Alternating Electric Field-Based Static Gesture-Recognition Technology
Currently, gesture recognition based on electric-field detection technology has received extensive attention, which is mostly used to recognize the position and the movement of the hand, and rarely used for identification of specific gestures. A non-contact gesture-recognition technology based on th...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/10/2375 |
| _version_ | 1811307224436310016 |
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| author | Haoyu Wei Pengfei Li Kai Tang Wei Wang Xi Chen |
| author_facet | Haoyu Wei Pengfei Li Kai Tang Wei Wang Xi Chen |
| author_sort | Haoyu Wei |
| collection | DOAJ |
| description | Currently, gesture recognition based on electric-field detection technology has received extensive attention, which is mostly used to recognize the position and the movement of the hand, and rarely used for identification of specific gestures. A non-contact gesture-recognition technology based on the alternating electric-field detection scheme is proposed, which can recognize static gestures in different states and dynamic gestures. The influence of the hand on the detection system is analyzed from the principle of electric-field detection. A simulation model of the system is established to investigate the charge density on the hand surface and the potential change of the sensing electrodes. According to the simulation results, the system structure is improved, and the signal-processing circuit is designed to collect the signal of sensing electrodes. By collecting a large amount of data from different operators, the tree-model recognition algorithm is designed and a gesture-recognition experiment is implemented. The results show that the gesture-recognition correct rate is over 90%. With advantages of high response speed, low cost, small volume, and immunity to the surrounding environment, the system could be assembled on a robot that communicates with operators. |
| first_indexed | 2024-04-13T09:00:03Z |
| format | Article |
| id | doaj.art-99a6ea877dc344d4bc034abbfe5bf817 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T09:00:03Z |
| publishDate | 2019-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-99a6ea877dc344d4bc034abbfe5bf8172022-12-22T02:53:09ZengMDPI AGSensors1424-82202019-05-011910237510.3390/s19102375s19102375Alternating Electric Field-Based Static Gesture-Recognition TechnologyHaoyu Wei0Pengfei Li1Kai Tang2Wei Wang3Xi Chen4State Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaCurrently, gesture recognition based on electric-field detection technology has received extensive attention, which is mostly used to recognize the position and the movement of the hand, and rarely used for identification of specific gestures. A non-contact gesture-recognition technology based on the alternating electric-field detection scheme is proposed, which can recognize static gestures in different states and dynamic gestures. The influence of the hand on the detection system is analyzed from the principle of electric-field detection. A simulation model of the system is established to investigate the charge density on the hand surface and the potential change of the sensing electrodes. According to the simulation results, the system structure is improved, and the signal-processing circuit is designed to collect the signal of sensing electrodes. By collecting a large amount of data from different operators, the tree-model recognition algorithm is designed and a gesture-recognition experiment is implemented. The results show that the gesture-recognition correct rate is over 90%. With advantages of high response speed, low cost, small volume, and immunity to the surrounding environment, the system could be assembled on a robot that communicates with operators.https://www.mdpi.com/1424-8220/19/10/2375human–computer interactiongesture recognitionelectric-field detection |
| spellingShingle | Haoyu Wei Pengfei Li Kai Tang Wei Wang Xi Chen Alternating Electric Field-Based Static Gesture-Recognition Technology Sensors human–computer interaction gesture recognition electric-field detection |
| title | Alternating Electric Field-Based Static Gesture-Recognition Technology |
| title_full | Alternating Electric Field-Based Static Gesture-Recognition Technology |
| title_fullStr | Alternating Electric Field-Based Static Gesture-Recognition Technology |
| title_full_unstemmed | Alternating Electric Field-Based Static Gesture-Recognition Technology |
| title_short | Alternating Electric Field-Based Static Gesture-Recognition Technology |
| title_sort | alternating electric field based static gesture recognition technology |
| topic | human–computer interaction gesture recognition electric-field detection |
| url | https://www.mdpi.com/1424-8220/19/10/2375 |
| work_keys_str_mv | AT haoyuwei alternatingelectricfieldbasedstaticgesturerecognitiontechnology AT pengfeili alternatingelectricfieldbasedstaticgesturerecognitiontechnology AT kaitang alternatingelectricfieldbasedstaticgesturerecognitiontechnology AT weiwang alternatingelectricfieldbasedstaticgesturerecognitiontechnology AT xichen alternatingelectricfieldbasedstaticgesturerecognitiontechnology |