A wearable medical device, comprising: a garment configured to be worn about a torso of a patient; one or more sensors for detecting a characteristic of a cardiopulmonary resuscitation (CPR) therapy; an output device; and a processor configured for processing information from the one or more sensors and providing, to the output device, information about the CPR therapy, wherein at least one of the one or more sensors is movably attached to the garment, the at least one sensor configured to be positioned to the center of the patient's chest prior to initiation of the CPR therapy.

An example accessory for an inhaler includes: a housing to couple to the inhaler; an accelerometer disposed in the housing, the accelerometer to obtain (i) motion data representing motion of the inhaler and (ii) orientation data representing an orientation of the inhaler; a microphone disposed in the housing, the microphone to obtain audio data for determining an inhalation rate of a user of the inhaler; a force sensor disposed in the housing, the force sensor to obtain force data representing force applied to the accessory; a communications interface disposed in the housing; a memory disposed in the housing; and a processor disposed in the housing, the processor interconnected with the communications interface and the memory the processor to: detect actuation of the inhaler based on the force data applied to the accessory; and generate dosage administration data based on the motion data, the orientation data and the audio data.

Respiratory-based biofeedback devices, systems, and methods are provided. A respiratory biofeedback method includes producing a respiratory signal in response to a user's respiratory activity, generating an audio output signal that includes a modified version of the respiratory signal, and converting the audio output signal into sound waves output to the user to provide biofeedback. The sound waves can be output to the user in real time response to the user's respiratory activity. A microphone can be used to generate the respiratory signal. The generated audio output signal can includes the respiratory signal modified to increase a volume level of a portion of the respiratory signal where the volume level exceeds a specified volume level.

A ceiling artificial intelligence (AI) health monitoring system, includes a monitoring device provided on a ceiling of a space to acquire health information from a patient, and a medical management device configured to apply the health information of the patient acquired to an artificial intelligence-based learning model to determine health condition information of the patient and provide the determination result to a doctor monitor. The medical management device is configured to provide remote medical diagnosis information from the doctor monitor to a user terminal.

An anti-snoring system comprising an adjustable bed having a sleeping surface that may be mechanically raised or lowered, and a control module adapted to receive commands from a source external to the adjustable bed; a mobile device in direct or indirect communication with the control module in the adjustable bed, and wherein the mobile device has sound recording capabilities; a mobile application resident on the mobile device, wherein the mobile application includes a sound classification machine learning model that includes an artificial intelligence or neural network operative to determine whether or not a person on the sleep surface is snoring, and wherein upon a determination that the person is snoring and has been snoring for a predetermined period of time, the mobile application instructs the control module to raise or adjust the sleeping surface to a height or position that will discourage the person from snoring.

Embodiments described herein include sensors and sensor systems having probe-off detection features. For example, sensors and physiological monitors described herein include hardware and/or software capable of providing an indication of the integrity of the connection between the sensor and the patient. In various embodiments, the physiological monitor is configured to output an indication of a probe-off condition for an acoustic sensor (or other type of sensor). For example, in an embodiment, a signal from an acoustic sensor is compared with a signal from a second sensor to determine a probe-off condition.

The utility model relates to a device for measuring the heartbeat, respiration, and body temperature of a human body, comprising of a shell and a base, wherein a PCB board, a buzzer, and a multi-point infrared temperature sensor and a camera are arranged in the shell. The infrared temperature sensor is used for temperature sampling of M×N sampling points, where M≧3, N≧3, and the camera is used for acquiring the video image of the measured object.

Detecting chronotropic incompetence includes determining, using a processor, a baseline cardiac health measure for a user based upon an estimate of activity level for the user, validating, using the processor, the estimate of activity level for the user with a validation factor determined from sensor data and determining, using the processor, a cardiac health measure for the user from the sensor data. A signal indicating chronotropic incompetence for the user can be provided by the processor based upon a comparison of the cardiac health measure for the user with the baseline cardiac health measure.

An electronic device and a smart method for controlling an alarm are provided. The smart method includes, controlling a collection device to collect physiological parameters of a user when an alarm device of the electronic device sounds an alarm at a schedules time, obtaining the physiological parameters collected by the collection device, and determining whether the user is asleep or awake according to the obtained physiological parameters. The alarm device is disabled if the user is awake.

A system comprising a remotely programmable micromonitor with a wireless sensing system-on-module (SOM), one or more sensors to detect one or more conditions in a subject by monitoring one or more parameters associated with the conditions by comparing any monitored parameter to a baseline measurement of the monitored parameter from the subject, a plurality of sensors corresponding to a monitored parameter and connected to the micromonitor to convey measurements of all monitored parameters, the sensors including at least one of a non-optical pulse wave sensor or an electrocardiogram (ECG) sensor, a communications module capable of communicating with a wireless technology, wherein the module can send an alert signal to the subject or an attending physician or a remote service center or any other subject, and one or more algorithms for monitoring conditions and/or for predicting conditions, including at least one of a fall detection or fall prediction algorithm.