Hand Rehabilitation Device with EMG and Force Sensor Integration
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Solution Overview
Problem
Current power assistive devices for hand rehabilitation are limited in providing comprehensive training as they often focus on a single degree of freedom and lack efficiency in performing various training exercises.
Innovation Solution
A power assistive device that includes a hand brace with finger driving units, actuators, force sensors, and an EMG sensor, combined with a base featuring a forearm rotator and C-shaped tracks, which together provide training for finger flexion-extension and forearm supination-pronation by analyzing EMG, MMG, and force signals to determine the onset time of muscle dynamics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single sensor and single degree of freedom design is used, then the device structure is simple, but the training comprehensiveness and efficiency are insufficient
Solution Approach 1:
The device integrates multiple sensors (EMG sensor, force sensors) and multiple degrees of freedom (finger driving units for flexion-extension, forearm rotator for supination-pronation) into a single system. The hand brace with platform connects to the base, enabling the device to perform comprehensive hand rehabilitation training covering both finger movements and forearm rotations simultaneously, thus achieving multi-functionality without requiring separate devices for each training type.
Solution Approach 2:
The patent combines multiple sensing functions (EMG signal detection, force measurement) and multiple actuation functions (finger driving, forearm rotation) into an integrated system. The EMG sensor detects muscle electrical signals while force sensors measure mechanical forces, and both are processed together to control the coordinated movement of fingers and forearm, merging multiple functions into a unified rehabilitation device.
2Productivity
If multiple sensors and degrees of freedom are integrated, then training comprehensiveness is improved, but device complexity increases
Solution Approach 1:
The integrated device performs multiple rehabilitation functions simultaneously - finger flexion-extension training via finger driving units and forearm supination-pronation training via the forearm rotator - enabling comprehensive training in a single session, thus improving training efficiency and productivity without requiring multiple separate devices.
Solution Approach 2:
The system uses EMG sensors to detect the user's intended muscle activation and automatically controls the actuators to assist the movement, creating a self-regulating rehabilitation system that adapts to the user's needs in real-time, improving training efficiency through intelligent control.
3Measurement precision
If EMG and force signals are analyzed to determine muscle contraction onset time, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system merges EMG signal detection with force measurement, analyzing both signals simultaneously to determine muscle contraction onset time. This multi-modal sensing approach cross-validates the timing measurement by comparing electrical muscle activity with mechanical force development, significantly improving measurement precision through signal correlation analysis.
Solution Approach 2:
The system continuously monitors EMG and force signals, providing real-time feedback on muscle contraction timing and intensity. This feedback mechanism enables precise measurement of contraction onset by detecting the temporal relationship between electrical activation and mechanical response, while also allowing dynamic adjustment of training parameters based on measured performance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise measurement and training of muscle contraction onset times, enhancing the effectiveness of robotic rehabilitation by synchronizing finger and forearm movements, thus providing comprehensive hand rehabilitation.
Implementation Method 1
an electromyography (EMG) sensor that attaches to the forearm of the user and that senses EMG signals generated by movement of the upper limb of the user
Implementation Method 2
a plurality of force sensors that connect to the finger driving units and the bottom of the hand brace and that detect force signals generated by movement of the hand brace
Data Source
AI summary
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.