Systems, apparatus, and methods for measuring heart rate are disclosed. An example system includes a transmitter to emit electromagnetic waves; a first sensor to output signals representative of the electromagnetic waves reflected by a subject; a second sensor to generate image data, the image data including data corresponding to a chest of the subject; machine readable instructions; and processor circuitry to at least one of instantiate or execute the machine readable instructions to generate heartbeat data by cancelling harmonics associated with respiration by the subject from data corresponding to the output signals of the first sensor based on the image data, and determine a heart rate for the subject based on the heartbeat data.

A method for measuring a high-accuracy and real-time heart rate based on a continuous-wave radar is provided. The method includes receiving an in-phase (I) signal and a quadrature (Q) signal for a receive signal received through the continuous-wave radar, selecting any one signal by comparing magnitudes of the received I signal and the received Q signal, performing frequency transform of each of bases respectively having predetermined phases with respect to the any one selected signal, and determining a heart rate based on a magnitude response of each of the bases by the frequency transform.

A system for determining peripheral artery disease and method of use for determining the presence or absence of peripheral vascular disease and the severity of the disease in particular vascular segments. The System for determining peripheral artery disease and method of use includes a continuous wave Doppler transceiver which generates a digitized version of quadrature detected stereo audio and is coupleable to a waveform converter and processor. The waveform converter and processor provides filtering, time domain to frequency domain conversion, gain control, and statistical processing of the converted Doppler Stereo audio and is operationally coupled to a display for presenting results to a technician.

An ambulatory medical device including a plurality of sensing electrodes and one or more processors operably coupled to the plurality of sensing electrodes is provided. Each sensing electrodes is configured to be coupled eternally to a patient and to detect one or more ECG signals. The one or more processors are configured to receive at least one electrode-specific digital signal for each of the plurality of sensing electrodes, determine a noise component for each of the electrode-specific digital signals, analyze each of the noise components for each of the plurality of sensing electrodes, generate electrode matching information for each sensing electrode of the plurality of sensing electrodes based upon analysis of each of the noise components, determine one or more sensing electrode pairs based upon the electrode matching information, and monitor each of the one or more sensing electrode pairs for ECG activity of the patient.

Provided is a respiratory state estimating device including a pulse wave signal acquiring unit that acquires a pulse wave signal from a portion of a living subject, a pulse rate calculating unit that calculates a pulse rate of the living subject based on the pulse wave signal, and a respiratory state estimating unit that estimates a respiratory state of the living subject based on the pulse rate. Also, provided is a respiratory state estimating method including optically acquiring a pulse wave signal from a portion of a living subject, calculating a pulse rate of the living subject based on the pulse wave signal, estimating a respiratory state of the living subject from the pulse rate.

A fully automated ultrasound apparatus includes a sensor or probe which can be initially manually attached to a side of the neck of a patient, an ultrasound interface to control the sensor and periodically acquire raw ultrasound data, a signal and image processing system to autonomously convert the raw ultrasound data into a measurement that is useful to physicians, and a display to relay the current measurements and measurement history to provide data trends. The sensor can include one or more ultrasound transducers built into a housing. A disposable component can serve to secure the sensor to the neck of the patient and to provide a coupling medium between the sensor and the skin of the patient.

An MEMS airborne ultrasonic transducer system operating on a thermoacoustic principle to determine brain haemorrhage, includes: an RF transmitter and ultrasound receiver systems to transmit RF energy and receive ultrasound wave, respectively, an RF transmitter system having an RF signal generator, an RF amplifier and a horn antenna, and an ultrasound receiver system having a lock-in amplifier, a DC supply and two ultrasonic transducer arrays wirebonded to low noise amplifier (LNA) chips. The MEMS airborne ultrasonic transducer system determines brain haemorrhage based on detecting RF-induced, blood-originating, thermoacoustic ultrasound wave at the pulse modulation frequency.

A method for predicting the presence of a malady of the respiratory system in a subject comprising: operating at least one electronic processor to transform one or more sounds of the subject that are associated with the malady into corresponding one or more image representations of said sounds; applying said one or more representations to at least one pattern classifier trained to predict the presence of the malady; and operating said processor to predict the presence of the malady in the subject based on at least one output of the at least one pattern classifier.

A method for converting physiological signals includes: obtaining a first signal as a function of a time parameter, wherein the first signal represents electrocardiogram data; obtaining a second signal as a function of the time parameter, wherein the second signal represents physiological data different from the electrocardiogram data; mixing the first signal and the second signal to obtain a mixed signal; and generating a frequency spectrum pertaining to the mixed signal.

One variation of a method for hosting mobile access to dense electroencephalography data includes: receiving a set of signals, in a raw resolution, recorded by a set of channels in an electroencephalography headset during an electroencephalography test; receiving, from a client computing device, a view parameters for viewing the set of signals on a display; calculating a quantity of raw signal points per pixel column of the display based on the view parameters and a length of a segment of the electroencephalography test; for each signal in the set of signals, for each discrete contiguous sequence of the quantity of raw signal points within the segment of the signal, calculating a value set characterizing the discrete contiguous sequence of the quantity of raw signal points in the signal; and generating a static image representing value sets for each channel, in the set of channels, across the segment of the electroencephalography test.