Example methods, apparatus, and articles of manufacture for monitoring use by a user of a portable research device in accordance with at least one predetermined use criterion are disclosed. The disclosed examples include passively gathering data for assessing an identity of a user of the portable research device, processing the passively gathered data to produce assessment data indicating a possibility that the user is not a predetermined correct user of the portable research device, based on the assessment data, displaying a message to the user requesting a response from which the user's identity may be determined, and processing a response to the message to produce data indicating whether the user is the predetermined correct user.

Described herein are methods and systems for monitoring acoustical activity from the abdominal region to guide the optimal timing of food ingestion. According to one embodiment of the method, the rate of intestinal digestion events, as well as the change in the rate across specific time periods, is analyzed to guide ingestion behavior in a way that improves health. The result of guidance may be to reduce weight in people who are obese, to improve performance in athletes seeking to balance energy availability and energy expenditure, or to increase caloric intake in people who are undernourished. The method can be applied using a smartphone application to provide contextually appropriate and specific user guidance about whether, when, and how much to eat in a manner that aligns with the physiologic patterns of intestinal activity.

Described herein are methods and systems for monitoring acoustical activity from the abdominal region to guide the optimal timing of food ingestion. According to one embodiment of the method, the rate of intestinal digestion events, as well as the change in the rate across specific time periods, is analyzed to guide ingestion behavior in a way that improves health. The result of guidance may be to reduce weight in people who are obese, to improve performance in athletes seeking to balance energy availability and energy expenditure, or to increase caloric intake in people who are undernourished. The method can be applied using a smartphone application to provide contextually appropriate and specific user guidance about whether, when, and how much to eat in a manner that aligns with the physiologic patterns of intestinal activity.

A system can include a foundation structure and a sensor. The foundation structure can have a plurality of deck panels configured to support a mattress. The plurality of deck panels can include a head panel. The plurality of deck panels can have a head, a foot, a first side, and a second side, a first edge along the head, a second edge along the foot opposite of the first edge, a third edge along the first side, and a fourth edge along the second side opposite the third edge. The sensor can be configured to detect a sound indicative of a snore. The sensor can be positioned along the third edge or fourth edge of the head panel.

A ventilation monitoring system for assisting in proper placement of an endotracheal tube in a subject includes: a capnography sensor configured to be placed in fluid communication with the endotracheal tube and to provide information representative of the subject's breath; and a processor in communication with the capnography sensor. The processor is configured to provide an indication of proper endotracheal tube placement when (1) a first indication of the subject's breath and a positive result of a first auscultation are identified within a first predetermined time period, and (2) a second indication of the subject's breath and a positive result of a second auscultation are identified within a second predetermined time period. The first auscultation includes auscultation of a subject's left lung, right lung, left axillary region, right axillary region, or abdomen. The second auscultation includes auscultation of another region of the subject different from the first auscultation.

A system adapted to assisting patients manage asthma includes a wearable sensor for detection of asthma symptoms and inhaler use, having a microphone capable of generating an electrical signal indicative of asthma symptoms or inhaler use; a processor with firmware adapted to process the electrical signal to determine potential asthma symptoms and inhaler use; and store the electrical signal in the memory when the electrical signal potentially corresponds asthma symptoms or inhaler use. In particular embodiments, the system includes an electronic asthma diary including detected asthma symptoms and detected inhaler usage, both with timestamps, and a prescribed treatment protocol. Protocol firmware processes detected asthma symptoms an inhaler usage recorded in the asthma diary to determine if asthma is controlled, and if asthma is not determined controlled determines if a treatment change is authorized; if treatment change is authorized the treatment change is displayed in human-readable form.

Systems and methods are disclosed related to using acoustic waves to detect neural activity in a brain and/or localize the neural activity in the brain. Sensors positioned outside of a skull encasing the brain can detect acoustic waves associated with the neural activity in the brain. From output signals of the sensors, a particular type of neural activity (e.g., a seizure) can be detected. A location of the neural activity can be determined based on outputs of the sensors. In some embodiments, the ultrasound energy can be applied to the location of the neural activity in response to detecting the neural activity.

The present invention relates to a classification system (1) for microprocessor-assisted identification of obstruction types (O1-O4) in sleep apnoea by means of appropriate classification of a snoring-noise signal (Au) to be analysed. The system comprises: a) an input interface for each snoring-noise signal (Au); b) a first classifier (K1) which can be trained such that it identifies and outputs the most probable type of snoring-noise origin (S1-S4) for a particular snoring-noise signal (Au); c) a second classifier (K2) which can be trained such that it identifies and outputs the most probable mouth position (M1-M2) for a particular snoring-noise signal (Au); and d) a third classifier (K3) or linkage matrix, which is designed to identify and output the most probable obstruction type (O1-O4) from the snoring-noise signal (Au) to be analysed, the determined type of snoring-noise origin (S1-S4) and the mouth position (M1-M2) determined therefor.

An infant sleep device may include a platform for supporting an infant, a base upon which the platform is supported, and one or more weight sensors positioned to measure weight of an infant positioned on the platform.

Disclosed are systems and methods for assessing pulmonary health. An example system includes a handheld electronic device (HED); a casing; and at least one circuit board. The HED includes a display screen, a processor, and a software application. The casing includes a plurality of ECG electrodes that are placed on the outer surface of the casing and at least one diaphragm. The ECG electrodes capture the electrophysiological data of the user. The circuit board is configured within the casing and electrically connected with the ECG electrodes and a microcontroller. The circuit board is further connected to at least one sound transducer and at least one Inertial Measurement Unit (IMU) sensor. The sound transducer captures pulmonary signals indicative of pulmonary health. The IMU sensor captures seismic and gyroscope signals indicative of the pulmonary health of the user and the orientation of the casing. The diaphragm enhances the pulmonary audio signals captured by the sound transducer. The microcontroller transmits the pulmonary health data to at least one of the HED and a computing device.