information request message and, in the example of Figure 7, includes a third timestamp "TS3" and the first difference "Diff1" (e.g., an indication thereof). As can be seen, the configuration message is sent from the same device that previously sent the time information request message. In the example of Figure 7, the configuration message includes a second timestamp "TS2" and either an indication of the adjustment amount or an adjustment (amount) command.

[0181] Examples of segments of a measurand, decomposition sequences of first segments of a measurand, and processed measurands Figure 88 shows an exemplary measurement of a user's EEG signal. As discussed above, for example, with reference to FIG. 3, FIG. 5, or FIG. 6, the measurement is divided into a total of 30 segments or "trials." The horizontal axis represents time, and the vertical axis represents the measured voltage or potential. As can be seen, each segment or trial is identified or defined as a predetermined time slot that references a predetermined time point, shown as a vertical dotted line in each of the segments in FIG. 8. The predetermined time point in this example may be a stimulation time point, as discussed herein.

[0182] Figure 9 8 shows an expanded view of one of the segments of FIG. 8. Again, the predetermined time points are shown as vertical dotted lines. It can be seen that the segment begins a first predetermined time before the predetermined time point and ends a second predetermined time after the predetermined time point, which is longer. In the example shown, the first predetermined time is 100 ms and the second predetermined time is 500 ms.

[0183] Figure 1010 shows multiple decomposition sequences of the segment of FIG. 9. The decomposition sequences are obtained by decomposing the segment of FIG. 9 into the time-frequency domain, for example, in step 502 or step 602. Each of the decomposition sequences shown in FIG. 10 has an amplitude corresponding to the magnitude of the coefficients obtained by the transform used for the decomposition. In the example shown, the decomposition sequences are obtained by decomposing the segment of FIG. 9 using a discrete wavelet transform (DWT). Therefore, each of the decomposition sequences shown in FIG. 10 has an amplitude corresponding to the magnitude of the coefficients obtained by the DWT. As is known, when a signal is decomposed from the first domain to the joint frequency domain by applying the DWT, a set of detail coefficients and approximation coefficients is obtained for different layers of the DWT. The upper left diagram of FIG. 10 shows the magnitude of the approximation coefficients of the fifth layer, the upper center diagram shows the magnitude of the detail coefficients of the fifth layer, and the upper right diagram shows the magnitude of the detail coefficients of the fourth layer. The bottom left figure shows the magnitude of the detail coefficients in layer 3, the bottom center figure shows the magnitude of the detail coefficients in layer 2, and the bottom right figure shows the magnitude of the detail coefficients in layer 1. Each of these figures represents a separate decomposition sequence. The resolution of the DWT is higher in layer 1 than in higher layers such as layers 2, 3, 4, or 5.

[0184] Figure 11 11 shows the results of fitting an autoregressive model individually to each of the decomposition sequences shown in FIG. 10. The top left diagram shows the AR model fitted to the decomposition sequence shown in the top left diagram of FIG. 10, the top center diagram shows the AR model fitted to the decomposition sequence shown in the top center diagram of FIG. 10, and so on. In the example of FIG. 11, the fitted AR model is an AR(2) model. Fitting the AR model to the decomposition sequence may be performed as part of step 504. As discussed further below, linear or quadratic AR models have been demonstrated to produce the best results.

[0185] Figure 12 11 indicates the residuals of the fitted autoregressive model. The residuals may be determined as at least one deviation in step 506. The top left diagram shows the residuals of the fitted AR model of the top left diagram of FIG. 11, the top center diagram shows the residuals of the AR model of the top center diagram of FIG. 11, and so on. The residuals may be the difference between the fitted AR model and the decomposed sequence to which the AR model is fitted. The residuals may then be used as processed measures as described herein. Alternatively, the residuals may be recombined as described herein with reference to FIG. 13.

[0186] Figure 13 13 shows a comparison of the residuals shown in FIG. 12 after being recombined into the time domain. Also shown are the original EEG signals of the segments used to obtain the recombined residuals, as already described above with reference to FIG. 9. The diagram in FIG. 13 differs from FIG. 9 only in that the recombined residuals are added as dotted lines. The residuals shown in FIG. 13 were recombined from the time-frequency domain shown in FIG. 12 into the time domain by applying the inverse transform of the DWT that was previously used to decompose the segments of FIG. 9 into the decomposed sequence of FIG. 10. That is, the inverse of this transform was used to recombined the residuals from the combined domain back to the first domain. The recombined residuals can be used as the processed measurements described herein.

[0187] The procedures described with reference to Figures 8 through 13 may be performed for all of the segments of EEG measurements shown in Figure 8. As a result, resynthesized residuals are obtained for each segment. These resynthesized residuals may then be averaged between (e.g., across) the segments. This average value may then be used as the processed measurement described herein.

[0188] Figure 14shows three graphs to clarify the results of the above-mentioned processing. In the upper diagram, the average of the signals of all segments shown in FIG. 8 is plotted as a solid line. The dashed line represents the resynthesized residual averaged over all segments. It can be seen that the average of the resynthesized residual follows the mainstream of the average EEG signal of the segment. However, the average of the resynthesized residual shows different amplitudes for some of the peaks, for example, the peaks at 100 ms and 200 ms.

[0189] Furthermore, the combined results of the first and second medical data processing methods described herein are shown in FIG. 14. In this case, M-estimation (Huber's T-estimation) aggregation was applied to the residuals of the fitted AR(2) model shown in FIG. 12, and the aggregated results were recombined into the first domain by applying the inverse DWT. This was done for all segments. The average of all recombined M-estimation results is shown as a dotted line in the upper diagram of FIG. 14. Again, the average amplitude of the recombined M-estimation results differs from the averaged EEG signal at some of the peaks.

[0190] The effect of the processing described with reference to Figures 9 to 13 becomes even clearer with reference to the central diagram of Figure 14. This diagram shows the mean standard deviation of the segment's signal as a solid line, the mean standard deviation of the residual as a dashed line, and the mean standard deviation of the recombined M-estimation results as a dotted line.

[0191] It is clear that the standard deviation of the signal mean is much larger than the standard deviation of the resynthesized residual or the standard deviation of the resynthesized M-estimation results. In other words, the resynthesized residual and the resynthesized M-estimation results may be more consistent than the original EEG signal across different segments.

[0192] The bottom panel of Figure 14 shows the effect sizes of the signal mean, the recombined residual mean, and the recombined M-estimation mean. The effect sizes in this case are calculated as standardized means (i.e., the mean divided by the standard deviation). That is, the curves shown in the bottom panel of Figure 14 correspond to the values ​​of the curves in the top panel divided by the values ​​of the curves in the middle panel.

[0193] Statistical comparisons typically use the ratio of amplitude to variance. This ratio may be improved by implementing the first and / or second medical data processing methods described herein. In particular, by comparing the average effect size of the recombined residuals and recombined M-estimation results to the average EEG signal in the bottom diagram of FIG. 14 and considering the top diagram of FIG. 14, it is clear that the processing described above for FIGS. 8 through 13 results in significant peak effects near the 100 ms, 150 ms, and 250 ms time points. The value of the processed measurement at each of these time points may be a feature of interest. In this example, it may be said that the statistical efficiency of the processed measurement has been improved compared to the initial measurement.

[0194] Review Processing by the first medical data processing method, processing by the second medical data processing method, or a combination thereof may result in a processed measurand being more consistent across different segments. Generally speaking, the more consistent a measurand is across different segments of the measurand, the more reliable the detection of features in the measurand. Thus, the techniques described herein may enable more reliable detection of features of interest (e.g., generated electrical potentials) in the measurand.

[0195] At least one feature may be identified (e.g., by the system 300) based on a temporal characteristic of the feature relative to at least one timestamp. At least one feature may be identified in a time slot having a predetermined relationship to the at least one timestamp. The at least one timestamp may indicate a time of a stimulus time point or have a predetermined temporal difference therefrom. The segments described herein may be defined or identified based on the stimulus time point. Each of the segments may include at least one feature. Using the techniques and methods disclosed herein may ensure that at least one feature occurs in each of the segments at the same first region location. This may improve the reliability of identifying the at least one feature and reduce processing effort.

[0196] The techniques and methods disclosed herein may provide compensation for a time offset between a second clock of a wireless handheld device (e.g., device 200) providing a stimulus and a first clock of a sensor arrangement (e.g., arrangement 100) generating a measurand. This may ensure that at least one timestamp assigned to at least one measurand is in accordance with both the first and second clocks. This may further ensure that at least one feature occurs at the same first region location in each of the segments defined based on the at least one timestamp.

[0197] The techniques and methods disclosed herein may also provide compensation for clock drift between a first clock and a second clock. This may ensure that one or more stimulus time points have a known position in at least one (e.g., initial) measurement. This may allow for reliable segment determination relative to the stimulus time point. Therefore, it may be ensured that at least one feature occurs at the same first region location in each of the segments.

[0198] As indicated above, the first medical data processing method may be combined with the second medical data processing method, which may include one or more additional steps performed by the computer system 300, the device 200, or the configuration 100. Similarly, the computer system 300 may be configured to perform the first medical data processing method and / or the second medical data processing method in addition to the steps described above with reference to Figure 3. Other variations are possible without departing from the scope of the present disclosure.

Claims

1. A wireless head-wearable sensor arrangement (100) for transmitting medical data to a wireless mobile device (200), comprising: at least one sensor (102) configured to generate at least one measure of a biosignal of a user wearing the wireless head-wearable sensor arrangement (100); a first wireless interface (104); a first clock (106); a first processor (108), performing a time synchronization procedure to synchronize the first clock (106) with a second clock (206) of the wireless mobile device (200) or to instruct the second clock (206) of the wireless device (200) to synchronize with the first clock (106); After performing the time synchronization procedure, acquiring the at least one measurement of the biosignal of the user wearing the wireless head-wearable sensor arrangement (100) from the at least one sensor (102), assigning at least one timestamp to the acquired at least one measurement, and transmitting medical data including a representation of the at least one measurement and the at least one timestamp assigned to the at least one measurement to the wireless mobile device (200) via the first wireless interface (104). a first processor (108) configured to A wireless head-wearable sensor arrangement (100) comprising:

2. The first processor transmitting a time information request message to the wireless mobile device via the first wireless interface, the time information request message including a first timestamp of a transmission time of the time information request message; receiving a time information response message including synchronization information from the wireless portable device via the first wireless interface; and configured to perform the time synchronization procedure by The arrangement of claim 1 , wherein the first processor is configured to synchronize the first clock by adjusting the first clock based at least on the synchronization information.

3. 3. The arrangement of claim 2, wherein the first processor is configured to send a configuration message to the wireless mobile device via the first wireless interface after adjusting the first clock, the configuration message including at least one of a second timestamp of a transmission time of the configuration message and an indication of an amount of adjustment of the first clock.

4. the synchronization information is dependent on at least the first timestamp; 3. The arrangement of claim 2, wherein the synchronization information includes an indication of a first time difference between a time of transmission of the time information request message and a time of reception of the time information request message as indicated by the first timestamp.

5. the synchronization information includes a third timestamp of a transmission time of the time information response message; 5. The arrangement of claim 4, wherein the first processor is configured to determine a synchronization deviation between the first clock and the second clock based on the first time difference and a second time difference between a transmission time of the time information response message and a reception time of the time information response message, as indicated by the third timestamp.

6. The arrangement of claim 5 , wherein the first processor is configured to determine a round-trip latency based on the first time difference and the second time difference, and to determine the synchronization deviation further based on the round-trip latency.

7. 6. The arrangement of claim 5, wherein the first processor is configured to synchronize the first clock by adjusting the first clock to compensate for the determined synchronization deviation.

8. 6. The arrangement of claim 5, wherein the first processor is configured to determine an adjustment command for the second clock that instructs the wireless mobile device to adjust the second clock so that the determined synchronization deviation is compensated for.

9. A wireless portable device (200) for receiving medical data from a wireless head-wearable sensor arrangement (100), comprising: a second wireless interface (204); a second clock (206); a second processor (208), performing a time synchronization procedure to synchronize the second clock (206) with the first clock (106) of the wireless head wearable sensor configuration (100) or to direct the synchronization of the second clock (206) with the first clock (106) of the wireless head wearable sensor configuration (100); After performing the time synchronization procedure, receive medical data from the wireless head-wearable sensor configuration (100) via the second wireless interface (204), the medical data including a representation of at least one measurement of a biosignal of a user wearing the wireless head-wearable sensor configuration (100) and at least one timestamp assigned to the at least one measurement, and transmit the medical data to a computer system (300). a second processor (208) configured to A wireless mobile device (200) comprising:

10. The second processor receiving a time information request message from the wireless head wearable sensor configuration via the second wireless interface, the time information request message including a first timestamp of a transmission time of the time information request message; determining synchronization information based at least on information included in the time information request message; transmitting a time information response message including the synchronization information to the wireless head-wearable sensor configuration via the second wireless interface; It is configured as follows:

10. The device of claim 9, wherein the second processor is configured to receive a configuration message from the wireless head wearable sensor configuration via the second wireless interface after transmitting the time information response message, the configuration message including an instruction on an amount of adjustment of the first clock and a second timestamp of a transmission time of the configuration message.

11. the synchronization information is dependent on at least the first timestamp; 11. The device of claim 10, wherein the synchronization information includes an indication of a first time difference between a time of transmission of the time information request message and a time of reception of the time information request message, as indicated by the first timestamp.

12. The device of claim 11 , wherein the synchronization information includes a third timestamp of a transmission time of the time information response message.

13. the second processor is configured to receive a time synchronization request message from the wireless head wearable sensor arrangement via the second wireless interface and to begin performing the time synchronization procedure in response to receiving the time synchronization request message; 13. The device of claim 9, wherein the time synchronization request message includes a fourth timestamp of a transmission time of the time synchronization request message, and the second processor is configured to pre-adjust the second clock based on the transmission time of the time synchronization request message indicated by the fourth timestamp before performing the time synchronization procedure.

14. the second processor is configured to send a time synchronization request message to the wireless head wearable sensor configuration via the second wireless interface to trigger the wireless head wearable sensor configuration to start performing a time synchronization procedure; 10. The device of claim 9, wherein the time synchronization request message includes a fourth timestamp of a transmission time of the time synchronization request message and instructs the wireless head wearable sensor configuration to pre-adjust the first clock based on the transmission time of the time synchronization request message indicated by the fourth timestamp before performing the time synchronization procedure.

15. A computer system (300) for receiving medical data from a wireless mobile device (200), comprising: one or more processors, receiving medical data from a wireless portable device (200) including an indication of at least one measure of a biosignal of a user wearing the wireless head-wearable sensor arrangement (100) and at least one timestamp assigned to said at least one measure; determining an indication of the health, well-being, or performance of the user of the wireless head wearable sensor configuration based on the representation of the at least one measured quantity and the at least one timestamp assigned to the at least one measured quantity. one or more processors configured to Computer system.

16. The one or more processors receive from the wireless mobile device: an indication of the amount of adjustment of either the first clock or the second clock used to synchronize the first clock or the second clock; or An adjustment command used to synchronize the first clock or the second clock configured to receive the one or more processors are configured to determine the indicator of the user's health, well-being, or performance further based on the indication of the adjustment amount or the adjustment amount command.

16. The system of claim 15.

17. the one or more processors are configured to receive from the wireless mobile device a temporal correlation between the adjustment amount and the at least one measured amount or between the adjustment amount command and the at least one measured amount; the one or more processors are configured to determine the indicator of health, well-being, or performance of the user further based on the temporal coordination.

17. The system of claim 16.

18. The one or more processors: receiving from the wireless portable device an indication of one or more stimulus time points at which at least one stimulus is to be presented to the user; It is configured as follows:

18. The system of claim 15, wherein the one or more processors are configured to determine the indicator of health, well-being or performance of the user further based on the one or more stimulation time points.

19. the one or more processors are configured to receive user data from the wireless mobile device representing user input received via a user interface of the wireless mobile device, and the one or more processors are configured to determine the indicator of the health, well-being or performance of the user further based on the user data; 19. The system of claim 15, wherein the user data comprises a temporal link between a time point of receipt of one or more user inputs and the at least one measured quantity.

20. the one or more processors are configured to determine at least one time-adjusted measurement by temporally adjusting at least a portion of the display of the at least one measurement based at least in part on information received from the wireless mobile device, and to determine an indicator of the health, well-being, or performance of the user of the wireless head wearable sensor arrangement based on the at least one time-adjusted measurement; 20. The system of claim 15, wherein the one or more processors are configured to determine at least one time-adjusted timestamp by temporally adjusting the at least one timestamp assigned to the at least one measured quantity based at least in part on the information received from the wireless mobile device, and to determine an indicator of the health, well-being or performance of the user of the wireless head wearable sensor configuration further based on the at least one time-adjusted timestamp.

21. Wireless head-wearable sensor configuration, wireless mobile devices, and Computer System and at least two of The wireless head-wearable sensor arrangement is an arrangement according to claim 1, the wireless handheld device is a device according to claim 9, and / or the computing system is a system according to claim 15. Medical data processing system.

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