The present disclosure relates to noninvasive methods, devices, and systems for measuring various blood constituents or analytes, such as glucose. In an embodiment, a light source comprises LEDs and super-luminescent LEDs. The light source emits light at at least wavelengths of about 1610 nm, about 1640 nm, and about 1665 nm. In an embodiment, the detector comprises a plurality of photodetectors arranged in a special geometry comprising one of a substantially linear substantially equal spaced geometry, a substantially linear substantially non-equal spaced geometry, and a substantially grid geometry.

A system includes a memory storing a user profile for a user of the system and machine-readable instructions and a control system including one or more processors configured to execute the machine-readable instructions to receive physiological data associated with the user during a sleep session, determine, based at least in part on the received physiological data, a set of sleep-related parameters for the sleep session, subsequent to the sleep session, select one of the set of sleep-related parameters as a targeted parameter, the selection of the targeted parameter being based at least in part on the stored user profile, the set of sleep-related parameters, or both, and cause information to be communicated to the user via a user device, the information being indicative of the targeted parameter, a recommendation associated with improving the targeted parameter for the user in one or more subsequent sleep sessions, or both.

The conversion adapter is provided that includes a radio communication unit that receives biological information based on the digital data transmitted from an external biological sensor by using radio communication; an information processing unit that performs data processing of the biological information based on the digital data; a converter that converts the biological information based on the digital data processed by the information processing unit to biological information based on analog data; and a connection unit that is connectable through wire to an external biological information monitor and that outputs the biological information based on the analog data converted by the converter.

A method for checking a PPG sensor of a hearing apparatus that has a rechargeable battery. A charger has a receiving space for the hearing apparatus and a testing environment for testing the functionality of the PPG sensor. The hearing apparatus is placed in the receiving space and the test environment is used to perform a function test on the PPG sensor.

A biological-measurement device includes a light-emitting unit configured to emit light on a body of a test-subject, a light-detecting unit configured to detect light reflected in the body of the test-subject, a control-unit configured to calculate information regarding a pulse-wave of the body of the test-subject based on the light detected by the light-detecting unit, a circuit-board that is flexible and has a first-surface on which the light-emitting unit and the light-detecting unit are provided, the circuit-board further having wiring connecting the light-emitting unit and the control-unit together and connecting the light-detecting unit and the control-unit together, a shielding-unit that is provided on the first-surface, the shielding-unit being situated between the light-emitting unit and the light-detecting unit and configured to protrude beyond the light-emitting unit and the light-detecting unit in a direction perpendicular to the first-surface, and an adhesive-part for firmly contacting with the body of the test-subject.

A physiological monitoring device is provided and includes a physiological sensing device, a first PPG sensor, a vital signs detector, and a PPG controller. The physiological sensing device senses at least one physiological feature of a subject to generate at least one sensing signal. The first PPG sensor senses pulses of a blood vessel of the subject to generate a first PPG signal when the first PPG sensor is activated. The vital signs detector obtains vital signs data according to the at least one sensing signal. The PPG controller detects whether a specific event is happening to the subject according to the vital signs data. In response to detecting that the specific event is happening to the subject, the PPG controller activates the first PPG sensor. The physiological monitoring apparatus obtains a blood oxygen level of the subject according to the first PPG signal.

A method of generating a model for generating a synthetic electrocardiography (ECG) signal comprises: receiving subject-specific training data for machine learning, said training data comprising a photoplethysmography (PPG) signal acquired from the subject and an ECG signal acquired from the subject, wherein the ECG signal provides a ground truth of the subject for associating the ECG signal with the PPG signal; using associated pairs of a time-series of the PPG signal and a corresponding time-series of the ECG signal as input to a deep neural network, DNN; and determining, through the DNN, a subject-specific model relating the PPG signal of the subject to the ECG signal of the subject for converting the PPG signal to a synthetic ECG signal using the subject-specific model.

Provided are a brain stimulation system, method, apparatus and storage medium based on artificial intelligence. The system includes: a plurality of brain stimulation terminals and a cloud platform. The cloud platform is configured to, with artificial intelligence algorithm especially machine learning and deep learning, generate multi-dimensional psychological big data using physiological data and psychological state evaluation parameters gotten from the plurality of brain stimulation terminals and established models of algorithm for disease diagnosis. The brain stimulation terminal is configured to analyze the physiological data and psychological state evaluation parameters of a target subject, measure a mental state of the target subject, obtain brain stimulation parameters required for the target subject according to the mental state, and generate corresponding non-invasive brain stimulation for the target subject according to the brain stimulation parameters based on the multi-dimensional big data through the artificial intelligence algorithm.

An apparatus and method for detecting a bio-signal feature are provided. The apparatus according to one aspect may include: a bio-signal acquirer configured to acquire a bio-signal; and a processor configured to generate an envelope signal of the bio-signal, and detect at least one feature of the bio-signal based on a difference between the envelope signal and the bio-signal.

Embodiments herein relate to reflective optical medical sensor devices. In an embodiment, a reflective optical medical sensor device including a central optical detector and a plurality of light emitter units disposed around the central optical detector is provided. A plurality of peripheral optical detectors can be disposed to the outside of the plurality of light emitter units. Each of the plurality of peripheral optical detectors can form a channel pair with one of the plurality of light emitter units. The reflective optical medical sensor device can also include a controller in electrical communication with the central optical detector, the light emitter units, and the peripheral optical detectors. The controller can be configured to measure performance of channel pairs; select a particular channel pair; and measure a physiological parameter using the selected channel pair. Other embodiments are also included herein.