Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton
Recognizing locomotion modes is a crucial step in controlling lower-limb exoskeletons/orthoses. Our study proposed a fuzzy-logic-based locomotion mode/transition recognition approach that uses the onrobot inertial sensors for a hip joint exoskeleton (active pelvic orthosis). The method outputs the r...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2021/6673018 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849305285543329792 |
|---|---|
| author | Gang Du Jinchen Zeng Cheng Gong Enhao Zheng |
| author_facet | Gang Du Jinchen Zeng Cheng Gong Enhao Zheng |
| author_sort | Gang Du |
| collection | DOAJ |
| description | Recognizing locomotion modes is a crucial step in controlling lower-limb exoskeletons/orthoses. Our study proposed a fuzzy-logic-based locomotion mode/transition recognition approach that uses the onrobot inertial sensors for a hip joint exoskeleton (active pelvic orthosis). The method outputs the recognition decisions at each extreme point of the hip joint angles purely relying on the integrated inertial sensors. Compared with the related studies, our approach enables calibrations and recognition without additional sensors on the feet. We validated the method by measuring four locomotion modes and eight locomotion transitions on three able-bodied subjects wearing an active pelvic orthosis (APO). The average recognition accuracy was 92.46% for intrasubject crossvalidation and 93.16% for intersubject crossvalidation. The average time delay during the transitions was 1897.9 ms (28.95% one gait cycle). The results were at the same level as the related studies. On the other side, the study is limited in the small sample size of the subjects, and the results are preliminary. Future efforts will be paid on more extensive evaluations in practical applications. |
| format | Article |
| id | doaj-art-07cd9888ee9941ff8ecded8b0b72a251 |
| institution | Kabale University |
| issn | 1176-2322 1754-2103 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-07cd9888ee9941ff8ecded8b0b72a2512025-08-20T03:55:28ZengWileyApplied Bionics and Biomechanics1176-23221754-21032021-01-01202110.1155/2021/66730186673018Locomotion Mode Recognition with Inertial Signals for Hip Joint ExoskeletonGang Du0Jinchen Zeng1Cheng Gong2Enhao Zheng3School of Information Engineering, China University of Geosciences, Beijing 100083, ChinaFaculty of Electrical Engineering, Mathematics and Computer Science, Technische Universiteit Delft, Delft 2600AA, NetherlandsCollege of Engineering, Peking University, Beijing 100871, ChinaThe State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, ChinaRecognizing locomotion modes is a crucial step in controlling lower-limb exoskeletons/orthoses. Our study proposed a fuzzy-logic-based locomotion mode/transition recognition approach that uses the onrobot inertial sensors for a hip joint exoskeleton (active pelvic orthosis). The method outputs the recognition decisions at each extreme point of the hip joint angles purely relying on the integrated inertial sensors. Compared with the related studies, our approach enables calibrations and recognition without additional sensors on the feet. We validated the method by measuring four locomotion modes and eight locomotion transitions on three able-bodied subjects wearing an active pelvic orthosis (APO). The average recognition accuracy was 92.46% for intrasubject crossvalidation and 93.16% for intersubject crossvalidation. The average time delay during the transitions was 1897.9 ms (28.95% one gait cycle). The results were at the same level as the related studies. On the other side, the study is limited in the small sample size of the subjects, and the results are preliminary. Future efforts will be paid on more extensive evaluations in practical applications.http://dx.doi.org/10.1155/2021/6673018 |
| spellingShingle | Gang Du Jinchen Zeng Cheng Gong Enhao Zheng Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton Applied Bionics and Biomechanics |
| title | Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton |
| title_full | Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton |
| title_fullStr | Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton |
| title_full_unstemmed | Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton |
| title_short | Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton |
| title_sort | locomotion mode recognition with inertial signals for hip joint exoskeleton |
| url | http://dx.doi.org/10.1155/2021/6673018 |
| work_keys_str_mv | AT gangdu locomotionmoderecognitionwithinertialsignalsforhipjointexoskeleton AT jinchenzeng locomotionmoderecognitionwithinertialsignalsforhipjointexoskeleton AT chenggong locomotionmoderecognitionwithinertialsignalsforhipjointexoskeleton AT enhaozheng locomotionmoderecognitionwithinertialsignalsforhipjointexoskeleton |