A system or method for measuring human ocular performance can be implemented using an eye sensor, a head orientation sensor, an electronic circuit and a display that presents one of virtual reality information, augmented reality information, or synthetic computer-generated 3-dimensional information. The device is configured for measuring saccades, pursuit tracking during visual pursuit, nystagmus, vergence, eyelid closure, or focused position of the eyes. The eye sensor comprises a video camera that senses vertical movement and horizontal movement of at least one eye. The head orientation sensor senses pitch and yaw in the range of frequencies between 0.01 Hertz and 15 Hertz. The system uses a Fourier transform to generate a vertical gain signal and a horizontal gain signal.

A method for measuring the mobility of a subject, the method comprising: receiving an audio signal from one or more microphones: for each of a plurality of overlapping regions of the audio signal, classifying the region as containing the sound of a footstep using a first supervised learning algorithm, determining that two or more of the regions classified as containing the sound of a footstep correspond to a series of two or more consecutive footsteps of a subject; and using a first neural network, analysing the determined two or more regions to determine a mobility factor.

A method for monitoring a progress during a rehabilitation using a wearable sensor. The sensor monitors activity of a patient during predetermined training program and acquires exercise signal during some or all training sessions. The method computes a compliance index and an improvement index and updates the training program accordingly.

A system for analyzing data from motion capture measurements has a sensor to measure motion capture measurements, a module configured to receive sensor data from the sensors, and a processor configured to analyze to the sensor data received from the sensors and create a report of such analysis. A computer-implemented method of analyzing data from motion capture measurements includes performing motion capture measurements on a subject, receiving motion capture data from the motion capture measurements, processing the motion capture data and the background data on a computer using an algorithm, including comparing the motion capture data and background data to one or more comparator waveforms, generating a report based on the processing analysis, and communicating the results of the report.

Data regarding typing by a user may be collected and analyzed in order to assess one or more health conditions or functional states of the user. Each health condition that is assessed may be a disease or a symptom of a disease. For instance, based on the typing data, a computer may assess the presence, severity or probability of, or a change in, one or more symptoms such as: mild cognitive impairment, dementia, impairment of fine motor control, impairment of sensory-motor feedback, or behavioral impairment. A computer may calculate keystroke tensors that encode information about the typing. A computer may select or derive features from the keystroke tensors. These features may be fed into one or more machine learning algorithms, which in turn may output an assessment of a health condition or functional state of the user.

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.

The present technology is directed to vestibular prostheses and associated systems and methods. In several embodiments, for example, a vestibular prosthesis includes an external rotational sensor configured to receive velocity and orientation information. The prosthesis further includes an external processor configured to convert the velocity and orientation information into an audio signal. The audio signal is sent to a cochlear implant, which applies stimulation to a semicircular ear canal in response to receiving the audio signal. In some embodiments, the processor and cochlear implant communicate in real time via an inductive link.

A system and method for assessing a patient's balancing ability in order to facilitate ascertaining the patient's current medical status. The system includes a balance plate for measuring the center of gravity dynamic weight distribution in combination with a sensor for measuring the patient's fine motor skills.

A fracture index determination system, method and storage medium are provided. The system includes: a bone mineral density (BMD) acquisition module, a balance degree acquisition module and a processing module. The BMD acquisition module and the balance degree acquisition module are connected to the processing module respectively; the BMD acquisition module is configured to acquire a BMD of a human body under test; the balance degree acquisition module is configured to acquire a balance degree of the human body under test, and the balance degree is used to characterize the standing stability of the human body; and the processing module is configured to determine a fracture index of the human body under test in accordance with the BMD and the balance degree of the human body under test. The system improves the accuracy of determining the fracture index.

The application discloses a method for monitoring a user gesture and a wearable device. The method comprises: providing an inertial sensor in a wearable device, the wearable device being located on the head of a user when being worn; monitoring movement data of the head of the user in real time, by using the inertial sensor, when the user is wearing the wearable device; conducting gesture solving by using the movement data to obtain gesture data of the head of the user; determining whether a head gesture of the user is a correct gesture according to the gesture data and a preset strategy; and sending a reminder to the user when the head gesture of the user is an incorrect gesture.