Dual sEMG Phase Comparison for Real-Time Muscle Contraction Detection
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Solution Overview
Problem
Existing muscle activation detection technologies face challenges in synchronizing human muscle intentions with wearable robots, particularly in real-time detection and control, due to issues with electrode comfort, noise interference, and limited communication interfaces.
Innovation Solution
A muscle activation detection apparatus using dual sEMG sensors with phase comparators and analog hardware to detect phase differences in sEMG signals, combined with wireless and wired communication modules, for real-time muscle contraction detection and robot control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dual sEMG sensors with phase comparators are used for real-time muscle activation detection, then measurement precision and response speed are improved, but device complexity increases
Solution Approach 1:
The system divides the detection task into two separate sEMG sensors placed at different locations (e.g., agonist and antagonist muscles), each independently capturing muscle activation signals. This segmentation allows the phase comparator to detect activation patterns more accurately by comparing signals from multiple independent sources, thereby improving measurement precision while distributing the complexity across modular components.
Solution Approach 2:
A phase comparator is introduced as an intermediary component between the two sEMG sensors and the control system. This intermediary device specifically processes the phase relationship between signals, extracting meaningful muscle activation information without requiring complex full-signal analysis. The phase comparator acts as a specialized mediator that simplifies the overall system architecture while enhancing detection accuracy.
2Adaptability or versatility
If multiple communication interfaces (wireless and wired) are integrated for robot control, then adaptability and ease of operation are improved, but device complexity increases
Solution Approach 1:
The control system is designed with multi-functional communication capabilities, integrating both wireless (e.g., Bluetooth, Wi-Fi) and wired (e.g., USB, CAN bus) interfaces within a single unified architecture. This universal design allows the system to adapt to different operational scenarios and user preferences without requiring separate dedicated systems, thereby improving versatility while managing complexity through integrated design.
Solution Approach 2:
The communication system employs dynamic interface selection, automatically switching between wireless and wired modes based on real-time requirements such as data transmission speed needs, mobility requirements, and environmental conditions. This dynamic adaptability allows the system to optimize performance for each specific situation while maintaining a relatively simple base architecture, as the complexity is activated only when needed.
3Productivity
If phase comparison method is used for muscle activation detection, then productivity and response speed are improved, but measurement precision may be affected by noise interference
Solution Approach 1:
The system incorporates feedback mechanisms where the phase comparator continuously monitors the phase relationship between sEMG signals and provides real-time feedback to the control system. This feedback loop enables dynamic adjustment of detection thresholds and parameters based on actual signal conditions, allowing the system to maintain high response speed while compensating for noise interference through adaptive decision-making.
Solution Approach 2:
The system performs preliminary signal processing and phase relationship analysis before final muscle activation determination. By pre-processing the sEMG signals to extract phase information and establish baseline relationships, the system prepares the data in advance for rapid decision-making. This preliminary action enables fast real-time detection while reducing the impact of noise, as the critical phase relationships are established before noisy conditions can interfere with final measurements.
Data Source
AI summary
A muscle activation detection apparatus includes a first surface electromyogram (sEMG) sensor arranged to receive a first sEMG signal associated with a user; a second SEMG sensor arranged to receive a second sEMG signal associated with the user; and a processing unit configured to determine the muscle contraction of the user based on the first and second sEMG signals.