Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation
Abstract Background Virtual and augmented reality (AR) have become popular modalities for training myoelectric prosthesis control with upper-limb amputees. While some systems have shown moderate success, it is unclear how well the complex motor skills learned in an AR simulation transfer to completi...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-01-01
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| Series: | Journal of NeuroEngineering and Rehabilitation |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12984-023-01136-5 |
| _version_ | 1811175939902537728 |
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| author | Christopher L. Hunt Yinghe Sun Shipeng Wang Ahmed W. Shehata Jacqueline S. Hebert Marlis Gonzalez-Fernandez Rahul R. Kaliki Nitish V. Thakor |
| author_facet | Christopher L. Hunt Yinghe Sun Shipeng Wang Ahmed W. Shehata Jacqueline S. Hebert Marlis Gonzalez-Fernandez Rahul R. Kaliki Nitish V. Thakor |
| author_sort | Christopher L. Hunt |
| collection | DOAJ |
| description | Abstract Background Virtual and augmented reality (AR) have become popular modalities for training myoelectric prosthesis control with upper-limb amputees. While some systems have shown moderate success, it is unclear how well the complex motor skills learned in an AR simulation transfer to completing the same tasks in physical reality. Limb loading is a possible dimension of motor skill execution that is absent in current AR solutions that may help to increase skill transfer between the virtual and physical domains. Methods We implemented an immersive AR environment where individuals could operate a myoelectric virtual prosthesis to accomplish a variety of object relocation manipulations. Intact limb participants were separated into three groups, the load control (CGLD; $$N=4$$ N = 4 ), the AR control (CGAR; $$N=4$$ N = 4 ), and the experimental group (EG; $$N=4$$ N = 4 ). Both the CGAR and EG completed a 5-session prosthesis training protocol in AR while the CGLD performed simple muscle training. The EG attempted manipulations in AR while undergoing limb loading. The CGAR attempted the same manipulations without loading. All participants performed the same manipulations in physical reality while operating a real prosthesis pre- and post-training. The main outcome measure was the change in the number of manipulations completed during the physical reality assessments (i.e. completion rate). Secondary outcomes included movement kinematics and visuomotor behavior. Results The EG experienced a greater increase in completion rate post-training than both the CGAR and CGLD. This performance increase was accompanied by a shorter motor learning phase, the EG’s performance saturating in less sessions of AR training than the CGAR. Conclusion The results demonstrated that limb loading plays an important role in transferring complex motor skills learned in virtual spaces to their physical reality analogs. While participants who did not receive limb loading were able to receive some functional benefit from AR training, participants who received the loading experienced a greater positive change in motor performance with their performance saturating in fewer training sessions. |
| first_indexed | 2024-04-10T19:45:12Z |
| format | Article |
| id | doaj.art-667cd7d37e0340e382fae8c258e883d1 |
| institution | Directory Open Access Journal |
| issn | 1743-0003 |
| language | English |
| last_indexed | 2024-04-10T19:45:12Z |
| publishDate | 2023-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of NeuroEngineering and Rehabilitation |
| spelling | doaj.art-667cd7d37e0340e382fae8c258e883d12023-01-29T12:06:04ZengBMCJournal of NeuroEngineering and Rehabilitation1743-00032023-01-0120111410.1186/s12984-023-01136-5Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitationChristopher L. Hunt0Yinghe Sun1Shipeng Wang2Ahmed W. Shehata3Jacqueline S. Hebert4Marlis Gonzalez-Fernandez5Rahul R. Kaliki6Nitish V. Thakor7Department of Biomedical Engineering, The Johns Hopkins UniversityDepartment of Electrical and Computer Engineering, Tufts UniversityDepartment of Biomedical Engineering, The Johns Hopkins UniversityDivision of Physical Medicine & Rehabilitation, University of AlbertaDivision of Physical Medicine & Rehabilitation, University of AlbertaDepartment of Physical Medicine and Rehabilitation, The Johns Hopkins UniversityDepartment of Biomedical Engineering, The Johns Hopkins UniversityDepartment of Biomedical Engineering, The Johns Hopkins UniversityAbstract Background Virtual and augmented reality (AR) have become popular modalities for training myoelectric prosthesis control with upper-limb amputees. While some systems have shown moderate success, it is unclear how well the complex motor skills learned in an AR simulation transfer to completing the same tasks in physical reality. Limb loading is a possible dimension of motor skill execution that is absent in current AR solutions that may help to increase skill transfer between the virtual and physical domains. Methods We implemented an immersive AR environment where individuals could operate a myoelectric virtual prosthesis to accomplish a variety of object relocation manipulations. Intact limb participants were separated into three groups, the load control (CGLD; $$N=4$$ N = 4 ), the AR control (CGAR; $$N=4$$ N = 4 ), and the experimental group (EG; $$N=4$$ N = 4 ). Both the CGAR and EG completed a 5-session prosthesis training protocol in AR while the CGLD performed simple muscle training. The EG attempted manipulations in AR while undergoing limb loading. The CGAR attempted the same manipulations without loading. All participants performed the same manipulations in physical reality while operating a real prosthesis pre- and post-training. The main outcome measure was the change in the number of manipulations completed during the physical reality assessments (i.e. completion rate). Secondary outcomes included movement kinematics and visuomotor behavior. Results The EG experienced a greater increase in completion rate post-training than both the CGAR and CGLD. This performance increase was accompanied by a shorter motor learning phase, the EG’s performance saturating in less sessions of AR training than the CGAR. Conclusion The results demonstrated that limb loading plays an important role in transferring complex motor skills learned in virtual spaces to their physical reality analogs. While participants who did not receive limb loading were able to receive some functional benefit from AR training, participants who received the loading experienced a greater positive change in motor performance with their performance saturating in fewer training sessions.https://doi.org/10.1186/s12984-023-01136-5Upper-limb prosthesesMyoelectric controlAugmented realityProprioception |
| spellingShingle | Christopher L. Hunt Yinghe Sun Shipeng Wang Ahmed W. Shehata Jacqueline S. Hebert Marlis Gonzalez-Fernandez Rahul R. Kaliki Nitish V. Thakor Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation Journal of NeuroEngineering and Rehabilitation Upper-limb prostheses Myoelectric control Augmented reality Proprioception |
| title | Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation |
| title_full | Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation |
| title_fullStr | Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation |
| title_full_unstemmed | Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation |
| title_short | Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation |
| title_sort | limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation |
| topic | Upper-limb prostheses Myoelectric control Augmented reality Proprioception |
| url | https://doi.org/10.1186/s12984-023-01136-5 |
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