Principal components analysis based control of a multi-DoF underactuated prosthetic hand.
Principal components analysis based control of a multi-DoF underactuated prosthetic hand.
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DOI：
10.1186/1743-0003-7-16
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发表时间：
2010-04-23
影响因子：
5.1
通讯作者：
Carrozza MC
中科院分区：
文献类型：
--
作者：
Matrone GC;Cipriani C;Secco EL;Magenes G;Carrozza MC
功能性、可控性和美观性是通过假肢成功实现人手功能替代所要解决的关键问题。假肢不仅应该在形状、功能、感觉、感知和身体归属感方面复制人手，而且还应该以最直观和最简单的方式控制它。目前，假手是通过基于肌电图（EMG）的非侵入性接口来控制的。驱动多自由度（DoF）手以实现手的灵活性意味着选择性地调制许多不同的EMG信号以使每个关节独立地移动，并且这可能需要用户的显著认知努力。基于主成分分析（PCA）的算法被用来驱动具有二维控制输入的16自由度欠驱动假手原型（称为CyberHand），以执行日常生活活动（ADL）中最常用的三种形式。这样的主成分集已直接从假手通过收集其感官数据，同时执行50个不同的把握，并随后用于控制。试验表明，两个独立的输入信号可以成功地用于控制真实的机器人手的姿势，并且可以实现正确的抓握（就涉及的手指、稳定性和姿势而言）。这项工作证明了生物启发系统的有效性，成功地结合了欠驱动，拟人化的手与PCA为基础的控制策略的优势，并开辟了一个直观可控的手假体的发展前景的可能性。
Functionality, controllability and cosmetics are the key issues to be addressed in order to accomplish a successful functional substitution of the human hand by means of a prosthesis. Not only the prosthesis should duplicate the human hand in shape, functionality, sensorization, perception and sense of body-belonging, but it should also be controlled as the natural one, in the most intuitive and undemanding way. At present, prosthetic hands are controlled by means of non-invasive interfaces based on electromyography (EMG). Driving a multi degrees of freedom (DoF) hand for achieving hand dexterity implies to selectively modulate many different EMG signals in order to make each joint move independently, and this could require significant cognitive effort to the user. A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoFs underactuated prosthetic hand prototype (called CyberHand) with a two dimensional control input, in order to perform the three prehensile forms mostly used in Activities of Daily Living (ADLs). Such Principal Components set has been derived directly from the artificial hand by collecting its sensory data while performing 50 different grasps, and subsequently used for control. Trials have shown that two independent input signals can be successfully used to control the posture of a real robotic hand and that correct grasps (in terms of involved fingers, stability and posture) may be achieved. This work demonstrates the effectiveness of a bio-inspired system successfully conjugating the advantages of an underactuated, anthropomorphic hand with a PCA-based control strategy, and opens up promising possibilities for the development of an intuitively controllable hand prosthesis.
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影响因子：
2.5
作者：
Parker, P.;Englehart, K.;Hudgins, B.
通讯作者：
Hudgins, B.
DOI：
10.1007/11553595_104
发表时间：
2005-01-01
期刊：
IMAGE ANALYSIS AND PROCESSING - ICIAP 2005, PROCEEDINGS
影响因子：
--
作者：
Fujiki, R;Arita, D;Taniguchi, R
通讯作者：
Taniguchi, R
影响因子：
4.6
作者：
Jiang, Ning;Englehart, Kevin B.;Parker, Philip A.
通讯作者：
Parker, Philip A.
DOI：
10.1016/0745-7138(85)90015-6
发表时间：
1985-01-01
期刊：
JOURNAL OF MICROCOMPUTER APPLICATIONS
影响因子：
--
作者：
NIGHTINGALE, JM
通讯作者：
NIGHTINGALE, JM
影响因子：
1.9
作者：
Carrozza, M. C.;Cappiello, G.;Micera, S.;Edin, B. B.;Beccai, L.;Cipriani, C.
通讯作者：
Cipriani, C.