WO2016111696A1

WO2016111696A1 - A ppg-based physiological sensing system with a spatio-temporal sampling approach towards identifying and removing motion artifacts from optical signals

Info

Publication number: WO2016111696A1
Application number: PCT/US2015/010792
Authority: WO
Inventors: Laurence Richard OLIVIER
Original assignee: Lifeq Global Limited
Priority date: 2015-01-09
Filing date: 2015-01-09
Publication date: 2016-07-14

Abstract

The invention pertains to fitness and/or sport performance by determination of physiological parameters, heart rate and breathing rate as indicators of physical exertion/intensity during exercise. In one embodiment, a PPG-based physiological sensing system employing spatiotemporal sampling towards identifying and removing motion artifacts received from a wearable optical sensing device in real-time and during various states of activity. The device capable of sensing and transmitting signals representative of physiological parameters to a remote electronic device. The device comprises an optical sensing unit with a light-emitting and light-detecting module for measuring blood volume changes caused by expansion and contraction of the small blood vessels in the skin and underlying tissue during the cardiac cycle. The spatial arrangement and temporal sampling configuration (sequence) allows for a common absorption point to be determined mathematically for each multi-channel sampling period, thereby obtaining an instantaneous optical measurement at different positions on the propagating pulse wave.

Description

A PPG-based Physiological Sensing System with a Spatio-Temporal Sampling approach towards Identifying and Removing Motion Artifacts from Optical Signals

FIELD OF THE INVENTION

[0001] The present invention pertains mainly to the fields of fitness and/or sport performance - in particular by enabling robust and accurate determination of physiological parameters, including but not limited to heart rate and breathing rate as indicator of physical exertion or intensity during exercise, and for the subsequent determination, but not limited to, excess post-exercise oxygen consumption (EPOC, informally referred to as afterburn).

BACKGROUND [0002] Pulse rate, commonly and interchangeably referred to as heart rate, is the rate at which the heart beats measured in beats per minute (bpm). Heart rate measured during physical activity (e.g. exercise) is generally higher than when measured at rest, and serves as a measure of the efficiency with which the heart responds to the increased demand in blood supply during physical activity. Therefore, heart rate is often used to monitor and regulate the level of intensity or exertion during exercise.

[0003] The recent upswing in self-monitoring of physiological parameters has resulted in a growing interest and demand for non-invasive, unobtrusive, wearable physiological sensing devices capable of accurate measurements of heart rate and other physiological parameters in real-time and during various states of physical activity i.e. at rest, during moderate activity, and vigorous exercise.

[0004] To this end, photoplethysmography (PPG) is a well-known optical sensing technique in widespread use to measure blood analytes and hemodynamic properties. In the most basic form PPG technology requires only a light source (e.g., light-emitting diode, LED) to illuminate a tissue sample (e.g., skin) and a light detector (e.g., photodiode) to measure small changes in light intensity i.e., absorption associated with physiological properties of the sample interrogated. Absoiption of light by the interrogated sample may be the result of absorption by the skin (melanin content), tissue, blood (water/fluid and different hemoglobin species), as well as blood volume, i.e., the level of tissue perfusion as a result of expansion and contraction of the small blood vessels during the cardiac cycle. PPG signals representative of changes in blood volume during the cardiac cycle may be used to determine heart rate by examining the time intervals between successive peaks (or troughs) in the PPG signal or volume pulse wave. Furthermore, information pertaining to hemodynamic properties such as beat-to-beat blood pressure and pulse wave velocity (as indicator of arterial stiffness) may be extracted from the waveform characteristics of the PPG signal, while the unique light absorption properties of different hemoglobin (Hb) species at distinct wavelengths can be used to determine blood oxygen status i.e. oxygen saturation.

[0005] Physiological sensing devices based on PPG technology are well known in the art and exist in two configurations: i) reflectance, and ii) transmission type sensing devices. Reflectance type PPG-based sensing devices contain the light source and light detector on the same side of the sample being interrogated, while transmission type PPG-based sensing devices contain the light source and light detector on opposite sides of the sample being interrogated. A major advantage of reflectance type PPG-based sensing devices is their adaptability to various locations on the human body (e.g. a user's arm, leg, torso, etc.) whereas transmission type PPG-based sensing devices are limited to locations on the body that allow light to be readily transmitted (e.g. a user's fingertip, earlobe, or another relatively thin well-perfused tissue or body part).

[0006] Although LED and photodiode technology have played a central role in reducing the cost and size of modern PPG-based physiological sensing devices, a universal drawback of existing optical- based physiological sensing devices are their inherent susceptibility to interference and subsequent inaccuracies caused by motion artifacts. Various methods, sampling approaches, and signals processing techniques have been developed and described to reduce the effect of motion on optical signals. To this end, numerous existing devises employ a combination of optical and accelerometer based solutions; however, there is currently no method or device that resolves the problem satisfactory for all states of physical activity, including vigorous movement such as during exercise.

[0007] Therefore, there is a need for a solution that overcomes many problems and disadvantages associated with existing optical-based physiological sensing devices that address the susceptibility to interference and inaccuracies caused by motion artifacts across the various states of physical activity.

[0008] While the present invention is described in detail with reference to various embodiments in subsequent pages, it will be appreciated that the present invention is not limited to the embodiments described herein, and that modifications may be made without departing from the scope of the invention defined in the accompanying claims. SUMMARY

[0009] In one embodiment, the present invention discloses a reflectance type PPG-based physiological sensing system with a spatio-temporal sampling approach towards identifying and removing motion artifacts from optical signals received from a wearable optical sensing device to enable accurate and robust determination of physiological parameters including but not limited to heart rate during various states of physical activity. The PPG-based physiological sensing system comprises a wearable optical sensing device preferably worn on, but not limited to, a user's upper arm, in communication with a remote electronic device such as a smartphone (e.g., an iPhone™) containing a specialized developed software application. The wearable optical sensing device comprises an optical sensing unit with a light-emitting and light-detecting module for measuring blood volume changes caused by expansion and contraction of the small blood vessels in the skin and underlying tissue during the cardiac cycle. The physical design of the optical sensing unit allows rapid sequential, i.e., near instantaneous sampling at different positions on the propagating volume pulse wave. The spatial arrangement and temporal sampling configuration (sequence) of the system subsequently allows for a common absorption point to be determined mathematically for each multichannel sampling period, thereby obtaining an instantaneous optical measurement at different positions on the propagating pulse wave. The raw optical signals representative of blood volume change are transmitted to a remote electronic device executing a specialized developed software application configured to i) receive and process raw optical signals and ii) obtain, store and display accurate and robust physiological outputs, including but not limited to heart rate and breathing rate, to the user via a user interface. In addition, the processed optical signals are used to determine, but are not limited to the determination of, real time oxygen consumption (V0₂) and metrics gauging strenuousness of exercise such as, but not limited to, excess post-exercise oxygen consumption (EPOC, informally referred to as afterburn). Naturally, several additional physiologically relevant metrics such as, but not limited to, (i) exercise cadence, (ii) optimal exercise cadence, (iii) total oxygen consumption normalized to movement, (iv) EPOC normalized to movement, (v) V0₂max, (vi) orthostatic heart rate testing to gauge overtraining, (vii) heart rate variability, (viii) calorie usage, and (ix) blood lactate concentration can be determined (with or without the use of an accelerometer or other movement sensing technology). BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The accompanying figures, where alike reference numerals refer to identical or functionally similar elements throughout the separate views, and which together with the detailed description below are incorporated in and form part of the specification, serve to further illustrate various embodiments of, and to explain principles in accordance with, the present invention.

[0011] The present invention is described by way of an exemplary embodiment with reference to the accompanying representations, not drawn to any scale, in which:

[0012]

Figure 1 is a conceptual illustration of the exemplary embodiment of the PPG-based physiological sensing system comprising a wearable optical sensing device in communication with a remote electronic device containing and executing a specialized developed software application configured to process optical signals and display physiological outputs to the user via the user interface.

Figure 2 is a conceptual illustration of the electronic components comprising the wearable optical sensing device preferably worn but not limited to a user's upper arm.

Figure 3 is a conceptual illustration of the electronic components comprising the remote electronic device such as a smartphone (e.g. an iPhone™).

Figure 4 is a conceptual illustration of the optical sensing unit comprising a light-emitting and light-detecting module, and the arrangement thereof within the scope of the exemplary embodiment.

Figure 5 is a series of conceptual illustrations of the spatio-temporal sampling approach, employed towards identifying and removing motion artifacts from optical signals, described by way of an exemplary spatial arrangement and temporal sampling configuration (sequence) in which:

Figure 5A illustrates the multi-channel sampling approach and accompanying nomenclature;

Figure 5B summarizes the spatial arrangement and temporal sampling configuration (sequence) used as example throughout the disclosure;

Figure 5C illustrates a complete sampling sequence including a sampling period comprising multiple sampling steps, and a non-sampling period; Figure 5D illustrates mathematical determination of a common absoiption point for each multi-channel sampling period.

DETAILED DESCRIPTION [0013] The following detailed description and appended drawings describe and illustrate various aspects of the present invention. The descriptions, embodiments and figures are not intended to limit the scope of the invention in any way.

[0014] Figure 1 is a conceptual illustration of the exemplary embodiment of the PPG-based physiological sensing system 1 comprising a wearable optical sensing device 2 preferably worn on, but not limited to, a user's 3 upper-arm, in communication with a remote electronic device 4 such as a smartphone (e.g. iPhone™) or equivalent device capable of receiving and processing optical signals transmitted from the wearable optical sensing device 2 and displaying outputs to the user via a user interface. An exemplary method of data transmission may be Bluetooth™, although other protocols may be employed. The remote electronic device 4 contains and executes a specialized developed software application configured to i) receive and process raw optical signals from the wearable optical sensing device 2 and ii) obtain, store and display robust and accurate physiological outputs, including, but not limited to, heart rate, to the user via a user interface. Optical signals received from the wearable optical sensing device 2 may also be used to obtain other physiological parameters including but not limited to breathing rate.

[0015] In an alternative embodiment of the invention, processing of raw optical signals may take place on the wearable optical sensing device 2, the final physiological outputs being transmitted to a remote electronic device 4 containing the appropriate software application to display physiological outputs to the user via the user interface. In another alternative embodiment of the invention, partial processing of raw optical signals may take place on the wearable optical sensing device 2, the partially processed signals being transmitted to a remote electronic device 4 containing the appropriate software application for final processing and display of physiological outputs to the user via the user interface. In yet another alternative embodiment of the invention, both processing of raw signals as well as display of physiological outputs to the user may take place on the wearable optical sensing device 2, in this processing configuration the wearable optical sensing device 2 comprising a suitable user interface.

[0016] Figure 2 is a conceptual illustration of the electronic components comprising the wearable optical sensing device 2 including but not limited to a microprocessor 9 coupled to a sensing unit 5, signal amplifier 6, low pass filter 7, analog-to-digital converter (ADC) 8, memory component 13, and transceiver 10. Communication, i.e., data transfer between the optical sensing device 2 and a remote electronic device 4, is supported by an antenna 11 coupled to the transceiver 10. The antenna 11 may be a wireless (e.g. Bluetooth™ or the like) connection or may be representative of a wired connection to the remote electronic device 4. All electronic components are coupled to and powered by a rechargeable battery 12 and housed in a waterproof casing (not shown). The optical sensing unit 5 under control of the microprocessor 9 generates an analog signal representative of the light intensity measured by the light detection module (described in Figure 4) which passes through a signal amplifier 6 and low pass filter 7. The conditioned analog signal is converted to a digital signal by an ADC 8 and prepared for transmission by a microprocessor 9. The raw optical signal is transmitted via the transceiver 10 and antenna 11 to a suitable remote electronic device (e.g. an iPhone™) for processing and output display.

[0017] Other functions of the microprocessor 9 may include determining whether the PPG signal peak values are too large, i.e., saturating, or too weak, i.e., resulting in poor signal-to-noise ratios. This level of gain control is achieved by the microprocessor 9 providing feedback to the optical sensing unit 5 via a digital-to-analog converter (DAC) (not shown). If the detected pulse peak values are too weak, the microprocessor 9 provides feedback to the optical sensing unit 5 via the DAC to increase in the intensity of the LEDs by increasing the electric current, or reducing the current if the signal is saturating. Adjusting the brightness of the LEDs to obtain a suitable signal is especially important since the normative values between user's may vary significantly based on skin color (melanin content), blood pressure, pulse strength and/or other changes that may occur during the course of a variable exercise regimen (e.g. change in ambient or body temperature). Furthermore, gain control contributes valuably to conserving battery power within the system.

[0018] Another function of the microprocessor 9 may include capturing the battery power level of the wearable optical sensing device 2, and if not displayed locally (e.g. via voice prompts, vibration alerts, other) transmitting the information to a remote electronic device 4 for display to the user via the user interface.

[0019] The requirement for a memory component 13 depends on the preferred processing configuration for the system, i.e., whether complete processing, partial processing or no processing whatsoever of raw optical signals takes place on the wearable optical sensing device 2. In the exemplary embodiment, all signal processing takes place on a remote electronic device 4 and therefore a memory component 13 is not a constraint to the design of the wearable optical sensing device 2. However, in an alternative embodiment with a processing configuration where any level of signal processing takes place on the wearable optical sensing device 2, a memory component 13 is essential to the design of the wearable optical sensing device 2.

[0020] Figure 3 is a conceptual illustration of the electronic components comprising the remote electronic device 4, including but not limited to a processor 16 coupled to a memory component 18, user interface 19 and a transceiver 14. Communication, i.e., data transfer between the remote electronic device 4 and the wearable optical sensing device 2, is supported by an antenna 22 coupled to the transceiver 14. The antenna 22 may be a wireless (e.g. Bluetooth™ or the like) connection or may be representative of a wired connection to the wearable optical sensing device 2. All electronic components are coupled to and powered by a rechargeable battery 17 and housed in a suitable casing as determined by the manufacturer. The remote electronic device 4 may comprise, for example, a smartphone such as an iPhone™ or equivalent device capable of receiving optical signals from the wearable optical sensing device 2 by executing a specialized developed software application (App) 15. In the exemplary embodiment, the remote electronic device 4 is executing a heart rate monitoring application configured to i) receive and process raw optical signals representative of blood volume change, i.e., pulse waves from the wearable optical sensing device 2, and ii) to obtain, store and display accurate and robust heart rate outputs to the user via the user interface 19.

[0021] Heart rate outputs displayed to the user via the user interface 19 of the remote electronic device 4 may be used, for example, to create an exercise schedule based on an individual's specific abilities and/or fitness goals. For example, to start a maximum estimated heart rate may be calculated based on factors including a user's age and fitness level, or determined empirically. The notion is to determine an ideal heart rate range for a specific fitness or performance goal. A maximum estimated heart rate may correspond to an extreme level of exertion, while different levels of exercise intensity may correspond to different ranges of heart rate spanning from the maximum estimated heart rate down to a range corresponding to a resting heart rate. In this way, a heart rate range may be established for different exercise intensities allowing a user to control and/or monitor his/her level of activity, track his/her progress, and reach his/her fitness goals more efficiently. Importantly, heart rate and other physiological outputs determined in this way are intended to serve as guidelines only, and are subject to appropriate modification and/or interpretation.

[0022] The wearable optical sensing device 2 contains an optical sensing unit 5 with a light-emitting and light-detecting module for measuring blood volume changes caused by expansion and contraction of the small blood vessels in the skin and underlying tissue during the cardiac cycle. Figure 4 illustrates the exemplary arrangement of the light-emitting and light-detecting modules comprising the optical sensing unit 5. In an exemplary embodiment, the light-emitting module consists of a set of four identical wavelength LEDs 20 arranged around a light-detecting module comprising a single photodiode 21 with a spectral sensitivity spanning that of light-emitting module. In alternative embodiments of the invention, the light-emitting module may comprise two or more distinct wavelengths and/or a higher plurality of light sources. Similarly, in an alternative embodiment of the invention, the light-detecting module may comprise a higher plurality of light sensors with a spectral sensitivity spanning that of the light-emitting module. The light-emitting and light-detecting modules are positioned in close enough proximity to each other and to the user's skin surface to allow accurate measurement of changes in blood volume at a single location on the user's body. The spatial arrangement and temporal sampling configuration (sequence) of the optical sensing unit 5 under control of the microprocessor 9 allows for a common absorption point to be determined mathematically for each multi-channel sampling step (described in Figure 5 below).

[0023] For the purpose of this disclosure, not to limit the scope of the invention in any way, an exemplary embodiment with a light-emitting module comprising four identical LEDs with a wavelength in the visible green spectrum (e.g., 525 nm) is described. Depending on the specific requirements of the system, a higher plurality of LEDs, and/or incorporating two or more distinct wavelengths in the measurement, may contribute additional information for subsequent analysis.

[0024] The spatio-temporal sampling approach employed towards identifying and removing motion artifacts from optical signals are described below with reference to Figure 5A-D. Multi-channel sampling by the optical sensing unit 5 comprising multiple LEDs 20 and a single common photodiode 21 is achieved by alternating sequential sampling of the LEDs under control of the microprocessor 9. An exemplary six-channel sampling configuration is illustrated in Figure 5A. The sampling period includes blanking periods at the onset (Blcl) and end (Blc2) of sampling. By measuring the light level when no LEDs are firing it is possible to determine, and compensate for, the effect of ambient light on the over-all sampling period. Following the onset blanking period (Blcl), the exemplary temporal sampling configuration (sequence) follows a 'diagonally-across' pattern starting at the top left (TL) position, and continuing to the bottom right (BR), bottom left (BL), and top right (TR) position. The sampling period is concluded with a blanking period (Blc2). This exemplary temporal sampling configuration (sequence) used as example throughout this disclosure is summarized in Figure 5B. Seven additional (eight in total) sampling configurations for which a common absorption point (see Figure 5D) can be determined exist within the scope of the exemplary embodiment and sampling sequence by simply rotating the 'diagonally-across' sampling sequence to different starting positions. Similarly, numerous sampling configurations (sequences) may be applied to alternative embodiments of the invention with a higher plurality of two or more distinct wavelength light sources towards achieving spatio-temporal sampling. Figure 5C serves to illustrate the complete sampling sequence of the exemplary sampling configuration including a sampling period comprising multiple sampling steps, and a non-sampling step designated for data preparation and transmission.

[0025] The physical design of the optical sensing unit 5 allows for near-instantaneous absorption measurement at different positions on the propagating pulse wave through rapid sequential sampling. The spatial arrangement together with the temporal sampling configuration (sequence) of the system allows for a common absorption point to be determined mathematically for each multichannel sampling period as illustrated in Figure 5D. The aim of the spatio-temporal sampling approach is to obtain an optical measurement at different positions of the propagating pulse wave at the same time, i.e., instantaneously. For example, an alternative approach to achieve the same goal would be to include a photodiode for each LED in the system, thereby permitting all LEDs to be fired and measured instantaneously. In doing so, unexpected behavior - i.e., unexpected based on known and/or deduced physiological constraints such as pulse wave velocity, heart rate acceleration and deceleration, etc. - such as motion artifacts corrupting the optical single, may be identified and removed more readily.

[0026] Spatio-temporal sampling is achieved by first assigning a common absorption point around which the optical measurements obtained at each sampling position on the propagating pulse wave is to be aligned. The common absorption point is assigned in such a way that it falls within the range spanned by the paired sampling points, e.g., TL-BL (top-bottom); TL-TR (left-right); BR-BL (right- left); BR-TR (bottom-top); Blcl -Blc2 (background). In the described example, the common absorption point is assigned to the middle of the sampling period comprising multiple sampling steps, however this need not always be case.

[0027] A known sampling time (t) and sampling point (0.5t) is further assigned to each sampling step. In the described example, the sampling point in assigned to the middle of the sampling step, however this need not always be the case. Given a known sampling time of t, the chosen temporal sampling configuration (sequence) allows for temporal alignment of absorbance values measured sequentially at different positions on the propagating pulse wave at the common absorption point. In this way, a temporally dependent estimate of the light absorbance values measured at different positions on the pulse wave, as well as the measurements obtained during the blanking periods, can be estimated at the same temporal point.

[0028] To explain, take the temporal alignment of the measured absorbance values obtained at the top-left (TL) and top-right (TR) positions: TL and TR are temporally aligned with respect to the common absorption point such that the sampling time before and the sampling time following the common absorption point is the same, and equal to 1.5t respectively. From this it follows that the 'top' temporally aligned absorption estimate may be obtained by averaging the absorption values obtained for the TL and TR positions respectively, i.e., the temporal coefficient for the temporally aligned 'top' absorbance estimate (a) is 0.5:

a = 0.5 (TL + TR)

[0029] The temporal coefficient is calculated by dividing the sampling time taken from the sampling point of the first relevant measurement position to the assigned common absorption point, by the total sampling time taken between the selected paired points. For example, for the temporal alignment of the measured absorbance values obtained at the TL and TR positions, the temporal coefficient is calculated as follows:

1.5t

Temporal coefficient = = 0.5

[0030] Similarly, the 'bottom' and 'blanking' temporally aligned absorbance estimates may be obtained by averaging (temporal coefficient of 0.5) the absorption values obtained at the bottom- right (BR) and bottom-left (BL) positions (b), and the blanking periods at the onset (Blcl) and end (Blc2) of sampling (c) respectively:

b = 0.5 (BR + BL)

c = 0.5 (Blcl + Blcl)

[0031] Although the same principle holds for the temporal alignment of absorbance values measured at the top-left (TL) and bottom-left (BL) positions, the alignment is asymmetrical in this case. To explain, TL and BL are temporally aligned relative to the common absorption point such that the sampling time before and the sampling time following the absorption estimation point is 1.5t and 0.5t respectively. From this it follows that the 'left' temporally aligned absorbance estimate (d) can be obtained with a temporal coefficient of 0. 75:

d = 0.75 (BL - TL) + TL [0032] Similarly, the 'right' temporally aligned absorbance estimate can be obtained from the absorption values measured at the bottom-right (BR) and top-right (TR) positions (e) with a temporal coefficient of 0.25:

e = 0.25 (TR - BR) + BR

[0033] Throughout the calculation of temporally aligned absorption estimates, the assigned sampling point (0.5t) of each sampling step is used as the point of measurement. Furthermore, the accuracy of this linear approximation of the absorbance values at the common absorption point is subject to the sampling time t approaching zero.

[0034] The temporally aligned absorption estimates may subsequently be incorporated in one or a combination of digital signal processing techniques (e.g. Kalman filter, Fourier analysis, peak identification, independent component analysis, other) towards identifying and removing motion artifacts from optical signals to obtain robust and accurate determination of physiological parameters. To this end, the temporally aligned 'top' (a), 'bottom' (b), 'left' (d) and 'right' (e) absorbance estimates may be applied separately, or averaged to obtain a spatially aligned absorbance estimate. The temporally aligned 'blanking' (c) absorbance estimate is applied to compensate the effect of ambient light, either during the individual sampling steps, or the overall sampling period.

[0035] In addition, the processed optical signals can be used to determine, but are not limited to the determination of, real time oxygen consumption (V0₂) and metrics gauging strenuousness of exercise such as, but not limited to, excess post-exercise oxygen consumption (EPOC, informally referred to as afterburn). Naturally, several additional physiologically relevant metrics such as, but not limited to, (i) exercise cadence, (ii) optimal exercise cadence, (iii) total oxygen consumption normalized to movement, (iv) EPOC normalized to movement, (v) V0₂max, (vi) orthostatic heart rate testing to gauge overtraining, (vii) heart rate variability, (viii) calorie usage and (ix) blood lactate concentration can be determined (with or without the use of an accelerometer or other movement sensing technology). The obtained information is intended to serve as guideline(s) towards a user's specific fitness and/or sport performance goals.

[0036] Having thus described exemplary embodiments of the present invention, those skilled in the art will appreciate that the within disclosures are exemplary only and that various other alternatives, adaptations, and modifications may be made within the scope of the present invention. Accordingly, the present invention is not limited to the specific embodiments as illustrated herein, but is only limited by the following claims.

Claims

1. An optical sensing device capable of transcutaneous measurement of a user, comprising:

a light-emitting module in proximity to the user's skin, the light-emitting module comprising a plurality of light sources with distinct wavelengths, at least one of the plurality of light sources having a wavelength in the green spectrum, and at least a second of the plurality of light sources having a second wavelength greater than 740 nm; and

a light-detecting module in proximity to the user's skin and to the light-emitting module, for detecting light originating from the light-emitting module and reflecting off of the user's skin.

2. The optical sensing device of claim 1 , wherein the second wavelength is greater than 740 nm.

3. The optical sensing device of claim 1 , wherein the second wavelength is at the isobestic point of oxy- and deoxy-hemoglobin.

4. The optical sensing device of claim 1 , wherein the light-detecting module measures light absorption related to physiological parameters of the user.

5. The optical sensing device of claim 1 , wherein the light-emitting module is arranged such that at least a portion of the emitted light penetrates the user's skin.

6. The optical sensing device of claim 1 , further comprising a processor coupled to the light- emitting module to:

disable the plurality of light sources during a first time period;

enable each of the plurality of light sources in sequence, one at a time; and disable the plurality of light sources during a final time period.

7. The optical sensing device of claim 6, further comprising a processor configured to compute physiological parameters using information from the light-detecting module obtained during the first and final time periods, to compensate information from the light-detecting module obtained during the time periods.

8. The optical sensing device of claim 1 , arranged so as to detect at least a portion of backscatter from the light that penetrates the user's skin from the light-emitting module, wherein at least one of the plurality of light sensors has a spectral sensitivity spanning that of the light-emitting module.

9. The optical sensing device of claim 1 , further comprising a processor coupled to the light- detecting module, wherein the processor employs a spatio-temporal sampling approach towards identifying and removing motion artifacts from the detected light representative of light-absorption related physiological parameters, the processor performing the steps of: receiving optical signals from the light detecting module;

processing the optical signals to obtain temporally aligned values;

incorporating temporally aligned and/or non- temporally aligned values in at least one digital signal processing technique; and

computing at least one relevant physiological parameter based on the at least one digital signal processing technique.

10. An optical sensing device capable of transcutaneous measurement of a user, comprising:

a light-emitting module in proximity to the user's skin, the light-emitting module comprising a plurality of light sources with distinct wavelengths, at least one of the plurality of light sources having a first wavelength, and at least a second of the plurality of light sources having a second wavelength; and

11. A method for transcutaneous measurement of a user, comprising the steps of: providing a light-emitting module in proximity to the user's skin, the light-emitting module comprising a plurality of light sources with distinct wavelengths, at least one of the plurality of light sources having a wavelength in the green spectrum, and at least a second of the plurality of light sources having a second wavelength greater than 740 nm; and

providing a light-detecting module in proximity to the user's skin and to the light- emitting module, for detecting light originating from the light-emitting module and reflecting off of the user's skin.

12. The method of claim 1 1 , further comprising the step of estimating oxygen uptake (V02) by calculating oxygen uptake (V02) from optically determined heart rate and/or breathing rate values

13. The method of claim 1 1 , further comprising the step of estimating oxygen uptake (V02) by calculating oxygen uptake (V02) from optically determined heart rate and/or breathing rate values and motion sensing data.

14. The method of claim 11, further comprising the steps of estimating excess post-exercise oxygen consumption (EPOC) by:

calculating oxygen uptake (V02) from optically determined heart rate and/or breathing rate values; and

calculating excess post-exercise oxygen consumption from oxygen uptake (V02).

15. The method of claim 1 1, further comprising the steps of estimating excess post-exercise oxygen consumption (EPOC) by:

calculating oxygen uptake (V02) from optically determined heart rate and/or breathing rate values and motion sensing data; and

calculating excess post-exercise oxygen consumption from oxygen uptake (V02).

16. The method of claim 1 1 , further comprising the step of estimating excess post-exercise oxygen consumption (EPOC) by calculating excess post-exercise oxygen consumption from oxygen uptake (V02).

17. The method of claim 1 1 , further comprising the steps of estimating energy expenditure by:

calculating energy expenditure from oxygen uptake (V02).

18. The method of claim 1 1 , further comprising the steps of estimating energy expenditure by:

calculating oxygen uptake (V02) from optically determined heart rate and/or breathing rate values and/or motion sensing data; and

calculating energy expenditure from oxygen uptake (V02) and/or motion sensing data.

19. The method of claim 1 1 , further comprising the step of estimating energy expenditure by:

calculating energy expenditure from oxygen uptake (V02).

20. The method of claim 1 1 , further comprising the step of estimating energy expenditure by:

calculating energy expenditure from optically determined heart rate and/or breathing rate values

21. The method of claim 1 1 , further comprising the step of estimating energy expenditure by:

calculating energy expenditure from optically determined heart rate and/or breathing rate values and/or motion sensing data.

22. The method of claim 1 1 , further comprising the steps of estimating blood lactate concentration by:

calculating oxygen uptake (V02) from optically determined heart rate and/or breathing rate values;

calculating excess post-exercise oxygen consumption from oxygen uptake (V02); and estimating blood lactate concentration from excess post-exercise oxygen consumption prediction.

23. The method of claim 1 1 , further comprising the steps of identifying and removing motion artifacts representative of light-absorption related physiological parameters, by:

generating an optical signal from the light-detecting module, configured to enable spatio-temporal sampling;

processing the optical signal to obtain temporally aligned values;

incorporating the temporally aligned and/or non-temporally aligned values in at least one digital signal processing technique; and

computing relevant physiological parameter from the at least one digital signal processing technique.

24. The method of claim 1 1 , further comprising the steps of identifying cadence, by:

generating an optical from the light-detecting unit, configured to enable spatio- temporal sampling;

processing the optical signal to obtain temporally aligned and non-temporally aligned values;

incorporating the temporally aligned values in at least one digital signal processing technique; and

computing cadence from the at least one digital signal processing technique.