A Semi-Autonomous Hierarchical Control Framework for Prosthetic Hands Inspired by Dual Streams of Human.

Xuanyi Zhou, Jianhua Zhang, Bangchu Yang, Xiaolong Ma, Hao Fu, Shibo Cai, Guanjun Bao

Abstract read

In one paragraph

Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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5 · Who and what money

Authors and funding

7 authors.

Xuanyi ZhouCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.ORCID 0000-0001-9584-9426

Jianhua ZhangSchool of Mechanical Engineering, Beijing University of Science and Technology, Beijing 100083, China.

Bangchu YangCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.

Xiaolong MaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.ORCID 0000-0002-6666-6775

Hao FuCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.

Shibo CaiCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.

Guanjun BaoCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.ORCID 0000-0002-7184-3510

Funding

National Natural Science Foundation of China 51775499the Fundamental Research Funds for the Provincial Universities of Zhejiang RF-C2019004the Key Research and Development Program of Zhejiang 2021C04015

6 · The paper itself

Abstract

The routine use of prosthetic hands significantly enhances amputees' daily lives, yet it often introduces cognitive load and reduces reaction speed. To address this issue, we introduce a wearable semi-autonomous hierarchical control framework tailored for amputees. Drawing inspiration from the visual processing stream in humans, a fully autonomous bionic controller is integrated into the prosthetic hand control system to offload cognitive burden, complemented by a Human-in-the-Loop (HIL) control method. In the ventral-stream phase, the controller integrates multi-modal information from the user's hand-eye coordination and biological instincts to analyze the user's movement intention and manipulate primitive switches in the variable domain of view. Transitioning to the dorsal-stream phase, precise force control is attained through the HIL control strategy, combining feedback from the prosthetic hand's sensors and the user's electromyographic (EMG) signals. The effectiveness of the proposed interface is demonstrated by the experimental results. Our approach presents a more effective method of interaction between a robotic control system and the human.

Indexed as

control strategygrasphuman inspiredmanipulationprosthetic hand

Identifiers

PMID38275458

DOI10.3390/biomimetics9010062

PMCPMC10813160

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.