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A Muscle Synergy-Inspired Method of Detecting Human Movement Intentions Based on Wearable Sensor Fusion
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- Liu, Yixing (author)
- KTH,Biomekanik,BioMEx
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- Wang, Ruoli (author)
- KTH,Biomekanik
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- Gutierrez-Farewik, Elena, 1973- (author)
- KTH,BioMEx,Biomekanik
- (creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2021
- 2021
- English.
- In: IEEE transactions on neural systems and rehabilitation engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 1534-4320 .- 1558-0210. ; 29, s. 1089-1098
- Journal article (peer-reviewed)
Abstract
Subject headings
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- Detecting human movement intentions is fundamental to neural control of robotic exoskeletons, as it is essential for achieving seamless transitions between different locomotion modes. In this study, we enhanced a muscle synergy-inspired method of locomotion mode identification by fusing the electromyography data with two types of data from wearable sensors (inertial measurement units), namely linear acceleration and angular velocity. From the finite state machine perspective, the enhanced method was used to systematically identify 2 static modes, 7 dynamic modes, and 27 transitions among them. In addition to the five broadly studied modes (level ground walking, ramps ascent/descent, stairs ascent/descent), we identified the transition between different walking speeds and modes of ramp walking at different inclination angles. Seven combinations of sensor fusion were conducted, on experimental data from 8 able-bodied adult subjects, and their classification accuracy and prediction time were compared. Prediction based on a fusion of electromyography and gyroscope (angular velocity) data predicted transitions earlier and with higher accuracy. All transitions and modes were identified with a total average classification accuracy of 94.5% with fused sensor data. For nearly all transitions, we were able to predict the next locomotion mode 300-500ms prior to the step into that mode.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Keyword
- Legged locomotion
- Electromyography
- Stairs
- Muscles
- Feature extraction
- Mechanical sensors
- Exoskeletons
- Intent recognition
- locomotion modes identification
- muscle synergies
- sensor fusion
- robotic exoskeletons
Publication and Content Type
- ref (subject category)
- art (subject category)
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