Method and apparatus for sensor tightness detection

Abstract

A system determines tightness of a wearable device (100). The system may include at least one processor configured to receive a photoplethysmography (PPG) signal from a wearable device. The at least one processor may determine a tightness measure from the PPG signal, such as from a segment of the PPG signal. The at least one processor may determine the tightness of the wearable device based on the tightness measure.

Description

METHOD AND APPARATUS FOR SENSOR TIGHTNESS DETECTION1 CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of United States Provisional Patent Application No. 63 / 511,309, filed 30 June 2023, the entire content of which is incorporated herein by reference.2 BACKGROUND OF THE TECHNOLOGY2.1 FIELD OF THE TECHNOLOGY

[0002] The present technology relates to determining tightness of fit of a wearable device worn by a user or a tight application of the wearable device to the user. In particular, the present technology relates to detecting inappropriate tightness of the wearable device based on signal measurement such as with respect to light measurement of photoplethysmography (PPG) sensors.2.2 DESCRIPTION OF THE RELATED ART

[0003] Wearable devices, such as such as smartwatches, activity trackers and finger probes, can help assess physiological parameters and / or conditions of users. For instance, wearable PPG devices can monitor pulse rate (PR), oxygen saturation (SpO2), peripheral arterial tone, blood pressure and / or blood vessel stiffness, and may be implemented for detection of sleep related events of the users.

[0004] It is important for the user to wear the PPG device with a suitable fit that is not too tight and not too loose, as the contact pressure between the PPG device and the user may negatively affect PPG signal quality. Excessive contact pressure, as in the case of overtightness, may block bloodstream and lower perfusion of peripheral arteries, causing artery stiffness and venous blood pooling. As a result, excessive contact pressure may distort PPG waveforms, lower AC signal amplitudes in the PPG waveforms, and reduce the signal to noise ratio, which, in turn, may reduce measurement accuracy (such as of SpCh measurements), and may, for example, delay screening or diagnoses.

[0005] On the other hand, insufficient contact pressure, as in the case of over-looseness, may result in an inadequate contact. The distance or angle between the PPG device and the user’s skin may scatter light, which, in turn, may reduce signal accuracy. The further away the PPG device from the user’s skin, the more signal noise may be introduced into the measurements.

[0006] Both reflective and transmissive PPG devices may be affected by the contact pressure. For instance, in the case of the reflective PPG device, the contact pressure may affect the PPG waveform morphology. In the case of the transmissive PPG device, excessive contact pressure may alter the measured blood samples because of severe blood flow restriction.

[0007] The optimum contact pressure varies markedly among individuals due to differences in skin elasticity and blood-vessel compliance. Despite numerous attempts, no generally accepted standards for clinical or fundamental PPG measurements to account or mitigate for unsuitable contact pressure have been adopted.

[0008] In view of the foregoing, there is a need to develop a solution that automates detection of fit or tightness of the wearable device, and which may be used to timely inform the user of when and / or how to adjust the fit or tightness of the sensing device. Further, to improve the overall accuracy of the physiological condition evaluation, there is a need to identify, filter and / or eliminate PPG signals that are affected by inappropriate tightness of the wearable device.3 BRIEF SUMMARY OF THE TECHNOLOGY

[0009] The present technology is directed towards systems and methods for determining tightness of a wearable device, such as determining inappropriate fit or tightness of the wearable device.

[0010] A first aspect of the present technology relates to a system for determining tightness of a wearable device.

[0011] A second aspect of the present technology relates to a method for determining tightness of a wearable device.

[0012] Some implementations of the present technology may include a system for determining tightness of a wearable device. The system, may include at least one processor. The at least one processor may be configured to receive a photoplethysmography (PPG) signal from a wearable device. The at least one processor may be configured to determine a tightness measure from the PPG signal, the tightness measure indicating the tightness of the wearable device.

[0013] In some implementations, the tightness measure may be determined from a detected segment of the PPG signal. The detected segment may include any of a detected peak and / or a detected trough. The tightness measure may be associated with an area formed between a computed curve and the detected segment of the PPG signal. The computed curvemay intersect the detected segment at two end points of the detected segment. The tightness measure may be determined based on a first parameter associated with a distance measure between the computed curve and the detected segment. The tightness measure may be determined based on a second parameter indicating presence of a concave characteristic in the detected segment.

[0014] In some implementations, the at least one processor may be configured to determine the first parameter and the second parameter for each detected segment of the PPG signal. The at least one processor may be configured to determine a moving median of the determined first and second parameters. The at least one processor may be configured to determine the tightness measure based on the moving median. The at least one processor may be configured to determine the first parameter by calculating a plurality of distances between a plurality of sample points on the computed curve and corresponding sample points on the detected segment. The at least one processor may be configured to determine the first parameter by also determining the first parameter by calculating an average of 50% of smallest distances of the plurality of distances. The at least one processor may be configured to determine the second parameter by calculating a plurality of second derivatives for a plurality of sample points on a curve between a trough and a peak in the detected segment, the trough preceding the peak. The at least one processor may be configured to determine the first parameter by also determining the second parameter by determining a percentage of the calculated plurality of second derivatives that have a negative value.

[0015] In some implementations, the at least one processor may be configured to determine validity of the PPG signal based on the tightness measure. The at least one processor may be configured to determine the validity of the PPG signal based on the tightness measure and low perfusion detection. The at least one processor may be configured to: compare the tightness measure to a threshold; and determine that the PPG signal may be valid when the tightness measure may be less than or equal to the threshold. The at least one processor may be configured to: identify a period of time in the PPG signal during which the tightness measure exceeds a threshold; and derive a peripheral arterial tonometry signal from the PPG signal, outside of the identified period of time, to detect an occurrence of a sleep-related event. The at least one processor may be configured to: determine whether the PPG signal may be valid by comparing the tightness measure to a first threshold; and after determining that the PPG signal may be valid, determine whether to exclude any period of time from the PPG signal forderiving a peripheral arterial tonometry signal to detect an occurrence of a sleep-related event by comparing the tightness measure corresponding to the period of time to a second threshold. The second threshold may be lower than the first threshold. The at least one processor may be configured to determine that the PPG signal may be valid when the tightness measure may be less than or equal to the first threshold. The at least one processor may be configured to exclude the period of time from the PPG signal for deriving the peripheral arterial tonometry signal when the tightness measure exceeds the second threshold.

[0016] In some implementations, the detected segment may be a segment of the PPG signal between two adjacent troughs. The PPG signal may be measured at a finger. The wearable device may include a PPG sensor configured to generate the PPG signal. The PPG sensor may include an infrared sensor and / or a red-light sensor. The at least one processor may be configured to receive the PPG signal from the wearable device via a wireless connection. The system may further may include the wearable device. The at least one processor may be configured to generate an output indicating the tightness of the wearable device.

[0017] Some implementations of the present technology may include a method for determining tightness of a wearable device. The method may include receiving, by at least one processor, a photoplethysmography (PPG) signal from a wearable device. The method may include determining, by the at least one processor, a tightness measure from the PPG signal, the tightness measure indicating the tightness of the wearable device.

[0018] In some implementations, the tightness measure may be determined from a detected segment of the PPG signal. The detected segment may include any of: a detected peak and / or a detected trough. The tightness measure may be associated with an area formed between a computed curve and the detected segment of the PPG signal. The computed curve may intersect the detected segment at two end points of the detected segment. The determining the tightness measure may include determining a first parameter associated with a distance measure between the computed curve and the detected segment. The determining the tightness measure may include determining a second parameter indicating presence of a concave in the detected segment. The method may further include determining the first parameter and the second parameter for each detected segment of the PPG signal. The method may further include determining a moving median of the determined first and second parameters. The method may further include determining the tightness measure based on the moving median.

[0019] In some implementations, the determining the first parameter may include: calculating a plurality of distances between a plurality of sample points on the computed curve and corresponding sample points on the detected segment; and determining the first parameter by calculating an average of 50% of smallest distances of the plurality of distances. The determining the second parameter may include calculating a plurality of second derivatives for a plurality of sample points on a curve between a trough and a peak in the detected segment, the trough preceding the peak; and determining the second parameter by determining a percentage of the calculated second derivatives that have a negative value. The method may further include determining validity of the PPG signal based on the tightness measure. The determining validity may include determining validity of the PPG signal based on the tightness measure and low perfusion detection. The method may further include comparing the tightness measure to a threshold. The method may further include determining that the PPG signal may be valid when the tightness measure may be less than or equal to the threshold. The method may further include identifying a period of time in the PPG signal during which the tightness measure exceeds a threshold. The method may further include deriving a peripheral arterial tonometry signal from the PPG signal, outside of the identified period of time, to detect an occurrence of a sleep-related event. The method may further include determining whether the PPG signal may be valid by comparing the tightness measure to a first threshold The method may further include, after determining that the PPG signal may be valid, determining whether to exclude any period of time from the PPG signal for deriving a peripheral arterial tonometry signal to detect an occurrence of a sleep-related event by comparing the tightness measure corresponding to the period of time to a second threshold, wherein the second threshold may be lower than the first threshold.

[0020] In some implementations, the method may further include determining that the PPG signal may be valid when the tightness measure may be less than or equal to the first threshold. The method may further include excluding the period of time from the PPG signal for deriving the peripheral arterial tonometry signal when the tightness measure corresponding to the period of time exceeds the second threshold. The detected segment may be a segment of the PPG signal between two adjacent troughs. The method may further include measuring the PPG signal at a finger. The wearable device may include a PPG sensor configured to generate the PPG signal. The PPG sensor may include an infrared sensor and / or a red-light sensor. The receiving the PPG signal may include receiving the PPG signal from the wearabledevice via a wireless connection. The method may further include generating an output indicating the tightness of the wearable device.

[0021] Some implementations of the present technology may include a processor- readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors to perform any one or more of the aforementioned aspects of the method previously described or described herein.

[0022] Some implementations of the present technology may include a processor- readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors to determine tightness of a wearable device. The processor-executable instructions may include instructions to receive, by the one or more processors, a photoplethysmography (PPG) signal from a wearable device. The processor-executable instructions may include instructions to determine, by the one or more processors, a tightness measure from the PPG signal, the tightness measure indicating the tightness of the wearable device.

[0023] Of course, portions of the aspects may form sub-aspects of the present technology. Also, various ones of the sub-aspects and / or aspects may be combined in various manners and also constitute additional aspects or sub-aspects of the present technology.

[0024] Other features of the technology will be apparent from consideration of the information contained in the following detailed description, abstract, drawings and claims.4 BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The present technology is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings, in which like reference numerals refer to similar elements including:

[0026] FIG. 1 illustrates an example wearable device, according to one aspect of the present technology, which may be implemented as for coupling to a finger of a user or other suitable body contact position (e.g., wrist).

[0027] FIG. 2 illustrates an example PPG waveform, according to one aspect of the present technology.

[0028] FIG. 3 illustrates the example wearable device positioned to measure signals at a user’s finger, according to one aspect of the present technology.

[0029] FIG. 4A is a hypothetical illustration of a segment of a PPG signal, without a diastolic peak, that may be collected by the wearable device that may be deemed to be detected during an acceptable fit, according to one aspect of the present technology.

[0030] FIG. 4B illustrates a segment of a PPG signal, with a clear diastolic peak, as collected by the wearable device with acceptable fit, according to one aspect of the present technology.

[0031] FIG. 4C illustrates a segment of a PPG signal as collected by the wearable device with increased tightness, according to one aspect of the present technology.

[0032] FIG. 4D illustrates another segment of a PPG signal as collected by the wearable device with increased tightness, according to one aspect of the present technology.

[0033] FIG. 5 illustrates example components of the wearable device and a system for determining tightness of the wearable device, according to one aspect of the present technology.

[0034] FIG. 6 illustrates an example process for determining tightness of the wearable device, according to one aspect of the present technology.

[0035] FIG. 7 illustrates a segment of a PPG signal with a computationally modelled straight line determined from and connecting between a detected trough and a detected peak of a sensor signal, according to examples of the present technology.

[0036] FIG. 8 illustrates an example flow chart for a method for determining tightness of the wearable device, according to one aspect of the present technology.5 DETAILED DESCRIPTION OF EXAMPLES OF THE TECHNOLOGY

[0037] Before the present technology is described in further detail, it is to be understood that the technology is not limited to the particular examples described herein, which may vary. It is also to be understood that the terminology used in this disclosure is for the purpose of describing only the particular examples discussed herein, and is not intended to be limiting.

[0038] The following description is provided in relation to various examples which may share one or more common characteristics and / or features. It is to be understood that one or more features of any examples may be combinable with one or more features of another example or other examples. In addition, any single feature or combination of features in any of the examples may constitute a further example.5.1 WEARABLE DEVICE 100

[0039] FIG. 1 illustrates an example wearable device 100 according to the present disclosure. When worn by a user 101, the device 100 may record data associated with the user. In examples, the device 100 may be worn by the user during sleep so as to record signals indicative of sleep related events.

[0040] The device 100 may include a button or switch 102 to activate or power on and off the device 100, and a sensor 104 to record data associated with the user. In examples, both the switch 102 and the sensor 104 may be disposed on a contact surface 106 of a housing of the device. The contact surface 106 may represent a sensing side of the device 100. Further, the device 100 may include a non-contact surface 108 opposite to the contact surface 106. The contact surface 106 and the non-contact surface 108 may face opposite directions. When the device 100 is worn correctly by the user, the contact surface 106 and the sensor 104 may be in direct contact with the user’s skin, such as finger, brachia, nostril, head, forehead, mouth, toe, wrist, ankle, torso, esophageal region, and ear (e.g., in-ear, earlobe, external ear cartilage, superior auricular region), among other possibilities, while the non-contact surface may face away from the user’s skin. The device 100 may be held against the contact portion of a user with a holding device such as a strap, ring, thimble, glove, bandage, band, belt, clip or other comparable sensor applicator.

[0041] The sensor 104 may include a PPG sensor configured to generate a PPG signal. The PPG sensor may include a light source and a detector. The light source may be configured to emit light. The light source may emit light of different wavelengths and intensities, including but not limited to green, red, blue and infrared-lights. The light source may include one or more light-emitting diodes (LEDs). The detector may be configured to detect reflections of light from the user’s tissue, and obtain reflectance-based PPG signals. In examples, the amplitude of a PPG signal may change depending on the blood volume of the user’s tissue. The blood volume in arteries may be greater during the systolic phase than the diastolic phase of the cardiac cycle. Changes in the PPG signal amplitude may indicate changes in the blood-flow volume based on the intensity of reflected light.

[0042] In examples, the PPG sensor may include one or more light sensors such as any of the following: an infrared sensor and / or a red-light sensor, among other possibilities.5.1.1 Example PPG Waveform

[0043] FIG. 2 illustrates an example PPG waveform of a PPG signal detected by the sensor 104, when the device 100 is correctly positioned on the user. The PPG waveform may include one or more pulses. Each pulse may have a pulse wave duration dl. The pulse wave duration dl may correspond to a cardiac cycle, including a systolic phase pl of the cardiac cycle and a diastolic phases p2 of the cardiac cycle. The pulse may have a systolic peak ml and a diastolic peak m2.

[0044] As shown in FIG. 2, the PPG signal may have a direct current (DC) component representing a steady part of the PPG signal, and an alternating current (AC) component representing a pulsatile part of the PPG signal. The DC component may correspond to the reflected optical signal from the user’s tissue. The DC component may depend on the structure of the user’s tissue, and may also depend on the average volume of both the arterial and venous blood. The DC component may change slowly with respiration. The AC component may fluctuate according to changes in the blood volume that occur between the systolic and diastolic phases of the cardiac cycle. The fundamental frequency of the AC component may depend on the heart rate (HR) and may be superimposed onto the DC component. The AC value may correspond to a vertical distance between the peak ml and a baseline bl where the troughs tl and t2 reside. The amplitude of the troughs tl, t2 may represent the base value or the DC value of the PPG signal.

[0045] A trough-to-trough segment is a segment of the PPG signal between two adjacent troughs, or otherwise consecutive troughs, such as between troughs tl and t2. As discussed in more detail herein, segments of the signal for analysis may also be evaluated in relation to other features such as peaks. Thus, a segment may be a peak-to-peak segment, or a peak-to-trough segment, for example.5.1.2 Acceptable vs. Tight Fit

[0046] FIG. 3 illustrates an application of the example device 100 to measure a PPG signal at the user’s finger. The device 100 may be secured to the user 101 via a bandage or tape 109. If the bandage 109 or strap that secures the device 100 too tightly to the user (e.g., finger), bloodstream is impeded or blocked in the finger, distorting PPG morphology and reducing PPG signal quality. Such a contact restriction between the skin contact region and the sensor may also create sensing interference with respect to the performance of the light receiver and / or emitter of the sensor.

[0047] FIGS. 4A-D illustrate distinctions in PPG morphology between acceptable fit and undesirable tight fit of the device 100. FIGS. 4A-B each illustrate a segment of a PPG signal as collected by the wearable device with acceptable fit or acceptable tightness. The PPG segment in FIG. 4A does not have a diastolic peak, whereas the PPG segment in FIG. 4B has a clear diastolic peak in a segment region showing a convex curvature CC (i.e., when considered from the perspective of the x axis of the graph). Aging or other pathological factors that increase arterial stiffness and / or reduce skin elasticity can reduce the diastolic peak. However, unacceptable sensor fit or tightness can also cause any of venous blood pooling, decreased / lowered perfusion and reduced peaks in the signal or obscured diastolic peaks. Sensor tightness can technically have the same effect as aging / pathologies in the sense that it ‘artificially’ produces the effect of increases in arterial stiffness, which therefore can decrease or lower perfusion, or reduce peaks in the signal or obscure diastolic peaks. Apart from that it can also result in venous blood pooling. FIGS. 4C-D each illustrate a segment of a PPG signal as collected by the wearable device with increased tightness.

[0048] Increased tightness may distort or skew time domain signals or otherwise obscure typical signal morphology. Systolic peaks as shown in FIGS. 4C-D may be narrower than those shown in FIGS. 4A-B. Each trough-to-trough segment as shown in FIGS. 4C-D may exhibit a more square shape. As shown in FIGS. 4C-D, increased tightness may result in merging of diastolic and systolic peaks, creating concave segments or segments approaching concavity (when again considered from the perspective of the x axis of the graph), in the PPG waveform as illustrated. For example, as the tightness increases, each trough-to-trough segment may include a section that becomes more of a concave shape or less of the type of convex shape. The convex or concave shape can be attributable to a whole trough-to-trough segment or at least to the trough-to-peak segment, or other smaller segment portion as discussed in more detail herein and, in some cases may be attributable to, for example, a diastolic peak as shown in FIG. 4B. In addition, as shown in FIGS. 4C-D, increased tightness may negatively impact perfusion and reduce the signal to noise ratio.

[0049] In examples described in more detail herein, any PPG signal, such as from a sleep or screening / diagnostic session or portions thereof, collected at a time when the device 100 is excessively tight on the user may be detected, such as based on morphology in relation to detected segment(s) such as using points between certain signal samples (e.g., end points), that may be points associated with trough(s) and / or peak(s), etc., and an evaluated curvature of the detected segment(s). Such detected segments may be between troughs and / or peaks (e.g., apeak-to-trough segment, a trough-to-trough segment, a peak-to-peak segment, trough-to-peak segment, etc.), Based on such detection and evaluation, the PPG signal, or portions thereof, may be labelled or deemed invalid due to tightness.5.1.3 Components of Wearable Device

[0050] Referring to FIG. 5, aside from the sensor 104 mentioned earlier, the device 100 may include one or more of the following: an accelerometer 110 configured to generate an accelerometer signal, memory 112, one or more processors 114 and a network interface 116.

[0051] The network interface 116 may transmit data, such as data recorded by the sensor 104 and the accelerometer 110, to a system 200 for further analysis. Detailed discussion of the system 200 is provided below.5.2 SYSTEM 200

[0052] The system 200 may determine tightness of the device 100. For example, the system 200 may detect whether the fit between the device 100 and the user 101 is acceptable, based on data provided by the device 100. The system 200 may estimate tightness based on PPG signal morphology.

[0053] The system 200 may include memory 212, one or more processors 214 and a network interface 216. The memory 212 may store data received from the device 100, including but not limited to, the PPG signal, and optionally the accelerometer signal. The memory 212 may also store data derived from the PPG and / or accelerometer signals. Such derived data may include, for example, artifacts and activity data. The memory 212 may include computer program code configured to cause the processor(s) 214 to perform one or more functions such as physiological condition evaluation 220, low perfusion detection 222, and tightness determination 224. Detailed discussion of each function is described below. Although such functions are generally described herein in relation to particular processors of either the device 100 or the system 200, it will be understood that in some implementations, any or each of the functions described herein may be performed in any one or more of these processors such as when a memory associated with such a processor includes the program code for such a processor to perform the function(s). For example, any or all of the operations / steps of the functions performed by the processor(s) 214 as described herein may be performed by the processor(s) 114 and vice versa.5.2.1 Physiological Condition Evaluation 220

[0054] In examples, the processor(s) such as processor(s) 214 may process the PPG signal to evaluate the physiological condition of the user 101. From the PPG signal, the processor(s) 214 may derive SpCh, pulse rate (PR), changes in peripheral arterial tone and other similar parameters from the signal. Such an evaluation may include a presentation of the derived parameter(s) from the signal, such as showing the parameter or one or more values thereof as it changes over time so that the user can observe his / her physiological condition. Still further, the evaluation may optionally involve the processor analyzing such parameters such as to determine the concurrence of drops in SpCh, surges in pulse rate, and increases in peripheral arterial tone. Thus, the processor(s) 214 may, for example, based on the peripheral arterial tone, also detect an occurrence of a sleep-related event of the user so that user can be presented with other information about his / her physiological condition. The sleep-related event may include, but not limited to, a sleep-disordered breathing event such as an apnea and / or hypopnea event, snoring, or a limb movement.

[0055] Before using the PPG signal to evaluate the physiological condition of the user 101, the processor(s) 214 may determine whether the PPG signal is valid. Such determination may include determining whether the PPG signal, as a whole or one or more portions thereof, is valid. In examples, validity of the PPG signal may be assessed based on low perfusion detection 222 and / or tightness determination 224. For example, if the PPG signal is collected at a time when the device 100 is excessively tight on the user, the PPG signal, or the portion of the PPG signal corresponding to the period of time when the device 100 is excessively tight on the user, may be deemed as invalid for purposes of elevating the physiological conditions of the user 101.

[0056] In examples, the system 200 and / or the processor(s) 214 do not need to perform evaluation of the physiological condition of the user 101. Rather, an external system may perform such evaluation. The system 200 may provide results of low perfusion detection 222 and / or tightness determination 224 of the device 100 to the external system. For example, if the system 200 informs the external system that the device 100 is excessively tight at the time when the PPG signal is detected by the device 100, the external system may discard such PPG signal, or portions thereof, when evaluating the physiological condition of the user 101. In some versions, a processor 114 of the device 100 may perform a tightness determination 224 of the wearing of the device 100 and activate a signal of the device, such as an unacceptable tightness indicator light or an acceptable tightness indicator light on the device 100, based onthe determination, to provide the user with an indication of proper fit or improper fit such as to suggest a need for change in fit or tightness. Optionally, such an indication (e.g., by a light and / or on a display) may be on an output component or user interface of the system 200 or other external system, based on a determination of any of the processors, such as the processor 214. Thus, an electronic message (audio and / or visual) may be generated by a processor described herein and provided to the user based on a tightness detection described herein to advise the user to adjust the tightness of the fit of the sensor to improve the measurement process with the sensor.5.2.2 Low Perfusion Detection 222

[0057] For example, to help assess validity of the PPG signal, the processor(s) 214 may determine if the PPG signal includes any low perfusion segment. In particular, the processor(s) 214 may determine a perfusion measure with respect to each peak (e.g., peak amplitude) of the PPG signal. If the perfusion measure falls below a predetermined threshold, then the corresponding segment in the PPG signal may be deemed as a low perfusion segment. Such a threshold may be determined empirically and may optionally be chosen to represent an unrealistic perfusion level such that it may be attributed to restriction from over tightness of the sensor band, strap, ring, thimble, glove, or belt, or other applicator / holding device described herein. In examples, the predetermined threshold may, for example, have a numerical value, such as 750. The numerical value may be any other value(s) depending on chosen scale, and may be based on empirical data.

[0058] In examples, the perfusion measure may be determined based on the prominence of a peak (e.g., peak amplitude) of the PPG signal. The prominence of the peak may indicate how much a peak stands out from the surrounding baseline of the PPG signal due to its intrinsic height and its location relative to other peaks. The prominence of the peak may be defined as the vertical distance between the peak and its lowest contour line. The lower the prominence, the lower the perfusion. Low prominences may indicate that peaks are less pronounced. The prominence may be represented by one or more of the following: a peak amplitude of the PPG signal, an AC value of the peak of the PPG signal, a peak-to-base ratio of the PPG signal, a ratio between AC and DC values of the peak of the PPG signal. As such, the perfusion measure may be determined by calculating one or more of the following: a peak amplitude of the PPG signal, an AC value of the peak of the PPG signal, a peak-to-base ratio of the PPG signal, and a ratio between AC and DC values of the peak of the PPG signal.

[0059] In another example, the perfusion measure may refer to a median prominence of a plurality of peaks of the PPG signal determined from one or more of the following: a median peak amplitude of the PPG signal, a median AC value of the PPG signal, a median peak-to- base ratio of the PPG signal, and a median ratio between AC and DC values of the PPG signal. If the median perfusion is less than the predetermined threshold, then the corresponding segment in the PPG signal may be deemed as a low perfusion segment.

[0060] In examples, the low perfusion segment based on any of such detection techniques of the PPG signal may be marked or deemed as invalid, and may be excluded from the physiological condition evaluation 220. Optionally, the low perfusion segment may be marked as a low perfusion segment. In some tightness determination implementations as described herein, such an indication or marking of a portion of a signal as having low perfusion may serve as a basis for omitting such signals from further analysis. For example, a tightness determination as described herein may be determined with portions of the signal that are not marked / determined as having low perfusion. Such a low perfusion determination may be an indication of low signal quality for purposes of making a tightness detection. Thus, in some implementations, portions of the signal with low perfusion may be omitted from a tightness analysis or other tightness measure determination.

[0061] In some implementations, such a low perfusion indication may be taken or implemented by the processor as an indication of sensor fit, such as in the case that the patient is not a person of reduced peripheral blood flow. For example, a low perfusion detection may be implemented for generating an output indication of unacceptable fit or tightness whereas an acceptable perfusion (e.g., not low / below a threshold) may be implemented for generating an output indication of acceptable fit or tightness. Such a determination may be combined with other measures herein for evaluating the validity of the signal determined with the sensor.5.2.3 Other Tightness Determination 224

[0062] Additionally, any of the processors, such as the processor 114 and / or he processor(s) 214 may generate an estimate of a tightness measure such as with respect to each peak (e.g., peak amplitude) in the PPG signal. The tightness measure may also indicate the tightness or fit of the device 100 on the user. FIG. 6 illustrates an example process for determining tightness. In some such implementations, each peak or evaluated segment may be marked according to its tightness measure. Such a measure may be based on a concavity / convexity detection of a portion of the signal. Such a measure may be assessed for discarding / rejecting portions of the signal and / or for discarding / rejecting the entirety of thesignal, such as in relation to one or more comparisons of the measure with one or more thresholds. In some implementations, the measure may represent or relate to the signal of essentially the whole of measurement session or the measure may represent or relate to a discrete portion of the signal. In the case of the measure concerning merely a discrete portion, the assessment may result in discarding of the portion from further physiological analysis. In the case of the measure concerning essentially the whole of the signal, such as a summary (e.g., average) of some or all of the discrete portions, the assessment may result in discarding of the whole of the signal or the portions related to the summary. In some implementations, an assessment of a measure from a portion of the signal may be taken as an indication to discard the whole of the signal. An example of such a process may be considered in relation to the evaluation illustrated in FIG. 6. Otherwise, the measure(s) may be, or may be also, utilized to generate a warning message to a user to adjust fit of the device, such as by assessing the measure(s) (e.g., comparing the measure(s) to one or more thresholds), which may concern a message to inform the user to decrease tightness or a message to inform the user to increase tightness.5.2.3.1 Define Segments

[0063] For example, in relation to the process of FIG. 6, at step 602, the processor(s) 214 may detect or identify one or more segments as previously mentioned, such as trough-to-trough segments or peak-to-trough segments, etc., in the PPG signal. For example, a segment that is a trough-to-trough segment may include two troughs and one peak. FIG. 7 shows a first trough- to-trough segment that is between troughs t3 and t4, and a second trough-to-trough segment that is between troughs t4 and t5. Such segment detections may be made, for example, by processing of the samples of the signal to detect local minima and maxima in portions of the sensor signal, such as any of the light signals (e.g., red or infrared) from the sensor. It is noted that FIG. 7 illustrates a signal analysis with a measured signal that is shown with the samples of the signal negated (e.g., multiplied by negative one) for the concavity / convexity analysis, which may be carried out as such simply for convenience. In such a case, the typical peaks of the PPG signal appear as troughs and the typical troughs of the PPG signal appear as peaks and the segments may be detected accordingly. However, the convexity / concavity assessment may also be performed without such negation of the signal. Similarly, the convexity / concavity assessment may also be performed on segments of a PPG signal that is reversed in time with later samples preceding earlier samples (not shown).5.23.2 Filter PPG

[0064] With continue reference to FIG. 6, at step 604, the processor(s) 214 may optionally filter the PPG signal by removing impact of one or more noise factors associated with one or more of the following: body temperature, motion artifacts, light wavelength, measurement site, contact force, ambient light intensity, and ambient temperature. Optionally, such noise filtering may be performed prior to step 602.5.2.3.2.1 Body Temperature

[0065] The user’s body temperature may affect tightness evaluation. Cold temperature may compromise PPG signal quality, and reduce accuracy of tightness detection. In examples, the device 100 may optionally include a temperature sensor, and transmit temperature reading to the system 200. In the event that the system 200 detects a low body temperature of the user, the system 200 may output a message requesting the user to warm up and / or may delay acquiring or transmitting the PPG signal until the body temperature reaches a predetermined threshold.

[0066] In examples, the processor(s) 214 may remove any segments of a PPG signal that corresponds to a low body temperature or refrain from performing a tightness evaluation described herein if the temperature is not at a suitable temperature or is below a suitable temperature range.5.2.3.2.2 Motion Artifacts

[0067] The motion artifacts may be caused by the user’s activities such as body movements (including limb movements, head movements, facial expressions, etc.), and physical disconnection or detachment of the device 100 from the user.

[0068] In examples, the processor(s) 214 may optionally identify artifacts related to the physical disconnection or detachment of the device 100 from the user. The processor(s) 214 may identify segments in the PPG signal that correspond to such noise, and discard the identified segments from the PPG signal. As such, in implementations described herein, signal portions marked by motion artefact may be omitted from the tightness detection assessment or omitted from the tightness measurement determinations as described herein. Optionally, such artifact may be detected by detecting signal loss or drops in the PPG signal and / or from analysis of a motion signal from an accelerometer associated with the device 100 and / or user.

[0069] For example, in any implementations described herein, the processor(s) 214 may identify high motion segments in the PPG signal. The processor(s) 214 may detect the high motion segments based on the accelerometer signal provided by the device 100, as the accelerometer signal may indicate activities of the user 101, such as body movements. The processor(s) 214 may eliminate the identified high motion segments from the PPG signal for purposes of the tightness determination.5.23.3 Normalize PPG

[0070] With continued reference to FIG. 6, at step 606, the processor(s) 214 may optionally normalize each detected segment (e.g., trough-to-trough segment) in the PPG signal. Such normalization may, for example, involve vertical normalization such as by scaling the amplitude of the signal, or dividing each sample by the standard deviation of the samples.5.2.3.4 Calculate Parameters

[0071] At 608, the processor(s) 214 may calculate one or more parameters for any of the segments, such as for each trough-to-trough segment of the PPG signal. The processor(s) 214 may also, or alternatively, calculate one or more parameters for each segment, such as trough- to-peak segment, peak-to-peak segment, or peak-to-trough segment or other segment of the signal defined by suitable samples of the signal between two detected points (i.e., samples which may include a detected peak and / or a detected trough and / or a point at a distance from such a peak or trough, etc.) on the PPG signal. The one or more parameters may be associated with an area formed with the signal, and may be computed to assess curvature (e.g., concavity or convexity) of the signal of the segment. The morphology of such segments may tend to concavity from convexity (more concave and less convex) with an increasing amount of undesirable sensor tightness. Of course, in the case of a vertical inversion (negating), such morphology changes may be inverted and the detections and indications may be similarly inverted. Thus, the parameters may serve to distinguish such curvatures. An example area is illustrated by the shaded area SA in Fig. 7 that illustrates a signal analysis with a measured signal that is shown negated for convenience. Such an area may be between an imaginary curve, that is a calculated or computationally modelled curve, such as a straight line (e.g., y = mx + b of slope (m) or intercept (b) form, or other form or polynomial function), that may be associated with end points for the curve or line that are taken from samples of a detected segment of the signal described herein, such as at a trough point and a peak point of a detected trough-to- trough segment, etc., and samples along the signal between such end points. That is, themodelled curve may intersect a segment of the signal at two end points. Referring to FIG. 7, for the trough-to-trough segment between troughs t3 and t4, a function representing a curve, such as an imaginary straight line 11, may be computed or calculated between the trough t3 and a peak m3. The trough t3 may precede the peak m3. Detailed discussion of example parameters is provided below.5.2.3.4.1 First Parameter

[0072] For example, referring to FIG. 7, a first parameter may be associated with a distance measure between the curve or line 11 and the trough-to-trough segment and may be used for purposes of mathematically integrating the signal with respect to the computed curve or line or otherwise determining an area between the signal and the computed curve (e.g., line 11).

[0073] For example, the processor(s) 214 may select a plurality of sample points, such as si, s2, s3, on the line 11, and determine an amplitude difference or a vertical distance between each sample point and a corresponding sample point, e.g., cl, c2, c3, on the trough-to-trough segment. Each sample point on the line 11 and its corresponding sample point on the trough- to-trough segment may have the same timestamp.

[0074] The processor(s) 214 may calculate a plurality of differences or distances between the sample points on the line 11 and their corresponding sample points on the trough-to-trough segment. For example, the processor(s) may determine a first difference or distance between the sample point si and its corresponding sample point cl, a second difference or distance between the sample point s2 and its corresponding sample point c2, and a third difference or distance between the sample point s3 and its corresponding sample point c3. Other methods for assessing the area with distances between the line 11 and the sensor signal may alternatively be utilized such as with distances to the signal from the line 11 along distance lines that are perpendiculars to the imaginary line 11.

[0075] The processor(s) 214 may determine the first parameter by calculating an average of 50% of smallest distances of the plurality of distances. In other words, the processor(s) 214 may determine the first parameter by computing an average of 50% of the lowest difference values in absolute value associated with the area SA. In some implementations, the first parameter from a plurality of segments may be applied to a moving median of a subset of segments from the segments of the signal from a measurement session with the device 100 to provide the first parameter as a moving median first parameter.5.2.3.4.2 Second Parameter

[0076] A second parameter may also provide an indication of the curvature of the signal such as to more directly indicate presence or absence of a concavity in the trough-to-trough segment or convexity in the trough-to-trough segment.

[0077] For example, the processor(s) 214 may evaluate one or more mathematical derivatives (e.g., instantaneous acceleration) of one or more selected sample points, e.g., cl, c2 and c3, on a segment of the signal between the trough t3 and the peak m3. For example, the processor(s) 214 may calculate a second derivative with respect to each of the sample points cl, c2 and c3. If the second derivative such as in relation to a sample point, has a negative value, that sample point may be deemed as part of a section of the segment exhibiting curvature of a more typical concave shape (See, e.g., segment with cl, c2, c3 which is concave down relative to line 11 in Fig. 7) that is indicative of over tightness of the sensor application. Greater concavity may be taken as greater tightness, such as with lesser negative values. Similarly, a sample point that has a positive value may suggest that the signal exhibits a more typical convex shape that is indicative of suitable tightness of the sensor application. Lesser positive values may be taken as a lesser convex shape and greater positive values may be taken as a more convex shape approaching a normal, suitable tightness. Such derivative determination(s) may be made with respect to a point in the sense of a continuous derivative (which may be calculated analytically). Such a determination(s) may also be made as a discrete derivative such as where the derivative is calculated as discrete derivative between two points (such as using neighbouring samples) of a section of a curve. It is noted that a determination of convexity and concavity as described above may be inverted, such as when the typical signal from sensor, such as the typical one shown in FIG. 4B, is not inverted for processing like the inverted PPG signal in Fig. 7. Without such signal inversion, greater convexity (e.g., concave up) may be taken as an indication of greater, and less desirable, tightness, and greater concavity may be taken as lesser, or more suitable, tightness.

[0078] In an example implementation, the processor(s) 214 may determine the second parameter by calculating a percentage of the calculated second derivatives that have a negative value. For instance, if 6 out of 10 sample points have a negative second derivative, then the second parameter may be 60%. In some implementations, the second parameter from a plurality of segments may be applied to a moving median of a subset of segments from the segments of the signal from a measurement session with the device 100 to provide the second parameter as a moving median second parameter.5.1.3.5 Determine Tightness Measure(s)

[0079] Referring back to FIG. 6, at step 610, the processor(s) 214 may determine one or more tightness measures, which may be based on any one or more of the parameters such as the first and / or second parameters. Thus, a plurality of different parameters may be combined. For example, the tightness measure may be a sum of parameters such as a sum of the first and second parameters. In some implementations, such parameters may be combined with a function or formula, depending on their relative importance, which may be indicated by a factor (Xn) for each. An example may be: xl*parameterl + x2*parameter2 = final parameterThus, in some implementations, the processor(s) may determine different measures of tightness, which may then be evaluated. For example, the processor may evaluate a first tightness measure concerning a measure attributable to any of: a discrete portion, several discrete portions or all of a measuring session. Depending on the magnitude of this value, the processor(s) may discard the whole recording and / or report to the user that she / he is applying the sensor too tightly or extremely tight. Moreover, the processor(s) may evaluate a second tightness measure concerning merely a discrete portion of the measuring session. The processor(s) may evaluate this and depending on a level of the measure, the discrete portion of the signal may be discarded. Depending on any of such assessments of the measure(s) using threshold(s), the processor(s) may generate output to provide one or more message(s) to a user to indicate the nature of the tightness condition detected (e.g., completely suitable [i.e., all segments deemed valid], completely unsuitable [i.e., all segments deemed invalid], or somewhat suitable / unsuitable [i.e., some segments deemed valid and some deemed invalid]).

[0080] Moreover, as described herein, a tightness measure may be determined on a segment basis as previously discussed such as a pulse-wise basis (e.g., pulse-by-pulse basis), such as with any of the aforementioned calculated parameters. The segment or pulse-wise tightness measures can be aggregated over multiple different segments or a recording session signal as a whole or can just exist as a discrete single pulse or single segment related measure. Depending on system goals, the signal recording session as a whole, or according to distinct segments or even distinct pulses of the signal, can be evaluated based on different thresholds or cut-offs. Moreover, different types of tightness measures, such as any of the measures described herein, can serve different purposes: e.g., rejecting a recording session as a whole,rejecting parts of a recording session (e.g., on a pul se-by -pulse basis, or on a segment basis, or segment-by-segment basis), and can also similarly be used to indicate or message a condition of elevated tightness to patients / users.5.1.3.6 Threshold Comparison

[0081] Thus, the processor(s) 214 may use one or more predetermined thresholds to effect evaluation of any tightness measure described herein, such as to detect different tightness conditions that may indicate severity, such as an escalated severity indicating extreme tightness, a moderate severity indicating slight tightness, or a threshold representative of suitable tightness. Each of such different tightness condition indications (e.g., severe, slight, suitable, etc.) may be associated with one or more thresholds such as a range of thresholds for a given tightness condition indication. Such thresholds may, for example, be predetermined based on empirical evidence (e.g., observation and calibration based on populations of users). Either one or both may be implemented.5.2.3.6.1 First Threshold

[0082] For example, at step 612, the processor(s) 214 may optionally compare a tightness measure, such as a first tightness measure, determined from step 610 to a first threshold. The first threshold may be used to identify extreme tightness. If the tightness measure exceeds the first threshold, the device 100 may be deemed as extremely tight, an unsuitable fit condition.

[0083] In examples, the first threshold may serve to validate a PPG signal, or portions thereof, collected from a measurement session, such as a sleep or screening / diagnostic session, with the device 100. For example, if the tightness measure from the session exceeds the first threshold, the PPG signal, such as all portions thereof, collected from the session, such as periods of the session coinciding with the tightness measure exceeding the first threshold, may be marked or deemed as invalid. For example, as shown in step 614, when the tightness measure exceeds the first threshold, the processor(s) 214 may discard the PPG signal of the session.

[0084] On the other hand, if the tightness measure is less than or equal to the first threshold, the PPG signal may be deemed as valid or acceptable.

[0085] The thresholds may, for example, have numerical values that may be dependent on the chosen parameter computations and desired indications and may be experimentally determined.5.2.3.6.2 Second Threshold

[0086] Optionally, at step 616, the processor(s) 214 may compare a tightness measure, such as a second tightness measure, to a second threshold. The second threshold may be used to identify slight tightness. If the tightness measure exceeds the second threshold, then the device 100 may be deemed as slightly tight, which may be taken as an unsuitable fit condition for at least a portion of the signal. The second threshold may have a value lower than that of the first threshold or other value. The value may be dependent on the chosen parameter computations and desired indications and may be experimentally determined.

[0087] In examples, the second threshold, such as then considered with a second tightness measure, may assist the processor(s) 214 to conduct piecemeal analysis of the PPG signal collected from a measurement session. For example, at 618, the processor(s) 214 may remove certain PPG segments corresponding to slight tightness from the PPG signal collected from a session, such as periods of the session coinciding with the tightness measure exceeding the second threshold, while maintaining others of the signal that may be valid. When the tightness measure, such as the second tightness measure, exceeds the second threshold where that tightness measure is attributable to a particular portion of the signal, the processor(s) 214 may exclude the corresponding period of time from the PPG signal. Thus, the particular portion may be marked or deemed invalid for further evaluation.

[0088] At step 620, any remaining PPG signal not marked or deemed invalid (if any), such as due to an unsuitable tightness detection, may be used for further analysis, e.g., the physiological condition evaluation 220. For instance, the processor(s) 214 may analyze the remaining PPG signal to derive the peripheral arterial tonometry signal and / or evaluate the signal for sleep disordered breathing events, for example.

[0089] Optionally, if the tightness measure is less than or equal to the second threshold, the device 100 may be deemed to have a suitable, or otherwise acceptable, fit with respect to the user. The PPG signal collected from the measurement session, up to its entirety, may be used for the physiological condition evaluation 220.

[0090] In examples, the processor(s) 214 may identify a period of time in the PPG signal during which the tightness measure exceeds the second threshold. The processor(s) 214 may derive a peripheral arterial tonometry signal from the PPG signal, outside of the identified period of time, to detect an occurrence of a sleep-related event of the user.

[0091] In examples, the processor(s) 214 may determine whether the PPG signal is valid by comparing the tightness measure to the first threshold. After determining that the PPG signal is valid, the processor(s) 214 may compare the tightness measure to the second threshold, and determine whether to exclude the corresponding period of time from the PPG signal for deriving a peripheral arterial tonometry signal to detect an occurrence of a sleep-related event of the user.5.2.4 Other Examples

[0092] In examples, the system may include any one or more of the following: a smart phone, a server, a base station, a laptop, and / or a tablet, among other possibilities.

[0093] In examples, the system 200 may include a smart phone. During and / or after a sleep session of a user, the device 100 may transmit the recorded data to the smart phone via, for example, Bluetooth. The smart phone may perform any one or more of the functions described herein such as including: physiological condition evaluation 220, low perfusion detection 222 and / or tightness evaluation 224. Thereafter, the smart phone may display any result to the user through its graphical user interface.

[0094] In another example, the system may include a smart phone and a server. During and / or after a sleep session of a user, the device 100 may transmit the recorded data to the smart phone via, for example, Bluetooth. The smart phone may then transmit the received data to the server, such as, via a wireless connection. The server may perform any one or more of the functions described herein, such as, including: physiological condition evaluation 220, low perfusion detection 222 and / or tightness evaluation 224. Thereafter, the server may send any result, message or output described herein back to the smart phone or another device for display to the user 101 or the user’s caregiver, for example.

[0095] In examples, the device 100 may be part of the system 200.

[0096] In examples, as the device 100 records the PPG signal and the accelerometer signal, the device 100 may transmit the recorded data to the system 200. In examples, the device 100 may send the recorded data to the system 200 in real time or quasi-real time, or during a setup session of the device 100 prior to sleep. The system 200 may then perform any one of following: physiological condition evaluation 220, low perfusion detection 222 and tightness evaluation 224. For example, as the user sets up the device 100 before sleep, the system 200 may assess tightness of the device 100, and display the determined tightness of the device 100 to the user through a graphical user interface, such as the graphical user interface of a smart phone. For instance, if the system 200 detects that the device 100 is tight on the user, the system200 may advise the user to adjust tightness through, for example, the graphical user interface or a signal (e.g., light signal) of the device or system. As the user adjusts the tightness of the device 100, the system 200 may continuously or repeatedly perform tightness determination, and continuously or repeatedly advise the user to perform adjustment until the system 200 determines a suitable fit.

[0097] In examples, the system 200 may receive recorded data from the device after a sleep session of the user The system 200 may then perform any one or more of the functions described herein, such as including following: physiological condition evaluation 220, low perfusion detection 222 and / or tightness determination 224, based on the PPG signal and the accelerometer signal recorded during the sleep session. For example, after the sleep session, the system 200 may determine tightness of the device 100 for all or part of the sleep session. Based on the tightness evaluation, the system 200 may determine whether any PPG signal collected during the sleep session is valid, or any PPG signal should be excluded from further analysis. In the event that the system 100 detects excessive tightness, the system 100 may output a message advising that the PPG signal collected during the sleep session is invalid due to excessive tightness, and may recommend that the user conducts more sessions with a suitable fit.

[0098] In examples, low perfusion detection 222 and tightness determination 224, may be used individually, or in combination, to assess validity of the PPG signal, or selectively exclude certain segments of the PPG signal from being used for physiological condition evaluation 220. For instance, if a PPG segment has low perfusion, and the same PPG segment indicates tightness, such as slight tightness, then that PPG segment may be removed from the PPG signal, while the remaining PPG signal may be used for physiological condition evaluation 220. In another instance, if all segments of the PPG signal have low perfusion, and excessive tightness is also detected, then the PPG signal to its entirety may be discarded.5.2.5 Flow Chart5.2.5.1 Second Flow Chart FIG. 8

[0099] FIG. 8 illustrates an example flow chart for a method for determining tightness of a wearable device. At 802, at least one processor may receive a photoplethysmography (PPG) signal from a wearable device. At 804, the at least one processor may determine a tightness measure from the PPG signal (e.g., from segment(s) thereof such as trough-to-trough segments), the tightness measure indicating the tightness of the wearable device.

[0100] In examples, the tightness measure may be associated with an area formed between a computed line and the trough-to-trough segment of the PPG signal. Such a computed line may be a straight line between a trough and a peak of the trough-to-trough segment.

[0101] In examples, the step of determining the tightness measure may include determining a first parameter associated with a distance measure between the computed line and the trough-to-trough segment, and may also include determining a second parameter indicating presence and / or degree of concavity in the trough-to-trough segment.

[0102] In examples, the at least one processor may determine the first parameter and the second parameter for each trough-to-trough segment of the PPG signal. The at least one processor may determine a moving median of the determined first and second parameters. The at least one processor may determine the tightness measure based on the moving median.

[0103] In examples, the step of determining the first parameter may include calculating a plurality of distances between a plurality of sample points on the calculated line and corresponding sample points on the trough-to-trough segment. The at least one processor may determine the first parameter by calculating an average of 50% of smallest distances of the plurality of distances.

[0104] In examples, the step of determining the second parameter may include calculating a plurality of second derivatives for a plurality of sample points on a curve between a trough and a peak in the trough-to-trough segment. The trough may precede the peak. The at least one processor may determine the second parameter by determining a percentage of the calculated second derivatives that have a negative value.

[0105] In examples, the step of the determining the tightness measure may include excluding, from the PPG signal, the following period of time during which: a perfusion level is below a perfusion threshold, a motion level exceeds a motion threshold; and / or the wearable device disconnects or detaches from the user.

[0106] In examples, the method may further comprise determining validity of the PPG signal based on the tightness measure. The at least one processor may determine the validity based on the tightness measure and low perfusion detection.

[0107] In examples, the at least one processor may compare the tightness measure to a threshold. The at least one processor may determine that the PPG signal is valid when the tightness measure is less than or equal to the threshold.

[0108] In examples, the at least one processor may identify a period of time in the PPG signal during which the tightness measure exceeds a threshold. The at least one processor mayderive a peripheral arterial tonometry signal from the PPG signal, outside of the identified period of time or during a period of time associated with an acceptable tightness measure, to detect an occurrence of a sleep-related event.

[0109] In examples, the at least one processor may determine whether the PPG signal is valid by comparing the tightness measure to a first threshold. After determining that the PPG signal is valid, the at least one processor may determine whether to exclude any period of time from the PPG signal for deriving a peripheral arterial tonometry signal to detect an occurrence of a sleep-related event by comparing the tightness measure corresponding to the period of time to a second threshold, wherein the second threshold is lower than the first threshold.

[0110] In examples, the at least one processor may determine that the PPG signal is valid when the tightness measure is less than or equal to the first threshold.

[0111] In examples, the at least one processor may exclude the period of time from the PPG signal for deriving the peripheral arterial tonometry signal when the tightness measure corresponding to the period of time exceeds the second threshold.

[0112] In examples, the trough-to-trough segment may be a segment of the PPG signal between two adjacent troughs.

[0113] In examples, the method may include measuring the PPG signal at a finger.

[0114] In examples, the wearable device may include a PPG sensor configured to generate the PPG signal.

[0115] In examples, the PPG sensor may include an infrared sensor and / or a red-light sensor.

[0116] In examples, the step of receiving the PPG signal may include receiving the PPG signal from the wearable device via a wireless connection.

[0117] In examples, the method may include generating an output indicating the tightness of the wearable device.5.3 ADDITIONAL EXAMPLE IMPLEMENTATIONS

[0118] In some implementations, any of the processor(s) described herein may implement a personalised tightness estimator process that may use any one or more of the aforementioned assessments of tightness. In an example process, a personalize tightness estimator process may be executed during a setup phase (e.g., a first use of the device 100), that prompts, via output, the user to follow steps for applying the sensor device. In an initial step of such a process, the processor(s) may be configured to prompt the user to apply the sensor device in a loose manner such as with the user’s hand holding still (which may optionally be confirmed by assessmentof a signal from an accelerometer of the sensor device) and the processor(s) may then log the morphology of the sensor signal(s) with the sensor device loosely applied and still. In a subsequent applying or tightening step, the processor(s) may then prompt the user to apply or tighten an applicator or holding device for appropriate mounting of the sensor device for use (e.g., (as applicable) push the sensor device ring down further on a finger, or push further onto the finger (if a stretchable fabric that surrounds the finger etc.) or adjust a strap of the sensor device such as a watch strap). Since a baseline signal may be determined from the sensor signal during the first loosely applied step, shape related fiducial points of the baseline signal can be extracted and then compared to extracted shape related fiducial points from the signal from the sensor device that are sensed during the subsequent tightening / application step. Such a comparison of fiducial points, and with detected difference(s) thereof, may be evaluated and used to generate output to identify to the user when the application of the sensor device 100 approaches an overtightening state, which may depend on the magnitude of the determined difference(s) between the compared fiducial points, which may be assessed by comparison of the difference(s) to one or more thresholds. Thus, the user can be instructed by the one or more processor(s) when a suitable tightness condition exists according to such difference(s).

[0119] In some such implementations, concavity etc. may be considered but is not required since the fiducial points may be considered from other parts of the signal rather than the particular curved segment previously discussed. Optionally, the one or more processors may also be configured to compensate for the staged process to account for warm-up effects, since during the slightly looser fit first application step, the user (e.g., finger) may warm up or start out colder, and may expand slightly as the user warms with the application of the device. The warming may result in differences in the sensor device signal during the subsequent step when compared to the earlier colder baseline of the first step. Such differences may be taken into account when comparing the fiducial points of the baseline signal to the subsequent signal fiducial points for determining when an optimal perfusion signal is being detected without a transition into an overtightness condition during the subsequent application step.

[0120] Similarly, the processor(s) may also be configured to compensate for changes in the condition of the holding device over time. For example, the physical structure and elastomeric properties of a strap or bandage used as a holding / applicator device may change over time such as by a reduction in initial tension. Thus, the assessment of tightness by the assessments of differences in fiducial points previously discussed may compensate for a change, such as reduction in tension over time, such that the processors may permit some orless transition into an overtightness condition, depending on the nature of the used holding device, during the subsequent application step of the setup process. For example, in the case of permitting some initial overtightness, the condition can alleviate over time due to the nature of the holding structure (e.g., an expected bandage tension reduction).5.4 FURTHER EXAMPLE IMPLEMENTATIONS

[0121] As previously described, example implementations of the present technology may determine a tightness measure for each segments of the signal determined on a pulse-to-pulse basis. The tightness measure may be calculated using a linear combination of two separate parameters (e.g., a trough-to-peak line based area parameter as previously discussed and a second derivative measure as previously discussed). Whenever the PPG signal has low perfusion or during excessive movement as determined from an accelerometer signal, the tightness measure may be skipped for that segment because signal quality is too low. Such pulse-to-pulse tightness measures can then be analyzed in different ways. They can be aggregated for the whole recording session signal or for specific segments of the signal and can be assessed by different thresholds as to any of the aggregations or a single pulse / segment measure. Doing so you can achieve different purposes. The assessment can serve as a basis to discard the whole recording signal (e.g. if an aggregation of tightness measures over the full recording is too high). The assessment can serve as a basis to message to a user or patient that elevated tightness is detected (e.g., if an aggregation of tightness measures over the full recording is high). The assessment can serve as a basis to discard specific segments or even single pulses of the PPG signal (e.g., by inspection of a tightness measure derived from a single pulse or at aggregations of tightness measures derived from a specific group of segments).5.5 EXAMPLE COMPONENTS

[0122] The memory 112 and / or the memory 212 may be a non-transitory computer- readable medium configured to store one or more algorithms and / or methods described herein in the form of computer program instructions and / or information / data described herein. Thus, the memory 112 and / or 212 may include one or more of the following: non-volatile memory, battery powered static random-access memory (RAM), and volatile RAM. The memory 112 and / or 212 may be in the form of electrically erasable programmable read-only memory (EEPROM) or NAND flash and / or any other secondary data storage device(s). Such memory may also include, for example one or more databases, which may be remote or collocated withthe processor(s) 114 and / or 214. Thus, such memory or databases may optionally be remotely accessible, for example, via the network interface 116 and / or 216.

[0123] The processor(s) 114 and / or the processor(s) 214 may be a dedicated electronic circuit or an application-specific integrated circuit. The processor(s) 114 and / or 214 may be formed with discrete electronic components. The processor(s) 114 and / or 214 may include a dedicated motor control integrated circuit. The processor(s) 114 and / or 214 may include one or more processors or microprocessors, configured to execute one or more computer programs stored in the memory 112 and / or 212.

[0124] The network interface 116 and / or the network interface 216 may include a wired and / or wireless communication interface(s). The wired communication interface may include a wired protocol, to allow, for example, communication via a network, such as an internet or the Internet via Ethernet or optical fibre. The wireless communication interface may include one or more transceivers using wireless protocols such as infrared protocol, cellular, Bluetooth, WIFI, Bluetooth LE, and Bluetooth BLE (5.0) with GATT profile, among other possibilities. The wireless communication interface may be a low power communication interface, e.g., a Bluetooth Low Energy, BLE, wireless interface. In examples, the network interface may allow wireless transmission between the device 100 and the system 200. For instance, the processor(s) 214 may receive the PPG signal and / or the accelerometer signal measured by the sensor 104 and / or the accelerometer 110 of the device 100 via a wireless connection.5.6 TECHNICAL ADVANTAGES

[0125] The present technology may detect tightness of the wearable device, and allow timely informing of the user to adjust the wearable device to a suitable fit. The present technology may improve the overall accuracy of the physiological condition evaluation, by identifying, filtering and / or eliminating PPG signals that are negatively affected by tightness of the wearable device.5.7 GLOSSARY

[0126] For the purposes of the present technology disclosure, in certain forms of the present technology, one or more of the following definitions may apply. In other forms of the present technology, alternative definitions may apply.

[0127] Apnea. According to some definitions, an apnea, which may be an event of sleep disordered breathing, is said to have occurred when flow falls below a predetermined thresholdfor a duration, e.g., 10 seconds. An obstructive apnea will be said to have occurred when, despite patient effort, some obstruction of the airway does not allow air to flow. A central apnea will be said to have occurred when an apnea is detected that is due to a reduction in breathing effort, or the absence of breathing effort, despite the airway being patent. A mixed apnea occurs when a reduction or absence of breathing effort coincides with an obstructed airway.

[0128] Hypopnecr. According to some definitions, a hypopnea, which may be an event of sleep disordered breathing, is taken to be a reduction in flow, but not a cessation of flow. In one form, a hypopnea may be said to have occurred when there is a reduction in flow below a threshold rate for a duration. A central hypopnea will be said to have occurred when a hypopnea is detected that is due to a reduction in breathing effort. In one form in adults, either of the following may be regarded as being hypopneas:(i) a 30% reduction in patient breathing for at least 10 seconds plus an associated 4% desaturation; or(ii) a reduction in patient breathing (but less than 50%) for at least 10 seconds, with an associated desaturation of at least 3% or an arousal.5.8 OTHER REMARKS

[0129] A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in Patent Office patent files or records, but otherwise reserves all copyright rights whatsoever.

[0130] Unless the context clearly dictates otherwise and where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit, between the upper and lower limit of that range, and any other stated or intervening value in that stated range is encompassed within the technology. The upper and lower limits of these intervening ranges, which may be independently included in the intervening ranges, are also encompassed within the technology, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the technology.

[0131] Furthermore, where a value or values are stated herein as being implemented as part of the technology, it is understood that such values may be approximated, unless otherwise stated, and such values may be utilized to any suitable significant digit to the extent that a practical technical implementation may permit or require it.

[0132] Furthermore, “approximately”, “substantially”, “about”, or any similar term used herein means + / - 5-10% of the recited value.

[0133] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this technology belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present technology, a limited number of the exemplary methods and materials are described herein.

[0134] When a particular material is identified as being used to construct a component, obvious alternative materials with similar properties may be used as a substitute. Furthermore, unless specified to the contrary, any and all components herein described are understood to be capable of being manufactured and, as such, may be manufactured together or separately.

[0135] It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include their plural equivalents, unless the context clearly dictates otherwise.

[0136] All publications mentioned herein are incorporated herein by reference in their entirety to disclose and describe the methods and / or materials which are the subject of those publications. The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present technology is not entitled to antedate such publication by virtue of prior disclosure. Further, the dates of publication provided may be different from the actual publication dates, which may need to be independently confirmed.

[0137] The terms "comprises" and "comprising" should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced.

[0138] The subject headings used in the detailed description are included only for the ease of reference of the reader and should not be used to limit the subject matter found throughout the disclosure or the claims. The subject headings should not be used in construing the scope of the claims or the claim limitations.

[0139] Although the technology herein has been described with reference to particular examples, it is to be understood that these examples are merely illustrative of the principles and applications of the technology. In some instances, the terminology and symbols may imply specific details that are not required to practice the technology. For example, although the terms"first" and "second" may be used, unless otherwise specified, they are not intended to indicate any order but may be utilised to distinguish between distinct elements. Furthermore, although process steps in the methodologies may be described or illustrated in an order, such an ordering is not required. Those skilled in the art will recognize that such ordering may be modified and / or aspects thereof may be conducted concurrently or even synchronously.

[0140] It is therefore to be understood that numerous modifications may be made to the illustrative examples and that other arrangements may be devised without departing from the spirit and scope of the technology.

Claims

6 CLAIMS1. A system for determining tightness of a wearable device, comprising: at least one processor configured to: receive a photoplethysmography (PPG) signal from a wearable device; and determine a tightness measure from the PPG signal, the tightness measure indicating the tightness of the wearable device.

2. The system of claim 1, wherein the tightness measure is determined from a detected segment of the PPG signal.

3. The system of claim 2 wherein the detected segment comprises any of a detected peak and / or a detected trough.

4. The system of any one of claims 2 to 3, wherein the tightness measure is associated with an area formed between a computed curve and the detected segment of the PPG signal.

5. The system of claim 4, wherein the computed curve intersects the detected segment at two end points of the detected segment.

6. The system of any one of claims 4 to 5, wherein the tightness measure is determined based on: a first parameter associated with a distance measure between the computed curve and the detected segment; and a second parameter indicating presence of a concave characteristic in the detected segment.

7. The system of claim 6, wherein the at least one processor is configured to: determine the first parameter and the second parameter for each detected segment of the PPG signal, determine a moving median of the determined first and second parameters; and determine the tightness measure based on the moving median.

8. The system of any one of claims 6 to 7, wherein the at least one processor is configured to determine the first parameter by: calculating a plurality of distances between a plurality of sample points on the computed curve and corresponding sample points on the detected segment; and determining the first parameter by calculating an average of 50% of smallest distances of the plurality of distances.

9. The system of any one of claims 6 to 8, wherein the at least one processor is configured to determine the second parameter by: calculating a plurality of second derivatives for a plurality of sample points on a curve between a trough and a peak in the detected segment, the trough preceding the peak; and determining the second parameter by determining a percentage of the calculated plurality of second derivatives that have a negative value.

10. The system of any one of claims 1 to 9, wherein the at least one processor is configured to determine validity of the PPG signal based on the tightness measure.

11. The system of claim 10, wherein the at least one processor is configured to determine the validity of the PPG signal based on the tightness measure and low perfusion detection.

12. The system of any one of claims 1 to 11, wherein the at least one processor is configured to: compare the tightness measure to a threshold; and determine that the PPG signal is valid when the tightness measure is less than or equal to the threshold.

13. The system of any one of claims 1 to 12, wherein the at least one processor is configured to: identify a period of time in the PPG signal during which the tightness measure exceeds a threshold; and derive a peripheral arterial tonometry signal from the PPG signal, outside of the identified period of time, to detect an occurrence of a sleep-related event.

14. The system of any one of claims 1 to 13, wherein the at least one processor is configured to: determine whether the PPG signal is valid by comparing the tightness measure to a first threshold; and after determining that the PPG signal is valid, determine whether to exclude any period of time from the PPG signal for deriving a peripheral arterial tonometry signal to detect an occurrence of a sleep-related event by comparing the tightness measure corresponding to the period of time to a second threshold, wherein the second threshold is lower than the first threshold.

15. The system of claim 14, wherein the at least one processor is configured to determine that the PPG signal is valid when the tightness measure is less than or equal to the first threshold.

16. The system of any one of claims 14 to 15, wherein the at least one processor is configured to exclude the period of time from the PPG signal for deriving the peripheral arterial tonometry signal when the tightness measure exceeds the second threshold.

17. The system of any one of claims 1 to 16, wherein the detected segment is a segment of the PPG signal between two adjacent troughs.

18. The system of any one of claims 1 to 17, wherein the PPG signal is measured at a finger.

19. The system of any one of claims 1 to 18, wherein the wearable device includes a PPG sensor configured to generate the PPG signal.

20. The system of claim 19, wherein the PPG sensor includes an infrared sensor and / or a red- light sensor.

21. The system of any one of claims 1 to 20, wherein the at least one processor is configured to receive the PPG signal from the wearable device via a wireless connection.

22. The system of any one of claims 1 to 21, further comprising the wearable device.

23. The system of any one of claims 1 to 22, wherein the at least one processor is configured to generate an output indicating the tightness of the wearable device.

24. A method for determining tightness of a wearable device, comprising: receiving, by at least one processor, a photoplethysmography (PPG) signal from a wearable device; and determining, by the at least one processor, a tightness measure from the PPG signal, the tightness measure indicating the tightness of the wearable device.

25. The method of claim 24, wherein the tightness measure is determined from a detected segment of the PPG signal.

26. The method of claim 25 wherein the detected segment comprises any of: a detected peak and / or a detected trough.

27. The method of any one of claims 25 to 26, wherein the tightness measure is associated with an area formed between a computed curve and the detected segment of the PPG signal.

28. The method of claim 27, wherein the computed curve intersects the detected segment at two end points of the detected segment.

29. The method of any one of claims 27 to 28, wherein the determining the tightness measure includes: determining a first parameter associated with a distance measure between the computed curve and the detected segment; and determining a second parameter indicating presence of a concave in the detected segment.

30. The method of claim 29, further comprising: determining the first parameter and the second parameter for each detected segment of the PPG signal, determining a moving median of the determined first and second parameters; anddetermining the tightness measure based on the moving median.

31. The method of any one of claims 29 to 30, wherein the determining the first parameter includes: calculating a plurality of distances between a plurality of sample points on the computed curve and corresponding sample points on the detected segment; and determining the first parameter by calculating an average of 50% of smallest distances of the plurality of distances.

32. The method of any one of claims 29 to 31, wherein the determining the second parameter includes: calculating a plurality of second derivatives for a plurality of sample points on a curve between a trough and a peak in the detected segment, the trough preceding the peak; and determining the second parameter by determining a percentage of the calculated second derivatives that have a negative value.

33. The method of any one of claims 24 to 32, further comprising: determining validity of the PPG signal based on the tightness measure.

34. The method of claim 33, wherein the determining validity includes determining validity of the PPG signal based on the tightness measure and low perfusion detection.

35. The method of any one of claims 24 to 34, further comprising: comparing the tightness measure to a threshold; and determining that the PPG signal is valid when the tightness measure is less than or equal to the threshold.

36. The method of any one of claims 24 to 34, further comprising: identifying a period of time in the PPG signal during which the tightness measure exceeds a threshold; and deriving a peripheral arterial tonometry signal from the PPG signal, outside of the identified period of time, to detect an occurrence of a sleep-related event.

37. The method of any one of claims 24 to 34, further comprising: determining whether the PPG signal is valid by comparing the tightness measure to a first threshold; and after determining that the PPG signal is valid, determining whether to exclude any period of time from the PPG signal for deriving a peripheral arterial tonometry signal to detect an occurrence of a sleep-related event by comparing the tightness measure corresponding to the period of time to a second threshold, wherein the second threshold is lower than the first threshold.

38. The method of claim 37, further comprising: determining that the PPG signal is valid when the tightness measure is less than or equal to the first threshold.

39. The method of any one of claims 37 to 38, further comprising: excluding the period of time from the PPG signal for deriving the peripheral arterial tonometry signal when the tightness measure corresponding to the period of time exceeds the second threshold.

40. The method of any one of claims 24 to 39, wherein the detected segment is a segment of the PPG signal between two adjacent troughs.

41. The method of any one of claims 24 to 40, further comprising: measuring the PPG signal at a finger.

42. The method of any one of claims 24 to 41, wherein the wearable device includes a PPG sensor configured to generate the PPG signal.

43. The method of claim 42, wherein the PPG sensor includes an infrared sensor and / or a red- light sensor.

44. The method of any one of claims 24 to 42, wherein the receiving the PPG signal includes: receiving the PPG signal from the wearable device via a wireless connection.

45. The method of any one of claims 24 to 44, further comprising: generating an output indicating the tightness of the wearable device.

46. A processor-readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors to perform the method of any one of claims 34 to 45.

47. A processor-readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors to determine tightness of a wearable device, the processor-executable instructions comprising: instructions to receive, by the one or more processors, a photoplethysmography (PPG) signal from a wearable device; and instructions to determine, by the one or more processors, a tightness measure from the PPG signal, the tightness measure indicating the tightness of the wearable device.

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