The described systems and methods determine a driver's fitness to safely operate a moving vehicle based at least in part upon observed impairment patterns. A smart ring, wearable on a user's finger, continuously monitors impairment levels. This impairment data, representing impairment patterns, can be utilized, in combination with driving data, to train a machine learning model, which will predict the user's level of risk exposure based at least in part upon observed impairment patterns. The user can be warned of this risk to prevent them from driving or to encourage them to delay driving. In some instances, the disclosed smart ring system may interact with the user's vehicle to prevent it from starting while the user is in a state of impairment induced by substance intoxication.

A rehabilitation feedback system is used during rehabilitation of one or more body appendages of a user. The system includes four finger tracking elements and a thumb tracking element supported for movement relative to one another so as to allow a user to performs a gripping motion when the elements are coupled to the fingers and thumb of a user. A biasing member provides a resistance force acting to urge each tracking element towards a starting position thereof. A visual barrier is adapted to hide the hand of the user at a first side of the visual barrier from direct visual sight by the user at a second side of the visual barrier. A sensor at the first side of the visual barrier detects movements of the tracking elements and communicates with an indicator element detectable by the user from a second side of the visual barrier.

A hand function testing device includes a base having a number of rigid wires protruding from a surface thereof, each rigid wire having a stationary bead affixed at a predetermined position along the rigid wire, a moving bead movably mounted on the rigid wire and movable along a working region of the rigid wire defined between a base-end of the rigid wire and the stationary bead, the moving bead being mounted on the rigid wire via reception of the rigid wire through a lumen in the moving bead, and at least one force sensing element for measuring a force input to the moving bead. A method of testing hand function includes using the hand function testing device to measure a force input to a moving bead as the moving bead is moved within a working region on the rigid wire.

A user interface device is adapted to provide tremor cancellation. The user interface device comprises a user interface for determining a position from a physical user input and a position output for providing a time-ordered output stream of position data, but also provides a tremor learning module and a tremor cancellation module. The tremor learning module can be trained to identify tremor patterns for a user by comparing time-ordered output streams of position data produced by the user with predetermined representations. The tremor cancellation module is adapted to apply the tremor patterns learned for the user to cancel tremors in a time-ordered stream of position data produced by the user to create an output stream of position data which is corrected for user tremor. A method of training and then using such a user interface device is also described.

A fixed-sensor finger action detecting glove has a glove body, five covering sheets, five fixing bases, five sensors, and five fixing assemblies. A side of the glove body forms a hand back section and five finger back sections. The covering sheet is mounted on the finger back section and forms a passage. The fixing base is made from a flexible material, is mounted through the passage, and has two limiting walls. The sensor is located in the passage between the two limiting walls, preventing the sensor from deviating. The fixing assembly is mounted between an end of the sensor and an end of the finger back section, detachably connects the sensor and the finger back section, and prevents the sensor from moving back and forth. Thus, the fixed-sensor finger action detecting glove is capable of detecting actions of the fingers precisely.

The present disclosure provides a finger joint rehabilitation training device, which includes a control member, a data acquisition member, a gas circuit system, and a wearable training member. The wearable training member is provided with a pneumatic component that can expand and contract. The data acquisition member is configured for acquiring hand motion information of a first hand and transmitting the hand motion information to the control member. The hand motion information includes hand pressing information. The control member controls the gas circuit system to inflate the pneumatic component or to draw air from the pneumatic component according to the hand motion information, to make the wearable training member change between a flexion condition and a stretching condition, so as to realize a hand mirror training of a second hand. The hand pressing information is simple and convenient to acquire, which is convenient for the first hand to realize the flexion condition and the stretching condition, and the condition of the second hand is adjusted through the condition of the first hand, so that the wearable training member can be better adjusted, different hand training intensity requirements are met, and a better training effect is achieved.

A rehabilitation feedback system is used during rehabilitation of one or more body appendages of a user. The system includes four finger tracking elements and a thumb tracking element supported for movement relative to one another so as to allow a user to perform a gripping motion when the elements are coupled to the fingers and thumb of a user. A biasing member provides a resistance force acting to urge each tracking element towards a starting position thereof. A visual barrier is adapted to hide the hand of the user at a first side of the visual barrier from direct visual sight by the user at a second side of the visual barrier. A sensor at the first side of the visual barrier detects movements of the tracking elements and communicates with an indicator element detectable by the user from a second side of the visual barrier.

A device and method for detecting control-point activation conditions corresponding to a portion of a glove body coming in contact with or being within a threshold distance from at least one of another portion of the glove body or a control surface separate from the glove body. The glove may include a conductive path attached to the glove body and an expanded conductive area conductively coupled to the conductive path and attached to the glove body. The expanded conductive area may be wider than individual portions of the conductive path.

Systems and methods for data compression which facilitate the diagnosis and treatment of neurodevelopmental and neurodegenerative disorders. The methods comprise performing the following operations by a computing device: generating Normalized Data (“ND”) from Original Data (“OD”) that defines a Normalized Waveform (“NW”) that is unitless and scaled from zero to one; processing ND to extract Micro-Movement Data (“MMD”) defining a Micro-Movement Waveform (“MMW”) comprising a plurality of MMD points; and generating compressed data comprising a stochastic signature of MMW. Each MMD point determined based on a value of a peak of NW and a value representing an average of all data point values between a first valley of NW immediately preceding the peak and a second valley of NW immediately following the peak. The stochastic signature is defined by empirically estimated values of at least one parameter representing a Probability Distribution Function (“PDF”) of a continuous family of PDFs.

The present invention provides a novel system and device for wearables for humans and animals that capture and store kinematic and kinetic data and movement during training, rehabilitation, real-time events, and the like, analyze such data and movement in real-time during and after such activities, and provide output, feedback, assessment, and actionable biomechanical data and information about the wearer.