An intelligent fitness set and anti-cheating method thereof is disclosed. The intelligent fitness set includes a support, a base, a plurality of handheld fitness equipments and two handles, wherein a processor, a movement posture sensor and a touch sensor are provided in each handle, and the movement posture sensor and the touch sensor are connected respectively with the processor. One end of each handle is closed, while a bayonet is provided in the other end of the handle and the switchable hot-pluggable bayonet is configured to connect respectively to the plurality of handheld fitness equipments. In the present disclosure, one set of action training of a plurality of handheld fitness equipments is performed through the same set of handles, so that a user can complete movement of one time only by strictly complying with active standards during movement.

A food distinguishing apparatus for each individual's healthy diet is disclosed. Because handgrip strength was reported to be one of the best future health predictors, having a good hand-grip strength could be a way to be healthy. The inventor has focused on a phenomenon of hand-grip strength changing by touching food. Touching good food immediately increases the muscle strength. The reactions with food vary on each individual. The invented apparatus measures the pressure variation of two clenched fingers' pinch-grip strength without touching food and with touching food under exerting pushing out force from an expandable container and distinguishes good food and bad food for each user.

A grip interface is used to provide information about a user to a range of connected devices and applications based on the users' interactions with the grip. By embedding into the grip an array of sensors for motion, health, environmental and other data using embedded microcontroller network technology, and focusing on the grip as the interface between the physical and virtual worlds, applications and services to existing grip-based devices are enabled. Applications for the grip include as sports, fitness equipment, health monitoring, activity tracking, coaching, physical therapy, mobility aide and virtual entertainment, among others.

Described herein is a system and method for ergonomic analysis including a sensorized glove having an inner glove including a plurality of extensometer sensors for detecting relative movements between parts of a worker's hand, and an outer glove including a plurality of pressure sensors distributed over a palmar surface and for detecting pressure exerted in corresponding areas of said palmar surface; a wearable network of sensors being located in the network so that they can be associated to corresponding joints of the human body; a unit for generating a sequence of images of a worker task; and a processing unit for receiving data and/or signals from the sensorized glove, from the wearable sensor network, and/or from the unit, and configured for processing said data and/or signals to estimate ergonomic indicators and/or to obtain local information of effort and/or posture.

This disclosure relates to a device to mechanically and electrically connect with a touch screen computing device, such as a tablet computer. The device can include a platform that can be moved into and out of physical contact with a surface of a touch screen. During engagement with the surface, the moveable platform electrically interacts with the touch screen (e.g., via capacitive coupling) to enable detection by the touch screen of contact members (e.g., pegs) even in the absence of user contact with the pegs.

Disclosed are a system and method of detection of an interaction-error. The interaction-error is derived from an incorrect decision and is directed to interacting with a machine. During human-machine interaction, command related data values are obtained. Command related data values characterize any one of an interacting-command and an interacting-action. The command related data values are compared with command related reference data values, and an interaction-error is identified if a difference between the command related data values and the command related reference data values complies with a predefined criterion.

The system includes a movement sensor and a core contraction sensor in communication with a processor. The core contraction sensor is placed on the core muscles of a user and transmits core contraction signals to the processor. The processor receives movement signals from the movement sensor and identifies user movements that are qualifying movements that benefit from core contractions. The processor also monitors the timing between the qualifying movements and the core contractions to identify protected and unprotected qualifying movements. The system can also include a memory for storing core scores that are calculated from the protected and unprotected qualifying movements, exercise information and core sensor calibration information. The core contraction information can be used to calibrate the core contraction sensor. The core contraction and movement information can be transmitted to a therapist who can monitor the user's activities and provide instructional feedback.

Generator systems and methods are provided for generating a neuromuscular-to-motion decoder from a healthy limb. The generator system is configured to receive neuromuscular signals from neuromuscular sensors associated to predefined muscle/nerve locations of at least one pair of agonist and antagonist muscles/nerves of the healthy limb, obtained during performance by the person of a predefined exercise (defined by predefined exercise data) with the healthy limb; to receive motion signals from motion sensors associated to predefined positions of the healthy limb, during performance by the person of the predefined exercise with the healthy limb; and to generate the neuromuscular-to-motion decoder by mapping the neuromuscular signals to the motion signals over time using a mapping method. Rehabilitation systems are also provided for rehabilitating a paretic limb by using a neuromuscular-to-motion decoder produced by a generator system.

A direction control apparatus with a sensor, a method for determining a driver status using the driving control apparatus, and a system for determining the driver status are provided. The direction control apparatus includes at least a pressure sensor to sense a plurality of pressure values applied to multiple positions of the direction control apparatus. When the pressure values are received by a controller of the apparatus, the driver status can be determined according to a change of pressure values over time, or further a change of the positions where pressure is applied. The system can connect with an autopilot system and an alarm system of a vehicle via the controller. Therefore, the system incorporates an autopilot system and issues an alarm when the driver status is determined to be abnormal.

Methods and apparatus for mitigating neuromuscular signal artifacts are described. The method comprises detecting in real-time, by at least one computer processor, one or more artifacts in a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors, determining, based at least in part, on the detected one or more artifacts, a plurality of derived neuromuscular signals to mitigate the one or more artifacts, and providing, as input to one or more trained statistical models, the plurality of derived neuromuscular signals.