Abstract: Activity monitors and smart watches utilizing optical measurements are becoming widely popular, and users expect to get an increasingly accurate estimate of their heart rate (HR) from these devices. These devices are equipped with a light source and an optical sensor which enable estimation of HR using a technique called photoplethysmography (PPG). One of the main challenges of HR estimation using PPG is the coupling of motion into the optical PPG signal when the user is moving randomly or exercising. The present disclosure describes a computationally feasible and fast HR estimation algorithm to be executed at instances of little or no motion. Resulting HR readings may be useful on their own, or be provided to systems that monitor HR continuously to prevent the problem of such systems being locked on an incorrect HR for long periods of time. Implementing techniques described herein leads to more accurate HR measurements.

Abstract: Embodiments of the present disclosure provide mechanisms that enable designing an FIR filter that would have a guaranteed globally optimal magnitude response in terms of the minimax optimality criterion given a desired weight on the error in the stopband versus the passband. Design of such a filter is based on a theorem (“characterization theorem”) that provides an approach for characterizing the global minimax optimality of a given FIR filter h[n], n=0, 1, . . . , N, where optimality is evaluated with respect to a magnitude response of this filter, |H(ej?)|, as compared to the desired filter response, D(?), which is unity in the passband and zero in the stopband. The characterization theorem enables characterizing optimality for both real-valued and complex-valued filter coefficients, and does not require any symmetry in the coefficients, thus being applicable to all non-linear phase FIR filters.

Abstract: Aspects of the embodiments are directed to passive depth determination. Initially, a high power depth map of a scene can be created. An object in the scene can be identified, such as a rigid body or other object or portion of an object. A series of lower power or RGB images can be captured. The object can be located in one or more of the lower power or RGB images. A change in the position of an object, represented by a set of pixels, can be determined. From the change in position of the object, a new depth of the object can be extrapolated. The extrapolated depth of the object can be used to update the high power depth map.

Abstract: Heart rate monitors are plagued by noisy photoplethysmography (PPG) data, which makes it difficult for the monitors to output a consistently accurate heart rate reading. Noise is often caused by motion. Using known methods for processing accelerometer readings that measure movement to filter out some of this noise may help, but not always. The present disclosure describes an improved filtering approach, referred to herein as an iterative frequency-domain mask estimation technique, based on using frequency-domain representation (e.g. STFT) of PPG data and accelerometer data for each accelerometer channel to generate filters for filtering the PPG signal from motion-related artifacts prior to tracking frequency of the heartbeat (heart rate). Implementing this technique leads to more accurate heart rate measurements.

Abstract: Heart rate monitors are plagued by noisy photoplethysmography (PPG) data, which makes it difficult for the monitors to output a consistently accurate heart rate reading. Noise is often caused by motion. Using known methods for processing accelerometer readings that measure movement to filter out some of this noise may help, but not always. The present disclosure describes an improved front-end technique (time-domain interference removal) based on using adaptive linear prediction on accelerometer data to generate filters for filtering the PPG signal prior to tracking the frequency of the heartbeat (heart rate). The present disclosure also describes an improved back-end technique based on steering the frequency of a resonant filter in order to track the heartbeat. Implementing one or both of these techniques leads to more accurate heart rate measurements.

Abstract: Heart rate monitors are plagued by noisy photoplethysmography (PPG) data, which makes it difficult for the monitors to output a consistently accurate heart rate reading. Noise is often caused by motion. Using known methods for processing accelerometer readings that measure movement to filter out some of this noise may help, but not always. The present disclosure describes an improved front-end technique (time-domain interference removal) based on using adaptive linear prediction on accelerometer data to generate filters for filtering the PPG signal prior to tracking the frequency of the heartbeat (heart rate). The present disclosure also describes an improved back-end technique based on steering the frequency of a resonant filter in order to track the heartbeat. Implementing one or both of these techniques leads to more accurate heart rate measurements.

Abstract: A method for detecting unbalance in a 3-phase voltage signal is disclosed. The method includes determining an unbalance indicator as a value of a square of an amplitude of a positive sequence of the voltage signal; and comparing the unbalance indicator with a threshold to determine unbalance of the voltage signal.