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 physiological monitoring system features a Floormat and Handheld Sensor connected by a cable. A user stands on the Floormat and grips the Handheld Sensor. These components measure time-dependent physiological waveforms from a user over a conduction pathway extending from the user's hand or wrist to their feet. The Handheld Sensor and Floormat use a combination of electrodes that inject current into the user's body and collect bioelectric signals that, with processing, yield ECG, impedance, and bioreactance waveforms. Simultaneously, the Handheld Sensor measures photoplethysmogram waveforms with red and infrared radiation and pressure waveforms from the user's fingers and wrist, while the Floormat measures signals from load cells to determine force waveforms to determine the user's weight, and ballistocardiogram waveforms to determine parameters related to cardiac contractility. Processing these waveforms with algorithms running on a microprocessor yield the vital sign, hemodynamic, and biometric parameters.

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 method for predicting whether a patient is afflicted by a vestibular disorder includes assaying vestibular noise; identifying a characteristic of the vestibular noise; and at least in part on the basis of the characteristic of the vestibular noise, providing information for predicting that a patient has a vestibular disorder.

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.

Virtual reality apparatus, and various methods therefore.

According to an embodiment, provided is a method of estimating a gait speed, the method including: determining N subjects for gait speed measurement and obtaining personal data of the subjects; performing a clinical assessment on the subjects; obtaining measured gait data by performing a gait assessment on the subjects; and developing a gait speed estimation model having a plurality of gait factors based on the measured gait data, wherein the gait speed estimation model includes, as gait factors, a roll angle, a yaw angle, and a body weight measured by using an accelerometer worn on a center of body mass of the subject.

A vestibular training device for improving vestibular function and balance and reducing fall risk of a subject may include a motion platform configured to support the subject and execute discrete motions, one or more input devices configured to enable the subject to provide responses to the motions, one or more feedback devices configured to provide the subject with feedback indicative of whether the responses are correct or incorrect, and a controller configured to cause the motion platform to execute a first motion, receive, via the one or more input devices, a first response indicative of the subject's perception of the first motion, cause the one or more feedback devices to provide first feedback indicative of whether the first response is correct or incorrect, determine a second motion based at least in part on the first response, and cause the motion platform to execute the second motion.

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.

In one embodiment, one or more suspension systems of a vehicle may be used to mitigate motion sickness by limiting motion in one or more frequency ranges. In another embodiment, an active suspension may be integrated with an autonomous vehicle architecture. In yet another embodiment, the active suspension system of a vehicle may be used to induce motion in a vehicle. The vehicle may be used as a testbed for technical investigations and/or as a platform to enhance the enjoyment of video and/or audio by vehicle occupants. In some embodiments, the active suspensions system may be used to perform gestures as a means of communication with persons inside or outside the vehicle. In some embodiments, the active suspensions system may be used to generate haptic warnings to a vehicle operator or other persons in response to certain road situations.