Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration
The human-in-the-loop technology requires studies on sensory-motor characteristics of each hand for an effective human–robot collaboration. This study aims to investigate the differences in visuomotor control between the dominant (DH) and non-dominant hands in tracking a target in the three-dimensio...
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MDPI AG
2020-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/21/6368 |
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| author | Hanjin Jo Woong Choi Geonhui Lee Wookhyun Park Jaehyo Kim |
| author_facet | Hanjin Jo Woong Choi Geonhui Lee Wookhyun Park Jaehyo Kim |
| author_sort | Hanjin Jo |
| collection | DOAJ |
| description | The human-in-the-loop technology requires studies on sensory-motor characteristics of each hand for an effective human–robot collaboration. This study aims to investigate the differences in visuomotor control between the dominant (DH) and non-dominant hands in tracking a target in the three-dimensional space. We compared the circular tracking performances of the hands on the frontal plane of the virtual reality space in terms of radial position error (Δ<i>R</i>), phase error (Δ<i>θ</i>), acceleration error (Δ<i>a</i>), and dimensionless squared jerk (<i>DSJ</i>) at four different speeds for 30 subjects. Δ<i>R</i> and Δ<i>θ</i> significantly differed at relatively high speeds (Δ<i>R</i>: 0.5 Hz; Δ<i>θ</i>: <i>0</i>.5, 0.75 Hz), with maximum values of ≤1% compared to the target trajectory radius. <i>DSJ</i> significantly differed only at low speeds (0.125, 0.25 Hz), whereas Δ<i>a</i> significantly differed at all speeds. In summary, the feedback-control mechanism of the DH has a wider range of speed control capability and is efficient according to an energy saving model. The central nervous system (CNS) uses different models for the two hands, which react dissimilarly. Despite the precise control of the DH, both hands exhibited dependences on limb kinematic properties at high speeds (0.75 Hz). Thus, the CNS uses a different strategy according to the model for optimal results. |
| first_indexed | 2024-03-10T15:00:35Z |
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| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T15:00:35Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-252d6e15f41e43c9aca2792f0fed23a12023-11-20T20:12:24ZengMDPI AGSensors1424-82202020-11-012021636810.3390/s20216368Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot CollaborationHanjin Jo0Woong Choi1Geonhui Lee2Wookhyun Park3Jaehyo Kim4Department of Mechanical and Control Engineering, Handong Global University, Pohang 37554, KoreaDepartment of Information and Computer Engineering, National Institute of Technology, Gunma College, Maebashi 371–8530, JapanDepartment of Mechanical and Control Engineering, Handong Global University, Pohang 37554, KoreaDepartment of Mechanical and Control Engineering, Handong Global University, Pohang 37554, KoreaDepartment of Mechanical and Control Engineering, Handong Global University, Pohang 37554, KoreaThe human-in-the-loop technology requires studies on sensory-motor characteristics of each hand for an effective human–robot collaboration. This study aims to investigate the differences in visuomotor control between the dominant (DH) and non-dominant hands in tracking a target in the three-dimensional space. We compared the circular tracking performances of the hands on the frontal plane of the virtual reality space in terms of radial position error (Δ<i>R</i>), phase error (Δ<i>θ</i>), acceleration error (Δ<i>a</i>), and dimensionless squared jerk (<i>DSJ</i>) at four different speeds for 30 subjects. Δ<i>R</i> and Δ<i>θ</i> significantly differed at relatively high speeds (Δ<i>R</i>: 0.5 Hz; Δ<i>θ</i>: <i>0</i>.5, 0.75 Hz), with maximum values of ≤1% compared to the target trajectory radius. <i>DSJ</i> significantly differed only at low speeds (0.125, 0.25 Hz), whereas Δ<i>a</i> significantly differed at all speeds. In summary, the feedback-control mechanism of the DH has a wider range of speed control capability and is efficient according to an energy saving model. The central nervous system (CNS) uses different models for the two hands, which react dissimilarly. Despite the precise control of the DH, both hands exhibited dependences on limb kinematic properties at high speeds (0.75 Hz). Thus, the CNS uses a different strategy according to the model for optimal results.https://www.mdpi.com/1424-8220/20/21/6368visuomotorhand dominancecontrol mechanismspatio-temporaltracking target |
| spellingShingle | Hanjin Jo Woong Choi Geonhui Lee Wookhyun Park Jaehyo Kim Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration Sensors visuomotor hand dominance control mechanism spatio-temporal tracking target |
| title | Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration |
| title_full | Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration |
| title_fullStr | Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration |
| title_full_unstemmed | Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration |
| title_short | Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration |
| title_sort | analysis of visuo motor control between dominant hand and non dominant hand for effective human robot collaboration |
| topic | visuomotor hand dominance control mechanism spatio-temporal tracking target |
| url | https://www.mdpi.com/1424-8220/20/21/6368 |
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