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- Liu, YixingKTH,Farkostteknik och Solidmekanik (author)
A method of detecting human movement intentions in real environments
- Article/chapterEnglish2023
Publisher, publication year, extent ...
- Institute of Electrical and Electronics Engineers (IEEE),2023
- printrdacarrier
Numbers
- LIBRIS-ID:oai:DiVA.org:kth-341996
- https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-341996URI
- https://doi.org/10.1109/ICORR58425.2023.10304774DOI
Supplementary language notes
- Language:English
- Summary in:English
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- SwePubSwePub
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Notes
- Part of proceedings ISBN: 979-8-3503-4275-8QC 20240109
- Accurate and timely movement intention detection can facilitate exoskeleton control during transitions between different locomotion modes. Detecting movement intentions in real environments remains a challenge due to unavoidable environmental uncertainties. False movement intention detection may also induce risks of falling and general danger for exoskeleton users. To this end, in this study, we developed a method for detecting human movement intentions in real environments. The proposed method is capable of online self-correcting by implementing a decision fusion layer. Gaze data from an eye tracker and inertial measurement unit (IMU) signals were fused at the feature extraction level and used to predict movement intentions using 2 different methods. Images from the scene camera embedded on the eye tracker were used to identify terrains using a convolutional neural network. The decision fusion was made based on the predicted movement intentions and identified terrains. Four able-bodied participants wearing the eye tracker and 7 IMU sensors took part in the experiments to complete the tasks of level ground walking, ramp ascending, ramp descending, stairs ascending, and stair descending. The recorded experimental data were used to test the feasibility of the proposed method. An overall accuracy of 93.4% was achieved when both feature fusion and decision fusion were used. Fusing gaze data with IMU signals improved the prediction accuracy.
Subject headings and genre
- NATURVETENSKAP Data- och informationsvetenskap Datorseende och robotik hsv//swe
- NATURAL SCIENCES Computer and Information Sciences Computer Vision and Robotics hsv//eng
- Robotic exoskeletons
- movement intention prediction
- eye tracker
- wearable sensor
Added entries (persons, corporate bodies, meetings, titles ...)
- Wan, Zhao-YuanKTH,Farkostteknik och Solidmekanik(Swepub:kth)u1sqx25i (author)
- Wang, RuoliKTH,Farkostteknik och Solidmekanik(Swepub:kth)u1nan6x1 (author)
- Gutierrez-Farewik, Elena,1973-KTH,Farkostteknik och Solidmekanik(Swepub:kth)u1tekbf6 (author)
- KTHFarkostteknik och Solidmekanik (creator_code:org_t)
Related titles
- In:2023 international conference on rehabilitation robotics, ICORR: Institute of Electrical and Electronics Engineers (IEEE)
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