A device for muscle strength support includes a flexible support structure configured to be worn on a body of a user during use of the device and an actuator unit configured to exert a tensile force on a first tension member of the flexible support structure to support the muscle strength during a movement of a first body part. The first tension member extends along a first path through a guide strap of the flexible support structure to the actuator unit, the guide strap limiting a section of the first path in a direction perpendicular to a path longitudinal direction. The first tension member is further configured to be attached to the first body part during use of the device by a first fastening member.

In an embodiment, a nerve stimulation system includes a headset and an earpiece which includes two or more ear-contacting elements, for example an ear canal insert, and a concha insert. Ear-contacting elements may be mounted onto an earpiece housing have projecting mounting structures, which provide mechanical and electrical connection between ear-contacting elements and housing through various materials and configurations. In an embodiment, a nerve stimulation system includes a neural stimulation subsystem including neural stimulation device control circuitry for use in combination with a personal computing device to control a neural stimulation device.

An exemplary embodiment of the present invention provides an exosuit support system, comprising first and second orthotic interfaces, first and second members, and first and second actuators. The first and second orthotic interfaces can be configured to attach to left and right legs of a user, respectively. The first member can comprise a first end connected to the first orthotic interface and a second end connected to a portion of the system configured to be positioned proximate a right shoulder of the user. The second member can comprise a first end connected to the second orthotic interface and a second end connected to a portion of the system configured to be positioned proximate a left shoulder of the user. The first actuator can be configured to apply a first tension to the first member. The second actuator can be configured to apply a second tension to the second member.

A mobility augmentation system monitors a user's motor intent data and augments the user's mobility based on the monitored motor intent data. A machine-learned model is trained to identify an intended movement based on the monitored motor intent data. The machine-learned model may be trained based on generalized or specific motor intent data (e.g., user-specific motor intent data). A machine-learned model initially trained on generalized motor intent data may be re-trained on user-specific motor intent data such that the machine-learned model is optimized to the movements of the user. The system uses the machine-learned model to identify a difference between the user's monitored movement and target movement signals. Based on the identified difference, the system determines actuation signals to augment the user's movement. The actuation signals determined can be an adjustment to a currently applied actuation such that the system optimizes the actuation strategy during application.

In a state where a drive unit is located on a lateral side of a joint(s) of a wearer wearing clothes and a communication unit and a frame unit are fixed and retained corresponding to the wearer's first and second body sites, respectively, a driving torque of an actuator according to movements of the wearer's joint is transmitted as an assist force to the first and second body sites without giving any physical burdens or hindrances in daily life to the wearer.

A wearer is made to judge, based on a detection result by a signal detection unit, either one of an opposition movement, an adduction movement, a flexion movement, and an extension movement of a thumb; and a linear member drive unit is controlled to pull or relax each linear member corresponding to the judged movement in order to cause the thumb's intrinsic muscles and/or extrinsic muscles, which are required for the judged movement, to generate an assist force.

A multimodal wearable band uses mechanical vibrations to stimulate sensory neurons in the wrist or ankle to reduce the severity of tremors, rigidity, involuntary muscle contractions, and bradykinesia caused by neurological movement disorders and to free users from freezing induced by movement disorders. The device uses sensors to provide output used by a processing unit to determine a stimulation pattern for the user and to determine when stimulation is necessary, and then uses one or more transducers to correspondingly stimulate the user’s neurological pathways to lessen the severity of the user’s symptoms. The device can also be adapted to integrate with third party devices.

A power assistive device (100) for hand rehabilitation that provides training of a combined movement of finger flexion-extension and forearm supination-pronation to a user. The power assistive device (100) includes a hand brace (102) and a base (104). The hand brace (102) includes finger driving units (206) that adjustably connect to a platform (202, 204), actuators (208) that connect to the finger driving units (206), and force sensors (232) that connect to the finger driving units (206) and the bottom of the hand brace (102) and detect force signals generated by movement of the hand brace (102). The base (104) removably connects to the hand brace (102) and includes a supporting structure (302), a forearm rotator (110) that includes C-shaped tracks (314, 316) formed along an inner circumferential surface, a rotatable platform (306) that moves along the C-shaped tracks (314, 316), a mounting platform (308) that connects to the rotatable platform (306), and an electromyography (EMG) sensor (402A-402B) that attaches to the upper arm or forearm of the user and senses EMG signals generated by the user.

A health-regain device includes a driving portion, a health portion disposed on one side of the driving portion, and a control module communicably connected to the driving portion, wherein the control module controls the driving portion driving the health portion in rhythmic reciprocating motion.

Methods and apparatuses for recognizing a gait task, that may detect a gait pattern of a user based on sensed data, generate a gait feature of the gait pattern based on similarities between the gait pattern and similar gait data extracted from each of a plurality of databases, and estimate a gait task corresponding to the gait pattern by applying the gait feature to a desired learning model, may be provided.