Elbow paresis, frequently caused by brachial plexus injuries, poses a significant challenge in rehabilitation. To tackle this issue, we have developed a prototype powered orthosis that employs non-invasive surface electromyography (EMG) signals from neck muscles, such as the sternocleidomastoid, for intuitive control. This EMG-driven system enables precise manipulation of the elbow joint, covering the full physiological range of motion. The prototype integrates an EMG signal processor with an orthosis action operator, creating a seamless interface between human intent and mechanical action. Healthy participants successfully used neck muscle contractions to control elbow rotation, demonstrating the system's potential for real-world application. For the proposed basic prototype, we implemented the following functionality: an extension from 0 to 90 degrees at a constant speed upon neck muscle contraction detected using single-channel EMG. We have developed a mechanical design, EMG measurement system, and a basic algorithm for contraction detection.
Figure 1 illustrates the key components of the orthosis:
• Orthosis: The core structure supporting and regulating elbow movement, acting as the interface between the user and the control mechanism.
• ESP32 Microcontroller: The central processing unit coordinating system components. It communicates with the PC via TCP/IP for EMG signal processing and orthosis control, adjusting the orthosis position based on input from the EMG sensor and angle decoder.
• Motor Driver (BTS7960): Bridges digital commands from the ESP32 to the orthosis, regulating motor power for smooth and accurate movement using PWM signals.
• Angle Decoder (AS5050A): Provides real-time feedback on the orthosis position, measuring rotation angles and relaying data to the ESP32 for precise control.
• PC: Captures and processes real-time EMG signals from muscle activity, transmitting processed data to the ESP32 to guide orthosis control.
• EMG Sensor (AD8232 and STM32F407): Detects and measures electrical signals from neck muscle contractions, transferring analog values to the PC for processing.
Fig.1. Block diagram of the orthosis control system with dual pathways to minimize interference.
Specialized software was developed, as well as capturing user interactions like button presses to evaluate orthosis performance. During data collection, the user, equipped with an EMG sensor, performs neck rotations and presses the SPACE button in response to sound at 5 or 10-second intervals. The system records EMG data and button states ('1' for pressed, '0' for not pressed) at a 1 kHz sampling rate. This data is then queued and written to a file. For user convenience, the system can be terminated at any time with the Ctrl+C key combination.
Contraction detection is performed every second on the recorded EMG signal. The raw EMG signal first passes through a high-pass filter with a 20 Hz cutoff frequency. It is then processed using a 4th-order Butterworth low-pass filter with a 250 Hz cutoff frequency. The filtered signal is rectified, converting all negative values to positive. After rectification, the signal is further smoothed using a 4th-order Butterworth low-pass filter with a 6 Hz cutoff frequency. Then the scaled EMG envelope directly influences the orthosis's rotational actuator, ensuring responsive and accurate control. Through rigorous sensitivity analysis, we optimized the control algorithm by adjusting EMG window lengths, signal filtering, and thresholding parameters.
This optimization ensures the system can adapt to individual user needs, providing personalized and efficient control. The real-time control achieved with this prototype marks a significant advancement in biomedical rehabilitation devices. It offers a practical solution for those affected by elbow paresis and lays the groundwork for future advancements in neuromechanical interfaces. Our ongoing research aims to further refine this technology, exploring the integration of signal processing algorithms to predict and adapt to user movements, thereby creating a more natural and intuitive user experience. The ultimate goal is to develop a fully functional orthosis that can be readily implemented in clinical settings, providing a non-invasive, effective solution for elbow rehabilitation.
References
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