A method and system for monitoring a user's intoxication including receiving a set of signals, derived from a set of samples collected from the user at a set of time points; providing a sobriety task to the user proximal to a time point of the set of time points; generating a performance dataset characterizing performance of the sobriety task by the user; receiving a supplementary dataset characterizing a demographic profile of the user and/or a physiological state of the user; determining a set of values of an intoxication metric, derived from the set of signals; generating a predicted temporal profile of the intoxication metric for the user based upon the set of values, the set of time points, and the supplementary dataset; generating an analysis of the user's sobriety based upon the performance dataset and the predicted temporal profile; and providing a notification to the user based upon the analysis.

A balance board fitness training device is provided. The fitness training device may include a deck having a top surface, a bottom surface, and opposing first and second side edges and opposing front and rear longitudinal edges together forming a perimeter of the deck; at least one wheel bracket structure positioned below the deck, the at least one wheel bracket structure rotatably supporting at least two wheels and configured so as to be movable relative to the deck about a pivot line at least partially extending between the opposing first and second side edges of the deck; and at least one resilient damping member connected to the at least one wheel bracket structure and the deck.

There is provided herein a system and method for performing a balance evaluation that utilizes a hand held accelerometer that measures upper body compensatory and correctional movement. Instead of testing movement in the waist or lower extremity as is commonly done, the instant invention measures thoracic trunk sway to estimate an individual's balance via positional change algorithms. By holding the measuring device to the chest and performing one or a variety of balance tests, the instant invention can determine the amount of sway in the trunk without attached or fixed monitors, which presents a novel approach to assessing postural sway above the center of mass.

A method and system for monitoring a user's intoxication including receiving a set of signals, derived from a set of samples collected from the user at a set of time points; providing a sobriety task to the user proximal to a time point of the set of time points; generating a performance dataset characterizing performance of the sobriety task by the user; receiving a supplementary dataset characterizing a demographic profile of the user and/or a physiological state of the user; determining a set of values of an intoxication metric, derived from the set of signals; generating a predicted temporal profile of the intoxication metric for the user based upon the set of values, the set of time points, and the supplementary dataset; generating an analysis of the user's sobriety based upon the performance dataset and the predicted temporal profile; and providing a notification to the user based upon the analysis.

A monitoring system includes a Doppler radar formed with an IEEE 802 protocol transmitter and an IEEE 802 protocol receiver to detect motion, wherein frequency waves are transmitted by the IEEE 802 protocol transmitter and reflected waves are received by the IEEE protocol 802 receiver; and an analyzer to perform Doppler operations using the IEEE 802 protocol transmitter and receiver, wherein the analyzer calibrates a training Doppler radar signal during a training phase to develop a model and wherein the analyzer applies the model with the Doppler radar signal during an operational phase to determine position.

Aspects of the present disclosure are directed toward obtaining a plurality of impedance-measurement signals while a set of at least three electrodes are concurrently contacting a user. Additionally, various aspects of the present disclosure include determining a plurality of pulse characteristic signals based on the plurality of impedance-measurement signals. One of the pulse characteristic signals is extracted from one of the impedance-measurement signals and is used as a timing reference to extract and process another of the pulse characteristic signals.

Systems and methods for monitoring heart failure (HF) status in a patient are discussed. An exemplary system includes a gait analyzer circuit than can receive gait or balance information, and generate a gait feature such as gait speed or a gait pattern. The system includes a HF detector circuit that can detect patient HF status, or to predict patient risk of a future worsening heart failure (WHF) event, using the gait feature. In some examples, the system may trigger sensing physiologic information according to the detected gait, and detect patient HF status using the sensed physiologic information. The system can initiate or adjust a heart failure therapy according to the HF status or the WHF risk.

A person's fall risk may be determined based on machine learning algorithms. The fall risk information can be used to notify the person and/or a third party monitoring person (e.g. doctor, physical therapist, personal trainer, etc.) of the person's fall risk. This information may be used to monitor and track changes in fall risk that may be impacted by changes in health status, lifestyle behaviors or medical treatment. Furthermore, the fall risk classification may help individuals be more careful on the days they are more at risk for falling. The fall risk may be estimated using machine learning algorithms that process data from load sensors by computing basic and advanced punctuated equilibrium model (PEM) stability metrics.

The present document describes a computer implemented system and method for performing a quantitative balance assessment on a subject. The method comprises instructing the subject to perform an assessment task with at least a first kinematic sensor mounted on the subject's head; collecting kinematic sensor measurements, comparing the measurements to a threshold value; summing the total number of kinematic sensor measurements that exceed the threshold value to generate a numerical score indicative of the subject's postural stability. The system makes use of only kinematic data collected from the wireless sensors to quantify BESS, and generate a BESS score, without any other physiological variables such as forward sway.

A method of assessing the balance impairment of a subject includes the steps of presenting the subject with a static scene on a display, collecting a first set of orientation measurements, presenting the subject with an unstable scene on a display, collecting a second set of orientation measurements, storing the first and second sets of orientation measurements on a computing device, referenced to a set of time indices, and calculating a balance score for the subject by comparing the second set of orientation measurements with the first set of orientation measurements. A system for assessing the balance impairment of a subject is also disclosed.