A biological information processor including a biological information estimating unit that estimates biological information on a subject in a second period on the basis of a correlation between a first parameter in a first period and biological information in the first period and the first parameter in the second period subsequent to the first period, the first parameter being acquired in advance for the subject.

An electronic device determining a vital sign while a user is active is provided. The electronic device includes a first sensor for detecting a vital sign of a user, second sensor for detecting an activity of the user, and at least one processor connected to the first sensor and the second sensor. The at least one processor may be configured to identify the vital sign determined through a first signal obtained through the first sensor, normalize the vital sign to correspond to an activity characteristic of the user based on the vital sign determined through the first signal and an activity level of the user determined through a second signal obtained through the second sensor, and determine a merged vital sign by merging the vital sign determined through the first signal and a normalized vital sign.

A wearable device for tracking swim activities of a user is provided. The wearable device may include one or more sensors configured to generate sensor data, and based on the sensor data, the wearable device may determine swim metrics such as swim stroke count, swim stroke type, swim lap count, and swim speed. The determined swim metrics may be filtered based on one or more swim periods during which the user is likely to have been swimming. The wearable device may determine such swim periods based on the sensor data and/or the determined swim metrics.

A monitoring system a user activity sensor to determine patterns of activity based upon the user activity occurring over time.

The present disclosure presents at least one communication interface for prediction of data related to health conditions, wherein the at least one communication interface is configured to receive health-related data, preferably comprising measurement data, from a first user device of a first user, associated with a first time and a first location. The at least one communication interface additionally comprises at least one processor configured to utilize said received health-related data to generate predictive data to be indicated to a second user device of a second user associated with a second time and a second location.

Hearing aid system comprising at least one hearing aid is provided. The hearing aid system further comprising an input unit for receiving an input sound signal from an environment of the hearing aid user and providing at least one electric input signal representing said input sound signal, an output unit for providing at least one set of stimuli perceivable as sound to the hearing aid user based on processed versions of said at least one electric input signal, a processing unit connected to said input unit and to said output unit and comprising signal processing parameters to provide said processed versions of said at least one electric input signal, at least one photoplethysmogram (PPG) sensor configured to provide a PPG signal of the hearing aid user, and a listening effort determination unit configured to provide at least one PPG morphology parameter value based at least on the PPG signal, compare the at least one PPG morphology parameter value with at least one corresponding reference PPG morphology parameter value and determine a morphology comparison measure, and determine a listening effort of the hearing aid user. A hearing aid is further provided.

A solution for estimating effectiveness of periodic motion during a physical exercise. such as a running exercise, is disclosed. According to an aspect, a computer-implemented method for estimating the effectiveness of the periodic motion includes: measuring, by using at least one motion sensor, periodic motion of a user, and thus acquiring motion measurement data during a time interval of a physical exercise; transforming the motion measurement data into frequency-domain samples; extracting, amongst the frequency-domain samples by using peak detection, a first subset of frequency-domain samples representing periodic motion; computing a metric indicating a ratio between energy on the first subset of frequency domain samples and energy on other frequency domain samples; and mapping the computed ratio to an effectiveness parameter by using a determined mapping rule and outputting the effectiveness parameter via an interface.

Apparatus and methods are described including identifying that a subject suffers from sleep apnea. Positive airway pressure (PAP) is applied to the subject via a mask placed on a face of the subject. A respiratory-related parameter of the subject is sensed, while the mask is on the face of the subject, and a need of the subject for respiratory support is assessed, responsively to the respiratory-related parameter. In accordance with the assessed need, the mask is configured to regulate the PAP provided to the subject's face. Other applications are also described.

A smart ring includes a curved housing having a U-shape interior storing components including: a curved battery approximately conforming to the curved housing, a semi-flexible PCB approximately conforming to the curved housing and having mounted thereon: a motion sensor for generating motion data from physical perturbations of the smart ring, a memory for storing executable instructions, a transceiver for sending data to a client computer, a temperature sensor, and a processor for receiving motion data and performing executable instructions in response thereto, and a potting material disposed in the interior, forming an interior wall of the smart ring, wherein the potting material encapsulates the components and is substantially transparent to visible light, infrared light, and / or ultraviolet light.

A method and system are disclosed for use in monitoring/screening/diagnosing sleep or wake state of a subject or patient. The method generally includes monitoring the patient's activity during one or more sleep sessions comprising a plurality of intervals known as epochs. The sleep/wake state of the subject is determined during each epoch of the session using actigraphy data obtained during the monitoring session. The actigraphy data provides information about the activity of a patient during an epoch. The sleep or wake state is determined based on a ratio of the activity count during an epoch to the activity count during a preceding epoch. If the ratio is greater than a first activity threshold, then a “wake” indication may be provided by, for example, the system. Alternatively, or additionally, a “wake” indication may be determined if the activity count during the epoch is greater than a threshold.