Embodiments of the disclosure include a Radar system for detecting presence of a living thing. The radar system includes a transmitter/receiver module configured to emit radio signals to an environment surrounding the Radar system and to detect returned radio signals from the environment, and a large-movement detection sub-module configured to determine a large movement of the living thing based on the returned radio signals. The radar system also includes a micro-movement detection sub-module configured to determine a micro movement of the living thing based on the returned radio signals, and a breath and heartbeat detection sub-module configured to determine a breath or heartbeat of the living thing based on the returned radio signals. The radar system further includes a presence detection sub-module configured to determine the presence of the living thing based on determinations received from the corresponding detection sub-modules.

Systems and methods are provided to combine multiple stimulation modalities to significantly increase the effectiveness of non-invasive stimulation. Multiple sensor and stimulation devices and modalities can be combined into a single, compact unit that minimizes the need for additional sensors or stimulation devices. The system features several subunits, referred to as sensory and stimulation devices (SSD), that are integrated into a headphone setup. The system is controlled by a centralized controller that communicates with all of the SSDs and with an external computer system that delivers learning material synchronized with the delivery of stimulations and the collection of user responses based on physiological signals.

A method and system are provided for estimating a physiological parameter using a parameter model determined by a deep neural network. An example method includes training a deep neural network with indirect and direct physiological parameters from a user database. The medical parameters include a respiratory rate, oxygen saturation, temperature, blood pressure, and pulse rate. The method includes determining if a new user belongs in a group. If the parameter model estimated physiological parameter using the closest group to the new user and associated calibration, then the method quantizes the parameter inputs to determine which physiological parameter a new user is most sensitive and to determine a new group and calibration coefficients or curves for the new user.

An imaging system, comprising a shooting operation interface that operates to form an image of a subject, and a processor that has a bio-information acquisition section and a stress determination section, wherein the bio-information acquisition section acquires bio-information of an operator when, during shooting awaiting action where an instant for acquiring still images is awaited, the shooting operation interface is operated, and the stress determination section determines stress conditions that shooting actions place on the operator based on the bio-information that has been acquired using the bio-information acquisition section.

The invention provides a system and method for measuring vital signs (e.g. SYS, DIA, SpO2, heart rate, and respiratory rate) and motion (e.g. activity level, posture, degree of motion, and arm height) from a patient. The system features: (i) first and second sensors configured to independently generate time-dependent waveforms indicative of one or more contractile properties of the patient's heart; and (ii) at least three motion-detecting sensors positioned on the forearm, upper arm, and a body location other than the forearm or upper arm of the patient. Each motion-detecting sensor generates at least one time-dependent motion waveform indicative of motion of the location on the patient's body to which it is affixed. A processing component, typically worn on the patient's body and featuring a microprocessor, receives the time-dependent waveforms generated by the different sensors and processes them to determine: (i) a pulse transit time calculated using a time difference between features in two separate time-dependent waveforms, (ii) a blood pressure value calculated from the time difference, and (iii) a motion parameter calculated from at least one motion waveform.

A dynamic wake-up alarm is provided-for, including a clock, a contactless biometric sensor, a processor, memory, and a speaker. The processor may be configured to receive a wake-up rule based on at least two wake-up criteria including a time from the clock and data from the biometric sensor, and evaluate whether the criteria are met to activate an alarm.

A biofeedback headset for providing input to and receiving output from an information handling system may include a controller to send and receive audio signals to and from the information handling system and send biofeedback signals to the information handling system; one or more speakers mounted to a wearable head band to provide audio output from the information handling system to a user; and a mouthpiece operatively coupled to the wearable headband including: a microphone to receive audio input from the user; a pressure sensor to detect a breathing rate and amplitude of the user and, with the controller, provide breathing rate and amplitude biofeedback signals to the information handling system; and a gas sensor to detect a composition of air at the mouthpiece as the user respirates and, with the controller, provide air composition biofeedback signals to the information handling system.

An emergency cardiac and electrocardiogram (ECG) electrode placement device with artificial intelligence is disclosed herein. The emergency cardiac and electrocardiogram (ECG) electrode placement device incorporates electrical conducting materials and elastic material into a pad that is applied to a chest wall of a patient, which places multiple electrodes in the appropriate anatomic locations on the patient to quickly obtain an ECG in a pre-hospital setting. The AI program continuously runs EKGs to continuously monitor a patient.

The present invention relates to physiological signal processing, and in particular to methods and systems for processing physiological signals to predict a fluid responsiveness of a patient. A medical monitor for monitoring a patient includes an input receiving a photoplethysmograph (PPG) signal representing light absorption by a patient's tissue. The monitor also includes a perfusion status indicator indicating a perfusion status of the PPG signal, and a fluid responsiveness predictor (FRP) calculator programmed to calculate an FRP value based on a respiratory variation of the PPG signal. The FRP calculator applies a correction factor based on the perfusion status indicator.

An article of clothing includes user-protection circuitry, integrated into the article of clothing. The user-protection circuitry includes condition-detection circuitry, which, in operation, generates one or more indications related to an environment of the article of clothing. The user-protection circuitry also includes broadcast circuitry including at least one pulsing device, and control circuitry. The control circuitry, in operation, activates the broadcast circuitry based on the one or more indications related to the environment of the article of clothing generated by the condition-detection circuitry.