An automated hand-biometric analyzer is provided. The analyzer comprises memory, a communication interface, a controller coupled to the memory, communication interface, and one or more load cell sensors configured to measure a hand grip strength of a user. A housing holds the memory, communication interface, controller, and load cell sensors, wherein the housing is configured to be received within the hand of a user. A gripping surface extends along a least a first portion of an outer surface of the housing and includes one or more connection points where the one or more connection points are communicatively coupled to the load cells. One or more cardiovascular sensors located on a second portion of the outer surface of the housing and configured to receive a palm of the hand of the user and measure cardiovascular parameters of the user.

A display device including: a display panel; a first input sensor disposed on the display panel and configured to generate a first reception signal in response to a user input; a second input sensor spaced apart from the first input sensor on the display panel and configured to generate a second reception signal in response to the user input; and a readout circuit configured to generate an output signal corresponding to the user input in response to the first reception signal and the second reception signal.

Described is a set for motor activities including a first stick for walking and a second stick for walking; each stick includes one or more sensors for detecting respective physical characteristics, an electronic module provided with an electronic unit for detecting and recording data acquired by the sensor; each electronic unit is configured to receive an activation command for starting recording of the data acquired and a deactivation command for ending recording; the electronic units of the first stick and of the second stick are configured for communicating with each other using a wireless data transmission network; one of either of the two electronic units of the first stick and of the second stick, called the reference, or main, electronic unit, is configured to send to the other electronic unit, called the dependent, or secondary, electronic unit, a timestamp, at the start of data recording.

Treatment of neurological injury through motor relearning. A game-based sensorimotor rehabilitator that enables individuals to interact with the functional objects using the appropriate amount of force, tilt, finger movement, and muscle activity to regain lost skill due to injury.

An embodiment of an exoskeleton glove at least provided with an individual linkage mechanism for each finger is provided wherein the linkage mechanism comprises sections that are interconnected with joints to enable changing their mutual angular orientation, which linkage mechanism comprises a first linkage attached to the glove, a second linkage connected to the first linkage through a first joint, a third linkage connected to the second linkage through a second joint, and a fourth linkage connected to the third linkage through a third joint, wherein the fourth linkage is provided with a finger orthosis, and the second linkage, the third linkage and the fourth linkage are capable to assume a mutually parallel placement wherein the finger orthosis is adjacent to the second joint at a farthest end from the glove, and the third joint is closer to the glove than the second joint.

Systems and methods to improve performance, reliability, learning and safety and thereby enhance autonomy of vehicles. Human sensors are used to capture human eye movement, hearing, hand grip and contact area, and foot positions. Event signatures corresponding to human actions, reactions and responses are extracted form these sensor values and correlated to events, status and situations acquired using vehicle and outside environment sensors. These event signatures are then used to train vehicles to improve their autonomous capabilities. Human sensors are vehicle mounted or frame mounted. Signatures obtained from events are classified and stored.

Systems and methods to improve performance, reliability, learning and safety and thereby enhance autonomy of vehicles. Human sensors are used to capture human eye movement, hearing, hand grip and contact area, and foot positions. Event signatures corresponding to human actions, reactions and responses are extracted form these sensor values and correlated to events, status and situations acquired using vehicle and outside environment sensors. These event signatures are then used to train vehicles to improve their autonomous capabilities. Human sensors are vehicle mounted or frame mounted. Signatures obtained from events are classified and stored.

A system and method are described for assessing muscle parameters (e.g., force(s) exerted, force dynamics, strength, voluntary muscle movement, etc.) in a diagnostic or therapeutic environment. The muscle parameter assessment system includes a force-gauging device and a computing device. The force-gauging device includes at least one pressure-sensing component (e.g., transducer, pressure sensor, etc.) configured to respond to a force applied by a subject and produce one or more output signals. The force-gauging device can further include electronic circuitry configured to convert the output signals into data indicative of a muscle parameter. The computing device is configured to build a muscle assessment protocol based on one or more patient characteristics and/or user input. The computing device is further configured to execute one or more muscle assessments via the force-gauging device, receive data from the force-gauging device, and determine one or more muscle measurements for a subject.

There are provided systems and methods for real-time age profiling. One system includes at least one sensor, a memory storing an algorithm, and a processor configured to execute the algorithm to receive data corresponding to a user interaction with the at least one sensor and calculate an age of a user using the data corresponding to the user interaction. The data corresponding to the user interaction may include pressure data from a pressure sensor, orientation data from an orientation sensor, motion data from a motion sensor, or interaction data from an interaction sensor.

A wearable device includes: at least one compliant region adapted and configured to be placed over a joint of a subject and at least two flexible but less compliant regions coupled to opposite ends of the compliant region. The device provides a wearable robotic device including a wearable and at least one actuator adapted and configured to move the flexible but less compliant regions relative to each other.