The present disclosure relates generally to systems, methods, and devices for interpreting neural signals to determine a desired movement of a target, transmitting electrical signals to the target, and dynamically monitoring subsequent neural signals or movement of the target to change the signal being delivered if necessary, so that the desired movement is achieved. In particular, the neural signals are decoded using a feature extractor, decoder(s) and a body state observer to determine the electrical signals that should be sent.

A motion data processing method and a motion monitoring system provided in the present disclosure may process an electromyography (EMG) signal in the frequency domain or time domain to identify an abnormal signal in the EMG signal, such as an abrupt signal, a missing signal, a saturation signal, an oscillation signal, etc. caused by a high-pass filtering algorithm. The motion data processing method and the motion monitoring system may further perform a data sampling operation on the EMG signal through a data sampling algorithm, and predict data corresponding to the time point when the abnormal signal appears based on the sampling data, so as to obtain prediction data, and replace the abnormal signal by using the prediction data to correct the abnormal signal. The motion data processing method and the motion monitoring system may not merely accurately identify the abnormal signal, but further correct the abnormal signal, so that the corrected data may be more in line with an actual motion of a user, thereby improving user experience.

A brace configured for attachment to a joint of a subject is provided. The brace includes a first arm having a first end and a second end. The brace includes a second arm having a first end and a second end. The brace includes a hinge assembly coupling the first end of the first arm with the first end of the second arm such that the first arm and the second arm are movable to different relative angular orientations. The brace includes a potentiometer coupled to the hinge assembly. A method of monitoring a relative angular orientation of a first arm of a brace relative to a second arm of the brace is also provided. The method includes monitoring an output of a potentiometer coupled to one of the first arm and the second arm.

A load measurement device includes an acquisition unit, a first extraction unit, a second extraction unit, and an output unit. The acquisition unit acquires measurement information output from a load distribution sensor that detects a load distribution received from a sole of a subject. The first extraction unit extracts a region having a load value equal to or larger than a first threshold value as a first region based on the measurement information, and detects the first region as a sole region. The second extraction unit extracts a second region having a load value equal to or larger than a second threshold value that is smaller than the first threshold value from a re-extraction target region defined with the first region as a reference, and adds the second region to the sole region. The output unit outputs information related to a load distribution of the sole region.

A walking training system includes a leg orthosis fitted to a leg of a user, a pulling member coupled to the leg orthosis, a first drive mechanism configured to apply pull force to the pulling member, according to walking motion of the user, a holding device that holds the pulling member at a holding level, at a point between a coupling point of the leg orthosis and the first drive mechanism, and a second drive mechanism configured to change the holding level of the pulling member held by the holding device, according to the walking motion of the user.

An example of a system for delivering neurostimulation energy to a patient using a plurality of electrodes may include a stimulation circuit and a sensing circuit. The stimulation circuit may be configured to deliver the neurostimulation energy using stimulation electrodes selected from the plurality of electrodes and to control the delivery of the neurostimulation energy. The sensing circuit may be configured to receive one or more neural signals from sensing electrodes selected from the plurality of electrodes and may include a signal processing circuit. The signal processing circuit may include a detection circuit and an analysis circuit. The detection circuit may be configured to detect one or more attributes of neural responses from the received one or more neural signals. The analysis circuit may be configured to analyze the detected one or more attributes of the neural responses for one or more indications of a neurodegenerative disease.

A system and method are disclosed including receiving, from a sensor, motion data captured from a human, the motion data representative of involuntary human motions. In one embodiment, the method includes storing, in a memory, the motion data captured from the human. In one embodiment, the method includes processing the motion data captured by the human to determine a cycle bandwidth of the involuntary human motions across the motion data. In one embodiment, the method includes outputting the cycle bandwidth of the involuntary human motions across the motion data.

A system for measuring an angle of a joint of a user includes a center hub, a first arm, a second arm, a magnet, and a sensor. The center hub includes a first hub and a second hub. The first arm is configured for attachment to a first limb portion of the user at a first outer end and to the first hub at a first inner end. The second arm is configured for attachment to a second limb portion of the user at a second outer end and to the second hub at a second inner end, wherein the first hub is pivotally coupled to the second hub. The magnet is coupled to the second hub. The sensor is disposed in the center hub and configured to detect a rotation of the magnet.

The present invention provides a human-computer interactive rehabilitation system, which can automatically calculate rehabilitation strength suitable for the patient, so that it is not necessary to manually evaluate and adjust the parameter settings in human-computer interactive rehabilitation system when different patients use it. At the same time, the human-machine interactive rehabilitation system and the hospital end can track the rehabilitation status and intervene through the data platform at any time. The platform establishes a cloud community feedback and encouragement mechanism, and immediately transmits the rehabilitation results to the designated barriers of the patients, provides patient encouragement feedback, and strengthens the community interaction and linkage in the medical relationship.

The disclosed technology provides for generating simulation training models that can be used to prepare people (i.e., building occupants, first responders) to safely and calmly respond to emergencies, such as fires in high-rise buildings. Using the training models, people can better cope with decision-making during emergencies. The disclosed technology also uses signaling devices, wearables, and other devices and sensors distributed throughout a building to provide egress or stay-in-place guidance to people located in the building during an emergency. Audio and/or visual information can be outputted to people to guide them along a safe pathway that is selected to provide safe egress for the person, including anticipating and protecting the person from changing emergency conditions within the building and in response to how the person responded to the simulation training models.