Abstract: A system for measuring long-distance respiration rate is provided. The system includes a processing unit configured to receive and normalized a sensor output signal. The processing unit is further configured to compute a series of four Discrete Prolate Spheroid window functions. For each of the series of four Discrete Prolate Spheroid window functions, the processing unit is configured to (1) multiply the normalized sensor output signal by the Discrete Prolate Spheroid window function to produce a windowed output signal, and (2) compute a Lomb-Scargle periodogram based on the windowed output signal. The processing unit is further configured to compute a weighted average of the Lomb-Scargle periodograms to produce an averaged periodogram. The processing unit is further configured to compute a frequency corresponding to a peak estimated spectral density on the averaged periodogram. The processing unit is further configured to output breaths per minute data based on the frequency.

Abstract: A system for estimating respiration rate is provided. The system includes an audio sensor, a displacement sensor, and a processing unit. The audio sensor, such as a parabolic microphone, produces an audio recording signal. The displacement sensor, such as a camera or laser rangefinder, produces a chest movement signal. The processing unit receives the audio recording signal and the chest movement signal. The processing unit computes an estimated audio respiration rate based on the audio recording signal and an estimated displacement respiration rate based on the chest movement signal. The processing unit computes an audio signal quality index for the audio recording signal and a displacement signal quality index for the chest movement signal. The processing unit determines a fused estimated respiration rate by fusing the estimated audio respiration rate with the estimated displacement respiration rate. The fusing is based on the audio and displacement signal quality indexes.

Abstract: A method for reporting a user's risk of infection, comprising: (i) receiving, from a sensor of a wearable device worn by the user, user heart data; (ii) determining, from the received user heart data by a pulse rate variability phase acceleration algorithm, the user's pulse rate variability phase acceleration values for the first time period; (iii) determining, from the received user heart data by a pulse rate variability phase deceleration algorithm, the user's pulse rate variability phase deceleration values for the first time period; (iv) determining, by a trained infection risk prediction algorithm using the user's pulse rate variability phase acceleration values and the user's pulse rate variability phase deceleration values for the first time period, the user's risk of a current infection; and (v) providing, via a user interface, the determined user's risk of a current infection.

Abstract: A controller (150) for waveform-based hemodynamic instability warning includes a memory (151) that stores instructions and a processor (152) that executes the instructions.