A personal health system, method and device that maintains a health knowledge base, inputs user characteristics, generates health scores based on the user characteristics and provides recommendations based on the user characteristics, health scores and knowledge base, wherein the recommendations are indicated by the knowledge base to be likely to improve the user's health.

Wellness capture devices, systems for tracking wellness of an individual and/or a team, and methods of tracking wellness of an individual and/or a team are described. A wellness tracking device includes a housing and a cover that cooperatively define a chamber, a circuit board disposed in the chamber and including a system on a chip module, a vibration motor, a light diffuser, a first attachment member attached to the housing and a second attachment member disposed on an outer surface of the housing opposite the cover.

The present disclosure includes a handheld processing device including medical applications for minimally and noninvasive glucose measurements. In an embodiment, the device creates a patient specific calibration using a measurement protocol of minimally invasive measurements and noninvasive measurements, eventually creating a patient specific noninvasive glucometer. Additionally, embodiments of the present disclosure provide for the processing device to execute medical applications and non-medical applications.

Methods, systems and computer readable media for computerized prediction of body parameters such as body fat percentage (BFP) and modeling of a subject (e.g., a human body) are described.

Embodiments described herein include a medical monitoring system with a cloud communication interface in which individual components of the medical monitoring system, including medical sensors and data receiving devices are configured to communicate with remote cloud servers of the medical monitoring system using cellular networks. The remote cloud servers process medical data reported by the medical sensors and deliver data to the data receiving devices. The components of the medical monitoring system are low-cost and durable. The sensors are considered disposable after the expiration of their active use lifetime. The data receiving device can be manufactured using low-cost durable components to be protected against loss caused by accidental damage, destruction, or misplacement. Embodiments described herein further provide for authentication and for secure communication among the components of the medical monitoring system.

Methods and apparatus for detecting body vital signs through the use of a Bioelectric Impedance Spectroscopy (BIS), either by (a) direct contact with the person (such as through one or more of their fingers) or (b) measurement of reflections from a field projected into the person's body. The techniques may be implemented using the projected capacitive touch array in a device such as the screen of a smartphone or tablet computer, or the touchpad of a laptop computer.

A physiological signal monitoring system includes a single set of sensing electrodes to provide conditioned physiological signals to a primary monitoring device and a secondary monitoring device. The monitoring system includes pre-processing circuitry configured to receive a raw physiological signal. The pre-processing circuitry is configured to produce a primary physiological signal and a secondary physiological signal. Each of the primary and secondary physiological signals are conditioned. The primary conditioned physiological signal is directed to a primary monitoring device such as a hospital wearable defibrillator device. The secondary conditioned physiological signal is directed to telemetry modeling circuitry where it is further processed to output one or more telemetry signals. The one or more telemetry signals are output to a secondary monitoring device such as a three lead ECG monitoring device. Thus, a single set of sensing electrodes can provide physiological signals to multiple monitoring devices.

A method for estimating total body water, TBW, content of a subject, comprises: receiving locally measured bioimpedances for at least two different frequencies of a stimulation current at a body part of the subject; determining a first resistance and a second resistance of the bioimpedance, wherein the first resistance corresponds to a representation of the bioimpedance being purely resistive at a low frequency of the stimulation current and the second resistance corresponds to a representation of the bioimpedance being purely resistive at a high frequency of the stimulation current; and estimating the TBW content of the subject using a ratio between the first resistance and the second resistance.

Systems and methods are provided for improved continuous glucose monitoring (“CGM”). The disclosed systems and methods provide for tracking analyte measurements, CGM-related event data, and sensor-related data. This data is combined and presented in connection with a graphical user interface that allows for improved functionality. Aspects of the disclosure allow for analyte measurements to be displayed in a graphical user interface that includes historical graphs of analyte measurements and incorporate event data as a plurality of event indications. The time frame of the historical graph can be altered by the user and the events can be presented a group within an event indication based on the time frame of the historical graph. The graphical user interface may also be configured to display graph trend data for each individual event as well as a sensor-life indication representing the period of time remaining before expiration of an analyte sensor.

A system, method, and computer platform product for an adaptive cognitive training platform. In accordance with various aspects of the present disclosure, an adaptive cognitive training platform is configured to process user activity data from one or more instances of a computerized cognitive training program to determine a baseline cognitive assessment for one or more cognitive abilities/skills of a user. The cognitive assessment model may be configured to further process the user activity data to predict a relative value or measure of efficacy for one or more computerized stimuli or interactions within the computerized cognitive training program. The adaptive cognitive training platform may be configured to configure, modify and/or present one or more graphical user interface elements for one or more subsequent instances of the computerized cognitive training program according to the predicted value or measure of efficacy of one or more cognitive training tasks.