Decoding individuated finger flexions with Implantable MyoElectric Sensors.

Justin J. Baker; Dimitri Yatsenko; Jack F. Schorsch; Glenn A. DeMichele; Phil R. Troyk; Douglas T. Hutchinson; Richard F ff Weir; Gregory Clark; Bradley Greger

Decoding individuated finger flexions with Implantable MyoElectric Sensors.

Justin J. Baker, Dimitri Yatsenko, Jack F. Schorsch, Glenn A. DeMichele, Phil R. Troyk, Douglas T. Hutchinson, Richard F ff Weir, Gregory Clark, Bradley Greger

Research output: Contribution to journal › Article › peer-review

Abstract

We trained a rhesus monkey to perform randomly cued, individuated finger flexions of the thumb, index, and middle finger. Nine Implantable MyoElectric Sensors (IMES) were then surgically implanted into the finger muscles of the monkey's forearm, without any observable adverse chronic effects. Using an inductive link, we wirelessly recorded EMG from the IMES as the monkey performed a finger flexion task. A principal components analysis (PCA) based algorithm was used to decode which finger switch was pressed based on the recorded EMG. This algorithm correctly decoded which finger was moved 89% of the time. These results demonstrate that IMES offer a safe and highly promising approach for providing intuitive, dexterous control of artificial limbs and hands after amputation.

Original language	English (US)
Pages (from-to)	193-196
Number of pages	4
Journal	Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
State	Published - 2008
Externally published	Yes

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Signal Processing
Biomedical Engineering
Health Informatics

Cite this

Baker, J. J., Yatsenko, D., Schorsch, J. F., DeMichele, G. A., Troyk, P. R., Hutchinson, D. T., Weir, R. F. F., Clark, G., & Greger, B. (2008). Decoding individuated finger flexions with Implantable MyoElectric Sensors. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 193-196.

Decoding individuated finger flexions with Implantable MyoElectric Sensors. / Baker, Justin J.; Yatsenko, Dimitri; Schorsch, Jack F. et al.
In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2008, p. 193-196.

Research output: Contribution to journal › Article › peer-review

Baker, JJ, Yatsenko, D, Schorsch, JF, DeMichele, GA, Troyk, PR, Hutchinson, DT, Weir, RFF, Clark, G & Greger, B 2008, 'Decoding individuated finger flexions with Implantable MyoElectric Sensors.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, pp. 193-196.

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abstract = "We trained a rhesus monkey to perform randomly cued, individuated finger flexions of the thumb, index, and middle finger. Nine Implantable MyoElectric Sensors (IMES) were then surgically implanted into the finger muscles of the monkey's forearm, without any observable adverse chronic effects. Using an inductive link, we wirelessly recorded EMG from the IMES as the monkey performed a finger flexion task. A principal components analysis (PCA) based algorithm was used to decode which finger switch was pressed based on the recorded EMG. This algorithm correctly decoded which finger was moved 89% of the time. These results demonstrate that IMES offer a safe and highly promising approach for providing intuitive, dexterous control of artificial limbs and hands after amputation.",

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Decoding individuated finger flexions with Implantable MyoElectric Sensors.

Abstract

ASJC Scopus subject areas

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