Optical muscular micromotion (fasciculation / fibrillation) sensor

Abstract

A wearable optical sensing device and methods are disclosed for concurrently deriving photoplethysmography (PPG) parameters and detecting tissue micromotions using the same optical modules. An emitter illuminates tissue and a photodetector produces signals that are demodulated subtraction synchronized to a pulsed drive. A signal processor separates the demodulated stream into bands, computing PPG parameters from about 0.5–4 Hz and a micromotion index from about 4–12 Hz (e.g., 4–6 Hz and 8–12 Hz). The optical modules may operate in reflective and / or transmissive geometries around a finger ring; other form factors are supported. Multi-wavelength operation (e.g., green, red and / or near-infrared) and / or differential photodetectors enable suppression of blood-volume pulsatility to enhance sensitivity to geometry-driven path-length modulation associated with micromotion. Optional inertial gating reduces artifacts from gross motion. An adaptive controller adjusts LED power, duty cycle, sampling, and pairing to maintain SNR. Metrics are logged or transmitted and may trigger user feedback.

Description

[0001] Docket: 0396-0022 WO 1

[0002] OPTICAL MUSCULAR MICROMOTION (FASCICULATION / FIBRILLATION) SENSOR

[0003] RELATED APPLICATIONS

[0004] [ oooi] This application claims the benefit under 35 U.S.C. § 119(e) of U.S. Provisional Application No. 63 / 716,801, filed on November 6, 2024, which is incorporated herein by reference in its entirety.

[0005] BACKGROUND OF THE INVENTION

[0006]

[0002] Wearable devices, such as fitness trackers or smartwatches, with optical heart rate sensors, are becoming common.

[0007]

[0003] The technology behind these sensors is called photoplethysmography (PPG), which is an optical measurement technique used to detect blood volume changes in living tissues. A PPG sensor requires few optoelectronics components, such as a light source, e.g. light-emitting- diode (LED) to illuminate the living tissue, a photodetector (PD) to track any light intensity variation due to the blood volume change and an analog front-end (AFE) for signal conditioning and processing. Today, the importance of PPG for medical monitoring is proven by the number of primary vital signs directly or indirectly recordable out of it.

[0008]

[0004] The PPG signal is obtained by shining light from the LED at a given wavelength, in the visible or near-infrared range, into a human tissue, e.g. finger, wrist, forehead, ear lobes. The PPG sensor or photodetector detects the light transmitted through (transmissive PPG) or reflected from (reflective PPG) the tissue and transforms it into a photogenerated current.

[0009]

[0005] Muscular fibrillation refers to the spontaneous contraction of individual muscle fibers, resulting in a quivering or twitching appearance of the muscle. This phenomenon often occurs in response to stress, which can lead to alterations in the neuromuscular system. In stressful situations, the body releases stress hormones like cortisol, which can impact nerve function and muscle activity. This disruption may manifest as fibrillation, signaling an underlying issue with neuromuscular communication or muscle fiber health. In some neuro- degenerative conditions, such as amyotrophic lateral sclerosis (ALS) or multiple sclerosis (MS), the pathways that facilitate muscle contractions become compromised, exacerbating symptoms like fibrillation.

[0010]

[0006] Micromotion refers to the subtle, often involuntary movements of muscles, such as fasciculations and fibrillation. In individuals with neuro-degenerative conditions, these micro- Docket: 0396-0022 WO 1 movements can be indicative of the central nervous system’s struggle to maintain coordinated muscle control. As the disease progresses, the brain’s ability to send precise signals to the muscles diminishes, leading to an increase in uncoordinated muscle activity. This lack of precision can result in heightened micromotion, further complicating physical mobility and stability. Patients may find themselves experiencing muscle spasms or tremors that affect their quality of life, often accompanied by increased anxiety and stress.

[0011]

[0007] Micromotion highlights the interplay between stress and neuromuscular health, particularly in the context of neuro-degenerative diseases. As stress levels rise, the neurochemical balance can shift, amplifying the symptoms of these conditions. The presence of micromotion can serve as critical indicators for healthcare providers, signaling the need for intervention and support. Understanding these phenomena is essential for developing effective therapeutic strategies aimed at alleviating symptoms and improving overall muscle function and coordination in affected individuals.

[0012]

[0008] Conditions such as Parkinson’s disease, Huntington’s disease and essential tremor are characterized by abnormal micromotions. In Parkinson’s, these tremors typically occur at rest and are rhythmic, with a frequency of around 4 to 6 Hz (resting tremor). In other neurodegenerative disorders, the frequency and type of micromotions may vary based on the area of the brain affected.

[0013]

[0009] Stress can amplify micromotions, especially in conditions such as essential tremor, which tends to worsen with anxiety or heightened emotional states. Stress activates the sympathetic nervous system, increasing the excitability of motor pathways and leading to more pronounced micromotions. Stress-related tremors (enhanced physiological tremor) tend to occur at a frequency of around 8 to 12 Hz. These tremors are often fine, rapid, and temporary, subsiding when the stressor is removed.

[0014]

[0010] Muscular fibrillations (in neurodegenerative diseases) typically occur at 1 to 10 Hz, and are typically detected via EMG (electromyography), but are not usually visible.

[0015]

[0011] Resting tremors in Parkinson’s typically occur at 4 to 6 Hz, while essential tremors and stress-related tremors occur from 8 to 12 Hz. In many of today’s wearable consumer devices, accelerometers are used to sense motion; however, micromotion amplitude falls below the accelerometers’ sensitivity. State of the art techniques to sense micromotions, fasciculation and fibrillations focus on EMG. Docket: 0396-0022 WO 1

[0016] SUMMARY OF THE INVENTION

[0017]

[0012] State-of-the-art PPG sensors are discrete component systems or integrated circuits (IC) embedding a photosensitive area, an analog front end (AFE) and an analog-to-digital- converter (ADC).

[0018]

[0013] Muscle micromotions are typically treated as noise when it comes to photoplethysmography .

[0019]

[0014] Embodiments of the present invention utilize pulsed light to detect micromotion. Red and near-infrared (NIR) penetrate deep enough through tissue on body areas like fingers. NIR light can cross the muscular area.

[0020]

[0015] The signal reflected back crosses an optical path that changes with micromotion, which changes its amplitude.

[0021]

[0016] The same optical module used for PPG can be used for this application, combined with signal processing that separates blood-volume pulsatility (-0.5-4 Hz) from micromotion content (-4-12 Hz) using bandpass / notch filtering and / or multi-wavelength subtraction.

[0022]

[0017] In one aspect, a wearable device comprises at least one optical module including a light emitter and an optical receiver, and a signal processor configured to drive the light emitter and acquire signals from the optical receiver. The signal processor is further configured to compute a micromotion index from a band pass including about 4-12 Hz from the acquired signals, and to compute at least one photoplethysmography (PPG) parameter from a band pass including about 0.5-4 Hz of at least one of the acquired signals.

[0023]

[0018] In some embodiments, the signal processor drives the light emitter with a pulsed waveform and, for each sample, subtracts a measurement acquired during an emitter off interval from a measurement acquired during an emitter on interval to produce a demodulated optical signal substantially free of ambient light.

[0024]

[0019] In certain implementations, computing the micromotion index includes computing a first amplitude in a 4-6 Hz band and a second amplitude in an 8-12 Hz band, and the index can be reported as one or both of the amplitudes or as a function of the amplitudes.

[0025]

[0020] In another embodiment, the optical module comprises emitters of different wavelengths, such as a red, and / or green emitter and / or a near-infrared emitter, and the signal processor forms a combination of signals from the different wavelengths — for example a linear Docket: 0396-0022 WO 1 combination with a selected coefficient — to reduce energy in the 0.5-4 Hz band prior to computing the micromotion index.

[0026]

[0021] The wearable device may further comprise an inertial sensor, such as an accelerometer and / or gyroscope, and the signal processor gates or down weights analysis of the acquired signals during intervals in which an activity metric derived from the inertial sensor exceeds a threshold.

[0027]

[0022] In some versions, the optical module comprises first and second optical receivers at different locations relative to the light emitter, and the signal processor forms a differential signal between outputs of the first and second optical receivers and computes the micromotion index from the differential signal.

[0028]

[0023] In a ring-based implementation, the wearable device comprises a plurality of optical modules arranged around an inner bore of a ring shaped body. The signal processor selects, according to a pairing map, opposed ones of the optical modules to obtain transmissive measurements across a finger and time division multiplexes operation of the optical modules to avoid optical crosstalk.

[0029]

[0024] The signal processor can compute at least one PPG parameter selected from heart rate, heart rate variability, perfusion index, arterial oxygen saturation, and an estimated blood pressure. Such parameters may be computed contemporaneously with the micromotion index from the same acquired signals.

[0030]

[0025] In some embodiments, the wearable device further comprises a memory and a wireless interface, and the signal processor stores to the memory or transmits via the wireless interface data including the micromotion index together with a timestamp and a confidence measure, and provides a user feedback through a user interface when the micromotion index satisfies a criterion.

[0031]

[0026] In another aspect, a photoplethysmography (PPG) sensor comprises an optical emitter that transmits a light beam into tissue, an optical detector that detects light from the tissue and outputs an output signal representative of an amplitude of the detected light, and an analyzer that receives the output signal and detects micromotion in the output signal and, if micromotion is detected, determines a frequency of the micromotion. The analyzer further detects vital signs including any of: heart rate / pulse, blood pressure, and oxygenation, and reports the micromotion and vital signs to a user device and / or a medical facility. Docket: 0396-0022 WO 1

[0032]

[0027] In a further aspect, a signal analysis method for a wearable device includes driving a light emitter and acquiring signals from an optical receiver from tissue of a user, computing a micromotion index from a band pass including about 4-12 Hz from the acquired signals, and computing at least one PPG parameter from a band pass including about 0.5-4 Hz of at least one of the acquired signals.

[0033]

[0028] In some embodiments of the method, driving the light emitter comprises alternately pulsing emitters of different wavelengths, and forming a coefficient-based combination to reduce energy in the 0.5-4 Hz band prior to computing the micromotion index.

[0034]

[0029] In additional embodiments, acquiring signals comprises selecting, according to a pairing map, opposed optical modules across an inner bore of a ring body to obtain transmissive measurements and selecting single optical modules to obtain reflective measurements, with time division multiplexing of the optical modules to avoid optical crosstalk.

[0035]

[0030] The method may further acquire inertial sensor data and gate or down-weight analysis during intervals in which an activity metric exceeds a threshold, and determine at least one of heart rate, heart-rate variability, perfusion index, arterial oxygen saturation, and an estimated blood pressure as the PPG parameter.

[0036]

[0031] Any of the foregoing features may be implemented alone or in combination unless technically incompatible, and the foregoing summaries are intended to illustrate, not limit, the scope of the invention as defined by the claims.

[0037]

[0032] The above and other features of the invention including various novel details of construction and combinations of parts, and other advantages, will now be more particularly described with reference to the accompanying drawings and pointed out in the claims. It will be understood that the particular method and device embodying the invention are shown by way of illustration and not as a limitation of the invention. The principles and features of this invention may be employed in various and numerous embodiments without departing from the scope of the invention.

[0038] BRIEF DESCRIPTION OF THE DRAWINGS

[0039]

[0033] In the accompanying drawings, reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale; emphasis has instead been placed upon illustrating the principles of the invention. Of the drawings:

[0040]

[0034] Fig. l is a schematic illustrating the inventive concept. Docket: 0396-0022 WO 1

[0041]

[0035] Fig. 2 is a block diagram illustrating the process executed by the invention.

[0042]

[0036] Fig. 3 shows an exemplary smart or sensor ring system for executing and implementing the processes and subprocesses described in Figs. 1 and 2.

[0043]

[0037] Fig. 4 shows an exemplary PPG apparatus, used to determine or estimate vital signs such as blood pressure and heart rate and micromotion.

[0044]

[0038] Fig. 5 illustrates a representative signal -acquisition and processing architecture executed by the signal processor 126 of the ring system 100.

[0045] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0046]

[0039] The invention now will be described more fully hereinafter with reference to the accompanying drawings, in which illustrative embodiments of the invention are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0047]

[0040] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items. Also, all conjunctions used are to be understood in the most inclusive sense possible. Thus, the word "or" should be understood as having the definition of a logical "or" rather than that of a logical "exclusive or" unless the context clearly necessitates otherwise. Further, the singular forms and the articles "a", "an" and "the" are intended to include the plural forms as well, unless expressly stated otherwise. It will be further understood that the terms: includes, comprises, including and / or comprising, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. Further, it will be understood that when an element, including component or subsystem, is referred to and / or shown as being connected or coupled to another element, it can be directly connected or coupled to the other element or intervening elements may be present.

[0048]

[0041] SYSTEM OPERATION

[0049]

[0042] Distal body parts, such as the hands, fingers, and feet, are generally more prone to stress-induced or disease-induced micromotions, such as tremors or fine muscle twitches. There are several reasons why distal areas are more affected by micromotions, for example: Docket: 0396-0022 WO 1

[0050]

[0043] 1) Higher sensitivity to fine motor control;

[0051]

[0044] 2) Proximity to peripheral nerves; and

[0052]

[0045] 3) Distal limbs have less muscular stability than other parts of the body.

[0053]

[0046] Optical sensors for micromotion according to aspects of the present invention are expected to better operate on fingers since the muscular tissue of the finger is smaller than other parts of the body, that is, a finger is easier to cover with limited optical power. In addition, the geometry is often better with fingers, i.e., shorter optical paths, smaller muscle volume, tighter mechanical coupling in a ring.

[0054]

[0047] For the above reasons, fitting such an optical sensor on a smart ring is particularly efficient.

[0055]

[0048] Fig. 1 is a schematic illustrating the concept. Lines 22A represent the skin of a user, for example, a finger, when not dilated. Lines 22B, on the other hand, represent the skin of the finger due to dilatation of the tissue due to micromotion. Line 13A represents the cross section of the finger when not dilated, while line 13B represents the larger cross section of the finger when dilated due to this micromotion.

[0056]

[0049] An optical emitter 11 of an optical module 200 emits a light beam into the tissue 22. As illustrated by optical pathways 15A and 15B, the emitted may take different pathways within the tissue. When the tissue is not dilated 22A, the light may take a path such as 15 A. On the other hand, when the tissue is dilated 22B, the light might take a different path 15B having a different attenuation. Alternatively, the light may pass through the tissue 22 and be detected on the other side of the tissue opposite the emitter.

[0057]

[0050] An optical receiver 12 detects the beam reflected by and / or transmitted through the tissue 22, and a signal processor follows the changing amplitude of the received beam to determine the frequency of any detected micromotion. Often, the amplitude change arises from geometric path-length and scattering-angle changes due to micro-dilatation or micro-translation of tissue relative to the module, and that it is detectable even when accelerometer noise floors mask such motion.

[0058]

[0051] Fig. 2 is a system schematic. An optical module 200 comprises both the optical emitter 11 and optical receiver 12 of Fig. 1. It emits a preferably pulsed light beam through the user’s tissue 22 and receives / detects the light after it is reflected by and / or has passed through at least a portion of the tissue 22, and passes a signal representing the time varying intensity of the Docket: 0396-0022 WO 1 detected light (137) to a signal processor 126. The signal processor 126 employs signal analysis to produce an option 136 that resolves small changes including small changes in the amplitude of the detected light, and determine the frequency of such changes if they exist. As discussed previously, a frequency in the range of 8-12 Hz suggests stress-induced micromotion 127, while a frequency in the range of 4-6 Hz may suggest micromotion due to a neurodegenerative disease 129. The signal processor 126 may also control the optical module, for example by turning it off or on, or by changing the output power.

[0059]

[0052] The frequency of micromotions and their amplitude can be used as input for algorithms that monitor different aspects such as early detection of neurological disorders or simply detection of a user’s mental health and stress. Indeed, several neurodegenerative diseases such as Parkinsons are characterized by a gradual increase of micromotion at specific frequencies that tend to increase with the severity of the disease. When it comes to stress, the amplitude and frequency of occurrence over the day are direct indicators that can help to alert the user about the user’s mental health.

[0060]

[0053] The data, once processed, can be used to deliver direct feedback to the user in order to guide him in improving his lifestyle and / or as a preventive action such warning the user that the user may be subject to falling. This information can either be directly fed to the user or shared with health partners. It can also be used in the frame of remote health monitoring or post treatment monitoring.

[0061]

[0054] Fig. 3 shows preferred embodiment of the invention in the context of a smart or sensor ring system 100.

[0062]

[0055] In general, the sensor ring includes a ring or annual-shaped ring body 110 having an inner bore 1101 sized to receive a human digit such as a finger, and specifically an index finger, middle finger, ring finger, or little finger or pinkie. The ring body 110 is typically a molded plastic or ceramic material, but could also be metal.

[0063]

[0056] An array of PPG sensor optical modules 200-1 to 200-8 are distributed around the inner bore and directed inwardly in order to perform PPG and micromotion sensing of the digit inserted into the inner bore 1101. In the illustrated example, the optical modules 200-1 to 200-8 are evenly arrayed in a concentric ring.

[0064]

[0057] A control unit CU is installed on a ring-shaped, concentric printed circuit board PCB. The control unit CU controls the triggering of and readout from the optical modules 200. In one mode of operation, the control unit CU alternates between a transmissive PPG mode, in Docket: 0396-0022 WO 1 which opposed pairs of optical modules such as 200-4, 200-8 are used, and reflective PPG mode, in which individual modules are used. The control unit CU preferably includes a Bluetooth-low- energy communications block BLE and a power management block PM, for communicating data with the external world and regulating system power, respectively.

[0065]

[0058] The control unit CU stores sensor readings to a memory unit M, which also contains the operating instructions for the system set-up and other firmware components required for operation.

[0066]

[0059] A battery B provides power to the system via the PCB, and is generally controlled by the power management unit PM in order to provide for extended operation.

[0067]

[0060] A sensor block S has inertial sensors, including a three axis accelerometer and a three axis gyroscope. In some cases, the accelerometer and the gyroscope each have more than three axes, possibly six axes. In addition, the sensor block S also preferably has a user temperature sensor and an ambient temperature sensor, for separate body and environmental temperature detection.

[0068]

[0061] A user interface block SUI provides active feedback from the device to the user and also receives user control input. In some examples, the SUI block includes a visible EED array and a touch sensor system, such as a capacitive touch sensor array.

[0069]

[0062] The PPG apparatus, such as the illustrated ring, 100 is used to determine or estimate vital signs such as blood pressure and heart rate. The apparatus 100 can also be realized in an earbud, wrist device, and / or chest patches.

[0070]

[0063] As shown in Fig. 4, each PPG optical module 200 embeds an optical emitter 11 and optical receiver 12. Multiple light sources and light detectors are also possible. The PPG sensor is in contact with the tissue, i.e., skin 22 of a user. Different body locations are possible, including, but not limited to, the finger, the wrist and the ear canal. Due to the pulsatility of blood flow through the tissue in the subcutaneous vasculature and blood vessels 27 and 28, the perfusion index of the skin changes. This is defined as the ratio between the AC component 29 of the reflective signal and the DC component 30. The superimposition of 29 and 30 builds the pulsatile signal that is input into a blood pressure estimator. Points 31 and 32 represent the systolic and diastolic points, respectively, of the signal, resulting from the light absorption in the skin 22 as illustrated by the Beer-Lambert law.

[0071]

[0064] According to embodiments of the invention, the same PPG device 100 is extended to determine or estimate vital signs, and detect and analyze micromotions. In some examples, the Docket: 0396-0022 WO 1 control unit CU accesses sensor readings from the memory unit M that carries out the signal analysis of the data and determines micromotions that might be due to stress or a neuro- degenerative disease. At the same time, the control unit CU provides other vital signs such heart rate, blood pressure, oxygenation, etc. This information may then be directed to a user interface and / or to a medical facility where the information may be further processed and / or displayed or reported.

[0072]

[0065] It should be understood that other signals processors can be used aside from the device’s control unit CU. For example, a first signal processor may be devoted to micromotion, while a second signal processor may be devoted to vital signs. In other example, the user device simply functions to detect signals and then sends the sensor data to another computer that functions as the signal processor 126.

[0073]

[0066] Fig. 5 illustrates a representative signal acquisition and processing architecture executed by the signal processor 126 of the ring system 100 to operate the same set of optical modules 200 for both photoplethysmography (PPG) and micromotion sensing. In the depicted embodiment, the processor 126 configures a scheduler 126A that addresses the optical modules 200, receives raw digitized samples from those modules, and then performs a sequence of demodulation, normalization and inertial gating operations (126B, 126C, 126C1). The resulting conditioned stream is routed concurrently into a PPG pipeline 126D and a micromotion pipeline 126E. A fusion and decision stage 126F combines the outputs, and an adaptive control loop 126H updates acquisition parameters in real time. The system then performs one or more device actions via block 126J. Although Fig. 5 presents these functions as discrete blocks, in practice they may be implemented in software, firmware, and / or hardware and may execute in a pipelined or parallel manner. The micromotion analysis is generalized to about 2-14 Hz to encompass tremor and fasciculation ranges reported across conditions (e.g., multiple sclerosis, Parkinson’s disease, amyotrophic lateral sclerosis and stress tremor), while PPG remains primarily in a lower-frequency band (about 0.5-4 Hz) that is more deterministic and thus amenable to separation from superimposed micromotion using multi-sensor processing.

[0074]

[0067] Each optical module 200 is positioned on the inner circumference of the ring body 110 (see Fig. 3) so that, when worn, the module optically couples to user tissue 22. In the illustrated embodiment a module 200 comprises at least one light emitter 11 (e.g., green, red and / or near infrared LEDs) and at least one photodetector 12 (e.g., a silicon photodiode) together with an analog front end (AFE) that includes a transimpedance stage, anti alias filtering and an analog to digital converter (ADC). Modules may be operated in reflective mode using a single Docket: 0396-0022 WO 1 emiter / receiver pair at one location on the finger, or in transmissive mode by activating opposed modules across the inner bore of the ring so that the emitted light traverses the finger and is captured by the receiver on the opposite side. Preferably, to suppress optical crosstalk, only one module (reflective) or one opposed pair (transmissive) is active within a given time slot. In one non limiting example, the emitter wavelength(s) are about 630-680 nm (red) and / or about 810— 940 nm (NIR), the reflective emitter detector spacing is about 2-8 mm, and the transmissive optical path across a finger is about 12-22 mm. In some frames the system acquires two optical channels (e.g., two wavelengths, two geometries or two receivers) so that the more deterministic PPG component can be reduced using cross-channel processing and the more stochastic micromotion component can be emphasized.

[0075]

[0068] The acquisition / scheduler 126A orchestrates which optical modules 200 are active at any instant and with what parameters. The scheduler maintains a pair map identifying, for each transmissive measurement, the transmitter module and the opposed receiver module, while reflective measurements use a single local transmitter / receiver pair. The scheduler also defines the pulse timing for light emission and the sampling instants for detection. In a representative embodiment, the scheduler defines a repeating frame of approximately 40 milliseconds (ms) divided into eight time slots of approximately 5 ms. Within each slot, the active emitter is pulsed for about 0.5-1.5 ms, and the receiver is sampled both during LED on and LED off sub windows; the LED off sample is used as an ambient reference as described below. The scheduler can interleave wavelengths (e.g., red then NIR), geometry (reflective then transmissive), and reference channels acquired in the same or adjacent slots to improve PPG / micromotion separation. The scheduler also controls any duty cycling of modules that are temporarily deactivated to save power or avoid heating, and it can be reconfigured on the fly by the adaptive control block.

[0076]

[0069] Demodulation and subtraction block 126B performs LED synchronous demodulation to reject ambient light and sensor offset. For each channel and wavelength, the processor 126 forms a demodulated sample by subtracting the LED off measurement from the immediately adjacent LED on measurement (i.e., lon-Ioff). In some embodiments, multiple on / off sub samples within a single slot are averaged to reduce quantization and thermal noise. Where the LED is pulsed at a stable repetition rate (e.g., 200-800 Hz at the sub slot level), demodulation and subtraction block 126B may implement lock in detection referenced to the LED drive signal to further suppress out of band ambient flicker such as 50 / 60 Hz lighting. The output of 126B is therefore a time series representing only optical power that is synchronous Docket: 0396-0022 WO 1 with the ring’s emitter(s), suitable for both PPG and micromotion analysis.

[0077]

[0070] Signal normalization block 126C conditions the demodulated stream to account for coupling variation, skin tone, and inter channel crosstalk. When two wavelengths are present, 126C may form a combination (e.g., a linear combination with an adaptively selected coefficient) to reduce energy in the PPG band (about 0.5-4 Hz) before micromotion analysis. In modules with two neighboring receivers, 126C may compute a differential signal between the receivers to cancel global intensity changes and enhance sensitivity to local optical path changes due to micromotion. When two optical channels (e.g., wavelength, geometry or receiver) are acquired, 126C can further apply multi-channel separation to reduce the deterministic PPG component while preserving the random micromotion component, for example by adaptive regression using one channel as a reference, by coherence-based subtraction that attenuates highly coherent content across channels, or by template subtraction using a PPG template provided by the PPG pipeline. The block may further equalize the per channel gain so that data from reflective and transmissive paths are on comparable scales and may output both a conditioned stream and a residual stream emphasizing micromotion.

[0078]

[0071] The optional inertial veto / gating block 126C1 uses the inertial sensors in sensor block S carried by the ring (e.g., a three axis accelerometer and / or gyroscope) to identify and suppress episodes dominated by gross motion that are likely to corrupt both PPG and micromotion estimates. In one embodiment, 126C1 computes the short time energy of the accelerometer signal in the 0-3 Hz band and compares it to a configurable threshold; windows exceeding the threshold are either discarded or down weighted before spectral estimation. In other embodiments, the inertial data are used to decorrelate orientation induced trends from the optical stream by adaptive filtering and to provide context (e.g., rest, posture-holding, or active movement). During voluntary movement, the system can compute an optical-inertial residual by modeling and removing inertial-correlated motion from the optical stream, enabling discrimination between involuntary micromotion during voluntary motion and micromotion at rest.

[0079]

[0072] The PPG pipeline 126D processes the conditioned optical stream to derive hemodynamic parameters. In one implementation the stream is band pass filtered between about 0.5 Hz and about 4 Hz to isolate blood volume pulsatility. Peak / valley detection and morphology analysis provide heart rate (HR), inter beat intervals and heart rate variability (HRV); the perfusion index (PI) may be computed as the ratio of AC to DC amplitude. When two wavelengths are present, PPG pipeline 126D may compute arterial oxygen saturation (SpCh) Docket: 0396-0022 WO 1 using a ratio of ratios method. In embodiments that estimate blood pressure, the pipeline extracts features such as the systolic peak, diastolic foot and dicrotic notch, and applies a calibrated regression or model to obtain a blood pressure estimate. Because the PPG is relatively deterministic and periodic, 126D can also form a PPG template or analytic envelope (e.g., using Hilbert transform or cycle-synchronous averaging) which 126C and / or 126E uses as a reference to further reduce PPG leakage when isolating micromotions. The pipeline maintains a signal quality metric based on pulse periodicity, waveform morphology and agreement across multiple modules / pairs and reports the metric to fusion block 126F.

[0080]

[0073] The micromotion pipeline 126E analyzes the same conditioned optical stream for small, involuntary movements of tissue within a generalized band of about 2-14 Hz. Within this band, the pipeline may compute energy and features in syndrome-targeted sub-bands, including by way of example: about 2.5-7 Hz (often associated with postural / action tremor such as in multiple sclerosis), about 4-6 Hz (resting tremor range often associated with Parkinson’s disease and characteristic “pill -rolling” finger movement), about 4-12 Hz (range observed for fasciculations such as in amyotrophic lateral sclerosis), and about 10-14 Hz (enhanced physiological / stress tremor). Within sliding windows of approximately 2-6 s with 50% overlap, the pipeline computes one or more of: root mean square (RMS) amplitude, Welch power spectral density (PSD), short-time Fourier transform or multi-taper spectra for peak frequency and stability, Hilbert-based analytic amplitude and instantaneous frequency, inter-band ratios, intermittency metrics, and residual energy after PPG suppression. Where two optical sensors are available, 126E can analyze inter-sensor phase and spatial patterns; for example, a spatial phase pattern consistent with a “pill-rolling” movement together with a rest context and a dominant about 4-6 Hz component can be flagged as indicative of a Parkinsonian resting-tremor pattern. Outputs include a micromotion index for the full 2-14 Hz band and optionally sub-indices per targeted sub-band.

[0081]

[0074] Fusion and decision 126F combines outputs from 126D and 126E together with their quality / confidence indicators and, optionally, temperature and the inertial context from 126C1. The block performs thresholding and classification with hysteresis to generate event flags (e.g., “micromotion episode detected,” “high stress index,” “stable PPG for BP estimation”) and continuous scores (e.g., sub-band indices for about 2.5-7 Hz, about 4-6 Hz, about 4-12 Hz, and about 10-14 Hz). Fusion can include outlier rejection across modules or geometries, majority voting, Bayesian combination, or a learned model (e.g., a supervised machine learning classifier) trained to map features to indices while preserving interpretability. By way of non-limiting Docket: 0396-0022 WO 1 examples, the fusion may increase a Parkinsonian index under conditions of limbs at rest with a dominant about 4-6 Hz component and a spatial pattern consistent with “pill-rolling”; may increase a postural / action tremor index when energy concentrates in about 2.5-7 Hz during posture-holding; may increase a stress-tremor index when energy concentrates in about 10- 14 Hz; and may increase an ALS-fasciculation index when broader, arrhythmic content appears in about 4-12 Hz. In preferred embodiments, decisions are expressed as indications or indices that are indicative of physiological states rather than definitive diagnoses.

[0082]

[0075] The adaptive control block 126H maintains measurement quality at low power. Based on the confidence and noise / SNR measures generated upstream, adaptive control block 126H dynamically adjusts one or more acquisition parameters: LED peak current and duty cycle, the set of active modules and their pairings, the slot / frame timing, the choice of wavelength(s), and the reflective vs. transmissive mix. For example, if coupling degrades due to loose fit, adaptive control block 126H can increase LED power within safety limits, select a different pair that currently exhibits higher DC coupling, or temporarily switch to reflective mode. Conversely, when SNR is high, adaptive control block 126H reduces duty cycle to conserve battery and limit heating. The block may also schedule periodic calibration sequences (e.g., brief dual wavelength bursts to re estimate the combination coefficient used in block 126C) and can command the scheduler 126A to perform diagnostic self tests to verify emitter and detector health. In some embodiments, 126H targets context by seeking rest windows (to improve specificity for resting tremor detection) or increasing sampling density during periods likely to exhibit about 10-14 Hz stress tremor.

[0083]

[0076] Upon reaching a decision, the system performs one or more actions via actions block 126J. Actions include, without limitation: (i) logging indices, episode timestamps and quality metrics — including full -band and sub-band (about 2-14 Hz) micromotion indices — to the on board memory M for later retrieval; (ii) wireless transmission of selected data or summaries via the BLE interface to a companion device or cloud service for further analysis or archiving; and (iii) user feedback through the user interface SUI, such as a brief haptic vibration or LED pattern indicating that micromotion above a threshold has been detected, that a high stress index persists, or that the device has initiated a low power or re calibration mode. In some embodiments, 126J can initiate a measurement workflow, for example prompting the user to keep still for a 30 second calibration to disambiguate resting from postural tremor, or requesting a finger reposition to improve coupling. In additional embodiments, actions block 126J can trigger safety or wellness automations defined by the user, such as scheduling a follow up measurement, sharing Docket: 0396-0022 WO 1 a weekly trend report with a designated caregiver, or adjusting the data collection schedule for the remainder of the day. Executing at least one concrete device action in response to detected indices also serves to reduce user burden and supports closed loop operation with actions block 126J.

[0084]

[0077] While this invention has been particularly shown and described with references to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims.

Claims

Docket: 0396-0022 WO 1CLAIMSWhat is claimed is:

1. A wearable device comprising: at least one optical module including a light emitter and optical receiver; and a signal processor configured to: drive the light emitter and acquire signals from the optical receiver; compute a micromotion index from a band-pass including about 4-12 Hz from the acquired signals; and compute a micromotion index from a band-pass including about 2-14 Hz from the acquired signals.

2. The wearable device of claim 1, wherein the signal processor is further configured to drive the light emitter with a pulsed waveform and, for each sample, to subtract a measurement acquired during an emitter-off interval from a measurement acquired during an emitter-on interval to produce a demodulated optical signal substantially free of ambient light.

3. The wearable device of claim 1, wherein computing the micromotion index comprises computing amplitudes in one or more sub-bands within about 2-14 Hz, including at least one of: about 2.5-7 Hz, about 4-6 Hz, about 4-12 Hz, and about 10-14 Hz.

4. The wearable device of claim 1, wherein the optical module comprises emitters of different wavelengths, and wherein the signal processor is further configured to form a combination of signals from the different wavelengths to reduce energy in the 0.5-4 Hz band prior to computing the micromotion index.

5. The wearable device of claim 1, further comprising an inertial sensor, and wherein the signal processor is configured to gate or down-weight analysis of the acquired signals during intervals in which an activity metric derived from the inertial sensor exceeds a threshold.

6. The wearable device of claim 1, wherein the optical module comprises first and second optical receivers at different locations relative to the light emitter, and the signal processor is configured to form a residual signal by removing an inter-receiver correlatedDocket: 0396-0022 WO 1 component from the outputs to suppress a deterministic PPG component and to compute the micromotion index from the residual signal.

7. The wearable device of claim 1, comprising a plurality of optical modules arranged around an inner bore of a ring-shaped body, and wherein the signal processor is configured to select, according to a pairing map, opposed ones of the optical modules to obtain transmissive measurements across a finger and to time-division multiplex operation of the optical modules to avoid optical crosstalk.

8. The wearable device of claim 1, wherein the signal processor is further configured to compute at least one PPG parameter selected from heart rate, heart-rate variability, perfusion index, arterial oxygen saturation, and an estimated blood pressure.

9. The wearable device of claim 1, further comprising a memory and a wireless interface, and wherein the signal processor is configured to store to the memory or transmit via the wireless interface data including the micromotion index together with a timestamp and a confidence measure, and to provide a user feedback through a user interface when the micromotion index satisfies a criterion.

10. A photoplethysmography (PPG) sensor comprising: an optical emitter that transmits a light beam into tissue; an optical detector that detects light from the tissue and outputs an output signal representative of an amplitude of the detected light; an inertial sensor that provides motion data; and an analyzer that receives the output signal and the motion data and that: detects micromotion within a band including about 2-14 Hz and determines at least one of a dominant frequency and a band-limited amplitude in one or more sub-bands including about 2.5-7 Hz, about 4-6 Hz, about 4-12 Hz, and about 10-14 Hz; detects vital signs including any of: heart rate / pulse, blood pressure, and oxygenation; and reports the micromotion and vital signs to a user device and / or a medical facility.

11. A signal analysis method for a wearable device, comprising: drive a light emitter and acquire signals from an optical receiver from tissue of a user;Docket: 0396-0022 WO 1 compute a micromotion index from a band-pass including about 2-14 Hz from the acquired signals; and compute at least one PPG parameter from a band-pass including about 0.5-4 Hz of at least one of the acquired signals.

12. The method of claim 11, wherein driving the light emitter comprises alternately pulsing emitters of different wavelengths, and further comprising forming a linear combination of wavelength-separated signals using a coefficient selected to reduce energy in the 0.5-4 Hz band prior to computing the micromotion index.

13. The method of claim 11, wherein acquiring signals comprises selecting, according to a pairing map, opposed optical modules across an inner bore of a ring body to obtain transmissive measurements and selecting single optical modules to obtain reflective measurements, and further comprising time-division multiplexing operation of the optical modules to avoid optical crosstalk.

14. The method of claim 11, further comprising acquiring inertial sensor data and (i) gating or down-weighting analysis of the acquired signals during intervals in which an activity metric derived from the inertial sensor exceeds a threshold and (ii) distinguishing micromotion during voluntary motion from micromotion at rest using the inertial sensor as a context input and / or by computing an optical-inertial residual.

15. The method of claim 11, wherein computing the at least one PPG parameter comprises determining at least one of heart rate, heart-rate variability, perfusion index, arterial oxygen saturation, and an estimated blood pressure.

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