Lower-limb exoskeleton speed control via plantar EMG waveform length
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Solution Overview
Problem
Conventional walk assist robots lack the ability to recognize and respond to the walking speed intention of users, particularly in gait rehabilitation training, which is essential for effective rehabilitation and independent walking post-rehabilitation.
Innovation Solution
A method using noninvasive surface electromyogram (EMG) signals to recognize the walking speed intention of a user and control the speed of a walk assist robot, incorporating joint angle and plantar pressure signal measurements to determine the stance phase and calculate waveform length, allowing the robot to adjust its speed accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional speed control methods are used in walk assist robots, then the robot can control its own speed, but it cannot recognize or respond to the user's walking speed intention
Solution Approach 1:
The patent replaces conventional mechanical speed control mechanisms with a bio-signal-based control system. Surface electromyogram (EMG) signals from plantar flexor muscles are processed to extract waveform length features, which are then used to recognize walking speed intention. This substitution allows the robot to adapt to user intention without complex mechanical modifications.
Solution Approach 2:
The patent introduces EMG signals as an intermediary between the user's neural intention and the robot's speed control system. The EMG signals from plantar flexor muscles serve as a mediator that translates muscular activation patterns into recognizable walking speed intentions, enabling natural human-robot interaction without direct mechanical coupling.
2Reliability
If EMG signals are used to recognize walking speed intention, then the robot can adapt to user intention, but the system complexity increases due to signal processing requirements
Solution Approach 1:
The patent extracts only the essential feature from EMG signals - the waveform length during the stance phase. By focusing specifically on this single parameter rather than processing the entire EMG signal spectrum, the system achieves reliable walking speed intention recognition while minimizing processing complexity. The waveform length is calculated from surface EMG signals of plantar flexor muscles and serves as the key indicator for speed intention.
Solution Approach 2:
The patent transforms the raw EMG signal into a meaningful parameter (waveform length) that directly correlates with walking speed intention. This parameter transformation simplifies the control system by converting complex bio-electrical signals into a single scalar value that can be directly used for speed regulation, reducing the need for complex multi-parameter processing.
3Measurement precision
If the robot controls walking speed based on EMG waveform length, then it can follow user intention accurately, but the control system becomes more complex
Solution Approach 1:
The patent performs preliminary detection of the stance phase using plantar pressure signals before processing EMG signals for waveform length calculation. By pre-identifying the stance phase boundaries, the system can accurately confine EMG processing to the relevant time window, improving measurement precision while reducing unnecessary processing during swing phase when EMG signals are less informative for speed control.
Data Source
AI summary
A walk assist robot for lower body walking of a walking trainee, including a joint angle signal measurement unit disposed on a joint of the walking trainee, an electromyogram (EMG) signal measurement unit disposed on a muscle related to ankle joint extension of the walking trainee, a plantar pressure signal measurement unit disposed on a sole of the walking trainee, and a control unit to recognize signals measured from the joint angle signal measurement unit, the EMG signal measurement unit and the plantar pressure signal measurement unit and process the signals to recognize a walking speed intention of the walking trainee, wherein the control unit controls a walking speed of the walk assist robot from the walking speed intention of the walking trainee.