Abstract: Systems and methods for analyzing a blood volume signal are described. In an example, the method comprises extracting self-normalized features from blood volume signals within a signal window; generating a signal quality prediction based on the self-normalized features to provide a quality prediction score, wherein the quality prediction score is between an upper bound and a lower bound; and generating a health metric score based on the blood volume signals in the signal window if the quality prediction score is above a predetermined threshold. In an example, the blood volume signals are photoplethysmography (PPG) signals. In an example, the method includes identifying a signal quality issue if the quality prediction score is below the predetermined threshold.

Abstract: A technique of estimating a continuous heart rate of a subject includes acquiring pulsatility data indicative of a cardiac cycle of the subject and motion data indicative of a motion of the subject. Frequency transformations are performed on the pulsatility and motion data over discrete windows of temporal length T to generate a set of windowed spectra. The discrete windows are temporally overlapping and each temporally offset from one another. Heart rate values, each corresponding to one of the windowed spectra, are output using a processing pipeline including one or more neural networks trained to collectively output one of the heart rate values for each windowed spectra. The continuous heart rate is estimated based upon a set of the heart rate values from the discrete windows that are temporally overlapping.

Abstract: In some embodiments, a computer-implemented method of measuring heart rate analytics using raw photoplethysmography (PPG) data is provided. A computing system determines a plurality of frequency peaks in the raw PPG data using a Fourier analysis. The computing system determines a plurality of selected frequency peaks from the plurality of frequency peaks. For each selected frequency peak of the plurality of selected frequency peaks, the computing system creates filtered PPG data by applying a frequency of the selected frequency peak as a high-pass filter to the raw PPG data; detects diastole peaks and systole valleys in the filtered PPG data; and performs one or more pulse quality checks on the detected diastole peaks and systole valleys. The computing system uses diastole peaks and systole valleys associated with a lowest selected frequency peak that passed the pulse quality checks to determine a heart rate analytic measurement.

Abstract: Accuracy of vital signs monitoring systems depend on the quality of the measurements by the sensors. Crude techniques are applied to discard measurements which have a low signal-to-noise ratio or are saturated. A more accurate and flexible technique enables more measurements to be kept, more meaningful signal quality information to be extracted, more accurate vital signs extraction and more systems to readily embed signal quality assessment in the signal processing pipeline. Improvements include preprocessing of the signal that is independent of variations of underlying hardware, use of features with low computational complexity and high predictive power, cross-channel feature extraction, application of a trained machine learning model, and flexible translation of signal quality classification information into a continuous metric for signal quality.

Abstract: System and apparatus for pulse oximetry. Systems, methods, and devices are presented for placement of the hardware on a body part where detracting signals are strong. In one example, detracting signals include signals from respiration. In various examples, the body part the oximeter is placed on is a wrist, chest, or arm. A computationally efficient pipeline is presented that allows for reliable and robust SpO2 estimation.