Abstract
This paper presents the design and preliminary experimental validation of a multigrasp myoelectric controller. The described method enables direct and proportional control of multigrasp prosthetic hand motion among nine characteristic postures using two surface electromyography electrodes. To assess the efficacy of the control method, five nonamputee subjects utilized the multigrasp myoelectric controller to command the motion of a virtual prosthesis between random sequences of target hand postures in a series of experimental trials. For comparison, the same subjects also utilized a data glove, worn on their native hand, to command the motion of the virtual prosthesis for similar sequences of target postures during each trial. The time required to transition from posture to posture and the percentage of correctly completed transitions were evaluated to characterize the ability to control the virtual prosthesis using each method. The average overall transition times across all subjects were found to be 1.49 and 0.81 s for the multigrasp myoelectric controller and the native hand, respectively. The average transition completion rates for both were found to be the same (99.2%). Supplemental videos demonstrate the virtual prosthesis experiments, as well as a preliminary hardware implementation.
| Original language | English |
|---|---|
| Article number | 6101579 |
| Pages (from-to) | 58-67 |
| Number of pages | 10 |
| Journal | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Volume | 20 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2012 |
Fingerprint
Keywords
- Biomechatronics
- electromyography (EMG)
- multigrasp prosthesis
- myoelectric control
- transradial prosthesis
ASJC Scopus subject areas
- Neuroscience(all)
- Computer Science Applications
- Biomedical Engineering
- Medicine(all)
Cite this
A method for the control of multigrasp myoelectric prosthetic hands. / Dalley, Skyler Ashton; Varol, Huseyin Atakan; Goldfarb, Michael.
In: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 20, No. 1, 6101579, 01.2012, p. 58-67.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A method for the control of multigrasp myoelectric prosthetic hands
AU - Dalley, Skyler Ashton
AU - Varol, Huseyin Atakan
AU - Goldfarb, Michael
PY - 2012/1
Y1 - 2012/1
N2 - This paper presents the design and preliminary experimental validation of a multigrasp myoelectric controller. The described method enables direct and proportional control of multigrasp prosthetic hand motion among nine characteristic postures using two surface electromyography electrodes. To assess the efficacy of the control method, five nonamputee subjects utilized the multigrasp myoelectric controller to command the motion of a virtual prosthesis between random sequences of target hand postures in a series of experimental trials. For comparison, the same subjects also utilized a data glove, worn on their native hand, to command the motion of the virtual prosthesis for similar sequences of target postures during each trial. The time required to transition from posture to posture and the percentage of correctly completed transitions were evaluated to characterize the ability to control the virtual prosthesis using each method. The average overall transition times across all subjects were found to be 1.49 and 0.81 s for the multigrasp myoelectric controller and the native hand, respectively. The average transition completion rates for both were found to be the same (99.2%). Supplemental videos demonstrate the virtual prosthesis experiments, as well as a preliminary hardware implementation.
AB - This paper presents the design and preliminary experimental validation of a multigrasp myoelectric controller. The described method enables direct and proportional control of multigrasp prosthetic hand motion among nine characteristic postures using two surface electromyography electrodes. To assess the efficacy of the control method, five nonamputee subjects utilized the multigrasp myoelectric controller to command the motion of a virtual prosthesis between random sequences of target hand postures in a series of experimental trials. For comparison, the same subjects also utilized a data glove, worn on their native hand, to command the motion of the virtual prosthesis for similar sequences of target postures during each trial. The time required to transition from posture to posture and the percentage of correctly completed transitions were evaluated to characterize the ability to control the virtual prosthesis using each method. The average overall transition times across all subjects were found to be 1.49 and 0.81 s for the multigrasp myoelectric controller and the native hand, respectively. The average transition completion rates for both were found to be the same (99.2%). Supplemental videos demonstrate the virtual prosthesis experiments, as well as a preliminary hardware implementation.
KW - Biomechatronics
KW - electromyography (EMG)
KW - multigrasp prosthesis
KW - myoelectric control
KW - transradial prosthesis
UR - http://www.scopus.com/inward/record.url?scp=84856484972&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84856484972&partnerID=8YFLogxK
U2 - 10.1109/TNSRE.2011.2175488
DO - 10.1109/TNSRE.2011.2175488
M3 - Article
VL - 20
SP - 58
EP - 67
JO - IEEE Transactions on Neural Systems and Rehabilitation Engineering
JF - IEEE Transactions on Neural Systems and Rehabilitation Engineering
SN - 1534-4320
IS - 1
M1 - 6101579
ER -