A system for acoustically monitoring a heartbeat includes an acoustic body having a first material in contact with a second material, a density and a propagation speed of sound of the first material is matched with a density and a propagation speed of sound of a human body, and a density and a propagation speed of sound of the second material is matched with the density and the propagation speed of sound of the first material, a covering material in contact with a first surface of the acoustic body formed by the first material, and a microphone acoustically coupled to a second surface of the acoustic body formed by the second material.

A system for acoustically monitoring a heartbeat includes an acoustic body having a first material in contact with a second material, a density and a propagation speed of sound of the first material is matched with a density and a propagation speed of sound of a human body, and a density and a propagation speed of sound of the second material is matched with the density and the propagation speed of sound of the first material, a covering material in contact with a first surface of the acoustic body formed by the first material, and a microphone acoustically coupled to a second surface of the acoustic body formed by the second material.

Controlled-environment facility resident behavioral and/or health monitoring may employ controlled-environment facility resident wearables each having a band configured to be affixed around a portion of a controlled-environment facility resident, irremovable by the resident and may include sensor(s) configured to measure biometric(s) of the controlled-environment facility resident and one or more physical parameter(s) experienced by the wearable, with a transmitter transmitting the biometric(s) and/or the physical parameter(s) to a controlled-environment facility management system. The controlled-environment facility management system may predetermine one or more normal input levels of the biometric(s) and/or physical parameter(s), receive the transmitted biometric(s) and/or physical parameter(s), determine whether received biometric(s) and/or physical parameter(s) rises above or falls below the predetermined normal input level(s), and alert controlled-environment facility personnel and/or law enforcement when received physical parameter(s) and/or received biometric(s) rise above or fall below the predetermined normal input level(s).

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.

In one aspect of the disclosure, a method that involves keeping state of a video workout program may include communicatively coupling a server in a cloud network to an exercise machine through a first network connection, communicatively coupling the server to a network device through a second network connection, the server providing a video workout program to the exercise machine for execution at the exercise machine to enable a user to perform at least a portion of a workout of the video workout program on the exercise machine, the server keeping state of the video workout program during execution of the video workout program based on inputs from the exercise machine and the network device, and taking an action based on the state. The action may include synchronizing multiple displays, adaptively scaling the video workout program, and/or generating and providing an exercise machine control command to the exercise machine.

In one aspect of the disclosure, a method that involves keeping state of a video workout program may include communicatively coupling a server in a cloud network to an exercise machine through a first network connection, communicatively coupling the server to a network device through a second network connection, the server providing a video workout program to the exercise machine for execution at the exercise machine to enable a user to perform at least a portion of a workout of the video workout program on the exercise machine, the server keeping state of the video workout program during execution of the video workout program based on inputs from the exercise machine and the network device, and taking an action based on the state. The action may include synchronizing multiple displays, adaptively scaling the video workout program, and/or generating and providing an exercise machine control command to the exercise machine.

Systems and methods for detecting data acquisition conditions using color-based penalties can include a computing device obtaining a sequence of images acquired by a photodetector. The computing device can determine, for each pixel position of a plurality of pixel positions associated with the sequence of images, a respective penalty score indicative of a similarity between a color value of a pixel of the pixel position and a desired color value. The desired color value can represent a color property of light emitted from body parts of users when placed opposite to the photodetector. The computing device can determine, using penalty scores of the plurality of pixel positions, a relative position of a body part of a user with respect to a desired position.

An adjustable measurement device is described that may include a housing, a power supply, a processor, a communication device, an elastic coupling member, a physiological sensor, and/or a clamp. The housing may be configured to attach to a wearable band that is wearable by a subject. The housing may include a chamber within the housing. The power supply, the processor, the communication device, the elastic coupling member, and or the physiological sensor may be disposed within the chamber. The elastic coupling member may couple the physiological sensor to the housing. A force exerted by the elastic coupling member on the physiological sensor may be in a direction through an opening towards a body part of a subject. As the subject wears the wearable band and the housing is coupled to the wearable band, the physiological sensor may be adjacent to or contact the subject.

Systems and methods for blood pressure estimation using smart offset calibration can include a computing device associating a calibration photoplethysmographic (PPG) signal generated from a first sequence of image frames obtained from a photodetector of the computing device with one or more measurement values generated by a blood pressure measurement device different from the computing device. The computing device can obtain a recording PPG signal generated from a second sequence of image frames obtained from the photodetector, and identify a calibration model from a plurality of blood pressure calibration models based on the calibration PPG signal and the recording PPG signal. The computing device can generate a calibrated blood pressure value using the recording PPG signal, features associated with the calibration PPG signal and the identified calibration model.

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.