Abstract: Semi-passive control system (10) comprises a pneumatic spring actuator (16), a pressure regulator (22) in communication with the pneumatic spring actuator (16), a hydraulic locking actuator (18), a hydraulic valve (20) in communication with actuator (18), a power source (14), a pulley wheel (42), and a cable (46) having a first end in contact with pulley wheel (42), first and second side portions (50, 56) extending from opposing sides of pulley wheel (42), and a second end adapted to connect to an orthosis device (76). At least one cable clamp (62) attaches to second side portion (56) of cable (46) and interconnects cable (46) to shafts (112b, 118b) of actuators (16, 18). A central control unit (12) includes a processor (13a) and a computer readable storage medium (13b) having program instructions stored thereon for execution by the central control unit to adjust stiffness, damping or stiffness and damping parameters.

Abstract: Semi-passive control system (10) comprises a pneumatic spring actuator (16), a pressure regulator (22) in communication with the pneumatic spring actuator (16), a hydraulic locking actuator (18), a hydraulic valve (20) in communication with actuator (18), a power source (14), a pulley wheel (42), and a cable (46) having a first end in contact with pulley wheel (42), first and second side portions (50, 56) extending from opposing sides of pulley wheel (42), and a second end adapted to connect to an orthosis device (76). At least one cable clamp (62) attaches to second side portion (56) of cable (46) and interconnects cable (46) to shafts (112b, 118b) of actuators (16, 18). A central control unit (12) includes a processor (13a) and a computer readable storage medium (13b) having program instructions stored thereon for execution by the central control unit to adjust stiffness, damping or stiffness and damping parameters.

Abstract: The invention concerns a method of driving assistance for assisting a human driver in safely driving a vehicle called host vehicle, implemented by a processor on board of said host vehicle. The host vehicle comprises means for obtaining first information relative to the host vehicle and means for obtaining second information relative to at least one other vehicle in a neighborhood of the host vehicle, said first and second information being obtained at regular time instants, comprising triggering an intervention of a collision avoidance system. The method comprises a step (51) of intervention decision adapted to decide whether to trigger the intervention of the collision avoidance system at a current time instant (Tc) or to postpone said intervention decision at a later time instant (Tl) depending upon additional first and second information to be acquired between the current time instant (Tc) and the later time instant (Tl), said additional first and second information having an associated probability.

Abstract: The invention concerns a method of driving assistance for assisting a human driver in safely driving a vehicle called host vehicle, implemented by a processor on board of said host vehicle. The host vehicle comprises means for obtaining first information relative to the host vehicle and means for obtaining second information relative to at least one other vehicle in a neighborhood of the host vehicle, said first and second information being obtained at regular time instants, comprising triggering an intervention of a collision avoidance system. The method comprises a step (51) of intervention decision adapted to decide whether to trigger the intervention of the collision avoidance system at a current time instant (Tc) or to postpone said intervention decision at a later time instant (Tl) depending upon additional first and second information to be acquired between the current time instant (Tc) and the later time instant (Tl), said additional first and second information having an associated probability.

Abstract: Methods for classifying aggregated data in a distributed sensor system are provided and illustrated with a wearable motion sensor network. The classification is operated in a distributed fashion on individual sensor nodes and a base station computer. The method classifies actions using a set of training motion sequences as prior examples and may reject outlying actions that are not in the training categories. Acquired sensor data is processed at the node by taking projections of the data to reduce dimensionality, calculating sparse representations of features using training sequences; validating and classifying local measurements and then transmitting classified measurements to a network base station.

Abstract: A portable and automated system and method for measuring physical function utilizing a contactless and vision-based sensor system for acquiring human movements and methods for the analysis of reachable or functional workspace and range of motion that can be used in tele-medicine applications, such as remote functional assessment and diagnosis. An interactive, shared virtual 3D environment is provided where the patient can follow the movement directions provided by a remote physician while body kinematics are extracted from depth sensing cameras and wireless sensors.

Abstract: An approach for determining motions of a body using distributed sensors is disclosed. In one embodiment, an apparatus can include: a plurality of sensors coupled to a body, where each sensor is positioned at about a designated location on the body, and where each sensor is configured to acquire motion data related to movement of the designated location on the body and at which the sensor is positioned, and to reduce the motion data into compressed and transmittable motion data; and a base station configured to receive the compressed motion data via wireless communication from at least one of the plurality of sensors, the base station being further configured to remove outlier information from the received motion data, and to match the received motion data to a predetermined action, where the predetermined action indicates a movement of the body.