An integrated cardio-respiratory system that fuses continuously recorded data from multiple physiological sensor sources to acquire signals representative of acoustic events caused by physiological phenomena occurring in the cardiac and/or arterial structures underneath particular areas of the chest and/or neck to monitor cardiac and respiratory conditions.

Systems and methods are provided that provide respiration entrainment cues to a user to encourage relaxation or a sleep state. The entrainment cues may be audible, visible, or tactile (or any combination). The entrainment cues include a rhythmic component associated with a target respiration rate and may include sub-components associated with a target breath architecture, such as an inhale-exhale cycle. The systems and methods detect the user's respiration to determine whether the user's respiration matches the entrainment cues or whether the user has fallen asleep.

This document discusses, among other things, systems and methods to generate a first pacing waveform during a first pacing period and a second pacing waveform during a second pacing period, and alternate the first and second pacing periods to provide pacing-based hypertension therapy to a heart of a patient to reduce patient blood pressure, wherein the first pacing waveform has a first atrioventricular (AV) delay and the second pacing waveform has a second AV delay longer than the first AV delay. Physiologic information can be received from the patient, and one of the first or second pacing period for delivery to the patient can be determined using the received physiologic information.

This document discusses, among other things, systems and methods to generate a first pacing waveform during a first pacing period and a second pacing waveform during a second pacing period, and alternate the first and second pacing periods to provide pacing-based hypertension therapy to a heart of a patient to reduce patient blood pressure, wherein the first pacing waveform has a first atrioventricular (AV) delay and the second pacing waveform has a second AV delay longer than the first AV delay. Physiologic information can be received from the patient, and one of the first or second pacing period for delivery to the patient can be determined using the received physiologic information.

There are provided a biological signal measurement device capable of obtaining a variety of biological information and applicable also to medical fields and the like, a biological state inference device, and a biological state inference system using these. The biological signal measurement device 1 of the present invention includes three biological signal detection units, namely, a left upper part biological signal detection unit 11, a right upper part biological signal detection unit 12, and a lower part biological signal detection unit 13. The biological state inference device 1 is capable of obtaining a highly precise inference-use processed waveform from which electrical noise has been removed, by using an appropriate combination of time-series data obtained from the three biological signal detection units 11 to 13. Because the precision of an inference-use processed waveform corresponding to target biological information on breathing, heart sound, or the like increases, the precision of inferring a biological state also increases.

Methods, devices and systems for predicting non-clinical, undiagnosed conditions through audio data related to intestinal sounds of a patient or subject, wherein the methods, devices and systems utilize machine learning algorithms, and predicting the likelihood of in vivo impairment relative to the identified spectral events.

Wearable fetal health monitoring device for determining a heath condition of a fetus based on biosignals of an expecting mother and the fetus is provided. The device includes a MEMS accelerometer that converts an acoustic wave sensed in an abdominal region into an abdominal acoustic signal. The device also includes a pulse oximeter generates a maternal photoplethysmogram (mPPG) value from a pulse sensed in the abdominal region. The device further includes a microcontroller configured to: generate a maternal phonocardiogram (mPCG) value from the abdominal acoustic signal; calculate a first maternal heart rate (mHR) value from the mPCG value; calculate a second mHR value from the mPPG value; compare the first mHR value with the second mHR value to identify a noise correction value; and apply the identified noise correction value to the mPCG value to extract a fetal phonocardiogram (fPCG) value.

Methods and systems are provided for diagnosis and possibly treatment of the large intestine, using samples from at least three portions of the large intestine, including sampling the ascending proximal portion thereof. Samples from the ascending portions of the large intestine were found to differ in their microbial characteristics significantly from prior art stool samples and from samples taken from the descending and transverse parts of the large intestine—enabling more accurate diagnosis and possibly more effective treatment of diseases of the large intestine.

A physiological acoustic monitoring system receives physiological data from an acoustic sensor, down-samples the data to generate raw audio of breathing sounds and compresses the raw audio. The acoustic monitoring system has an acoustic sensor signal responsive to tracheal sounds in a person. An A/D converter is responsive to the sensor signal so as to generate breathing sound data. A decimation filter and mixer down-samples the breathing sound data to raw audio data. A coder/compressor generates compressed audio data from the raw audio data. A decoder/decompressor decodes and decompresses the compressed audio data into decompressed audio data. The decompressed audio data is utilized to generate respiration-related parameters in real-time. The compressed audio data is stored and retrieved so as to generate respiration-related parameters in non-real-time. The real-time and non-real-time parameters are compared to verify matching results across multiple monitors.

A method and apparatus for the treatment of Sleep Apnea events and Hypopnea episodes wherein one embodiment comprises a wearable, belt like apparatus containing a microphone and a plethysmograph. The microphone and plethysmograph generate signals that are representative of physiological aspects of respiration, and the signals are transferred to an imbedded computer. The embedded computer extracts the sound of breathing and the sound of the heart beat by Digital Signal Processing techniques. The embedded computer has elements for determining when respiration parameters falls out of defined boundaries for said respiration parameters. This exemplary method provides real-time detection of the onset of a Sleep Apnea event or Hypopnea episode and supplies stimulation signals upon the determination of a Sleep Apnea event or Hypopnea episode to initiate an inhalation. In one embodiment, the stimulus is applied to the patient by a cutaneous rumble effects actuator and/or audio effects broadcasting.