Estimation of Phantom Arm Mechanics About Four Degrees of Freedom After Targeted Muscle Reinnervation

Massimo Sartori, Justin Van De Riet, Dario Farina

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The intuitive control of bionic arms requires estimation of amputee's phantom arm movements from residual muscle bio-electric signals. The functional use of myoelectric arms relies on the ability of controlling large sets of degrees of freedom (>3 DOFs) spanning elbow, forearm, and wrist joints. This would assure optimal hand orientation in any environment. As part of this paper we recorded high-density electromyograms with >190 electrodes from the residual stump of a trans-humeral amputee who underwent targeted muscle reinnervation. We employed clustering to determine eight spatially separated sub-sets of channels sampling electromyograms associated to the actuation of four phantom arm DOFs. We created a large-scale musculoskeletal model of the phantom arm encompassing 33 musculo-tendon units. For the first time, this enabled the accurate electromyography-driven simulation of complex phantom joint rotations about elbow flexion-extension, forearm pronation-supination, wrist flexion-extension, and radial-ulnar deviation. These results support the potential for a new class of bionic limbs that are controlled as natural extensions of the body, an important step toward next-generation prosthetics that mimic human biological functionality and robustness.
Original languageEnglish
Pages (from-to)58-64
Number of pages7
JournalIEEE Transactions on Medical Robotics and Bionics
Volume1
Issue number1
DOIs
Publication statusPublished - 28 Jan 2019

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Mechanics
Arm
Electromyography
Muscles
Bionics
Amputees
Forearm
Wrist Joint
Pronation
Supination
Elbow Joint
Elbow
Wrist
Tendons
Cluster Analysis
Electrodes
Extremities
Hand
Joints

Cite this

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title = "Estimation of Phantom Arm Mechanics About Four Degrees of Freedom After Targeted Muscle Reinnervation",
abstract = "The intuitive control of bionic arms requires estimation of amputee's phantom arm movements from residual muscle bio-electric signals. The functional use of myoelectric arms relies on the ability of controlling large sets of degrees of freedom (>3 DOFs) spanning elbow, forearm, and wrist joints. This would assure optimal hand orientation in any environment. As part of this paper we recorded high-density electromyograms with >190 electrodes from the residual stump of a trans-humeral amputee who underwent targeted muscle reinnervation. We employed clustering to determine eight spatially separated sub-sets of channels sampling electromyograms associated to the actuation of four phantom arm DOFs. We created a large-scale musculoskeletal model of the phantom arm encompassing 33 musculo-tendon units. For the first time, this enabled the accurate electromyography-driven simulation of complex phantom joint rotations about elbow flexion-extension, forearm pronation-supination, wrist flexion-extension, and radial-ulnar deviation. These results support the potential for a new class of bionic limbs that are controlled as natural extensions of the body, an important step toward next-generation prosthetics that mimic human biological functionality and robustness.",
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Estimation of Phantom Arm Mechanics About Four Degrees of Freedom After Targeted Muscle Reinnervation. / Sartori, Massimo; Van De Riet, Justin; Farina, Dario.

In: IEEE Transactions on Medical Robotics and Bionics, Vol. 1, No. 1, 28.01.2019, p. 58-64.

Research output: Contribution to journalArticleAcademicpeer-review

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AB - The intuitive control of bionic arms requires estimation of amputee's phantom arm movements from residual muscle bio-electric signals. The functional use of myoelectric arms relies on the ability of controlling large sets of degrees of freedom (>3 DOFs) spanning elbow, forearm, and wrist joints. This would assure optimal hand orientation in any environment. As part of this paper we recorded high-density electromyograms with >190 electrodes from the residual stump of a trans-humeral amputee who underwent targeted muscle reinnervation. We employed clustering to determine eight spatially separated sub-sets of channels sampling electromyograms associated to the actuation of four phantom arm DOFs. We created a large-scale musculoskeletal model of the phantom arm encompassing 33 musculo-tendon units. For the first time, this enabled the accurate electromyography-driven simulation of complex phantom joint rotations about elbow flexion-extension, forearm pronation-supination, wrist flexion-extension, and radial-ulnar deviation. These results support the potential for a new class of bionic limbs that are controlled as natural extensions of the body, an important step toward next-generation prosthetics that mimic human biological functionality and robustness.

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