One embodiment relates to an apparatus, comprising logic, at least partially incorporated into hardware, to: receive first sensor data associated with a first sensor of a first smart device; determine a first reliability factor associated with the first sensor data; receive second sensor data associated with a second sensor of a second smart device; and determine a second reliability factor associated with the second sensor data. The logic is further to determine a sensor data reporting plan based upon the first reliability factor and the second reliability factor, the sensor data reporting plan indicating whether each of the first sensor and the second sensor are to subsequently send their respective sensor data to a primary communication device.

An implantable medical device includes a detecting unit, a control unit and a communication unit. The control unit uses a seizure prediction algorithm to predict epilepsy seizure events in real time based on physiological information detected by the detecting unit, and stores internal data which comprise the detected physiological information and prediction information about the prediction result. The control unit is configured to, in a first communication mode, control its memory unit and communication unit to transmit the internal data to the external monitoring device, and in a second communication mode, control the communication unit to receive an updated seizure prediction algorithm from the external monitoring device and stores the algorithm in the memory unit for predicting seizure events.

A method and system for determining training status of a user from exercises using a device with a heart rate sensor, a processor, memory, an output device and software. The training status is selected from a fixed group of alternatives. Each exercise is monitored using the heart rate sensor. Chosen exercise characteristics of each executed exercise are determined using obtained heart rate data and the determined characteristics of each executed exercise are stored in a memory. The chosen exercise characteristics include values of at least following variables: a date of the exercise, a value depicting physical readiness level for exercise during the exercise, a value depicting a training load of the exercise. When the exercises have been executed, values of selection variables are calculated using the stored exercise characteristics in the memory.

Methods, computer systems, and computer readable media are provided for promoting positive activity patterns for users and facilitate long-term adherence to the activity patterns, such as by providing alerts or electronic reminders to ambulate in a fashion that is responsive to an individual's actual activity patterns and behaviors and compatible with routine activities in the workplace and home. In particular, embodiments of the present invention are directed to measuring physical activity patterns during the waking hours of a human, and in some embodiments continuously measuring these activity patterns; automatically ascertaining whether the patterns exhibit sufficient frequency and variability of activity such as confers certain health benefits; and if the patterns do not manifest such features, to adaptively provide sensible reminders at irregular within-day intervals such as are likely to establish healthy patterns of ambulation and other light activity.

An optical sensor, an optical sensor array, and an apparatus and method for measuring a bio-signal are provided. The optical sensor includes a photodetector, and a light source disposed on the photodetector. The optical sensor is configured to operate the light source in a light source mode, and operate the photodetector in a photodetector mode, based on a control signal.

A hand-held point of care monitoring system that includes a plurality of assay modules configured to receive different assay devices that perform assays on one or more samples. At least two of the assay modules or at least two of the assay devices have different identifiers that identify the assays. The system also includes an apparatus having a portable frame configured to interchangeably receive the plurality of assay modules in a same port; a means for decoding the different identifiers when received by the frame; and a means for reading assay results.

Described is a system for health assessment. The system is implemented on a mobile device having at least one of an accelerometer, a geographic location sensor, and a camera. In operation, the system obtains sensor data related to an operator of the mobile device from one of the sensors. A network of networks (NoN) is generated based on the sensor data, the NoN having a plurality of layers with linked nodes. Tuples are thereafter generated. Each tuple contains a node from each layer that optimizes importance, diversity, and coherence. Storylines are created based on the tuples that solves a longest path problem for each tuple. The storylines track multiple symptom progressions of the operator. Finally, a disease prediction of the operator is provided based on the storylines.

System for the purpose of realizing wellness and wellbeing that enables users to define personal wellness and wellbeing objectives that establish the scope of contextualizing user specific condition. The system collects and co-analyzes ambient pollution and physiological biomarkers data that include ambient airborne pollution, electric field radiation pollution, magnetic field radiation pollution, RF signal radiation pollution, temperature changes, relative humidity, and users' physiological biomarkers. The system operates in three modes: interactive, passive, and physical mode, and it uses range extender remote ambient pollution monitors to cover any desired indoor-space. The system is built on a universal holder that expands and retracts both vertical and horizontal dimensions to fit as a protective case and sleeve for various sizes of smartphone and handheld devices. The system guides and orchestrates users' deliberate effort of achieving target wellness and wellbeing objectives, and it informs any adverse condition to the users' wellness and wellbeing.

A system, method and apparatus is disclosed, comprising a biomathetical model for optimizing cognitive performance in the face of sleep deprivation that integrates novel and nonobvious biomathematical models for quantifying performance impairment for both chronic sleep restriction and total sleep deprivation; the dose-dependent effects of caffeine on human vigilance; and the pheonotypical response of a particular user to caffeine dosing, chronic sleep restriction and total sleep deprivation in user-friendly software application which itself may be part of a networked system.

A system obtains a maternal electrocardiogram (ECG) signal that represents an ECG of a pregnant mother during a first time interval. The system further obtains a mixed maternal-fetal ECG signal that represents a combined ECG of the mother and her fetus during the first time interval; processes the maternal ECG signal and the mixed maternal-fetal ECG signal to generate a fetal ECG signal that represents the ECG of the fetus during the time interval, the fetal ECG signal substantially excluding the maternal ECG signal; and provides an output based on the fetal ECG signal.