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前臂压力特征作为握力的预测指标。

Pressure signature of forearm as predictor of grip force.

作者信息

Wininger Michael, Kim Nam-Hun, Craelius William

机构信息

Department of Biomedical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.

出版信息

J Rehabil Res Dev. 2008;45(6):883-92. doi: 10.1682/jrrd.2007.11.0187.

Abstract

We studied the relationship between grip force and external forearm pressure in nondisabled subjects using force myography (FMG). FMG uses a sensorized cuff surrounding the forearm to register the distributed mechanical force, detecting pressure on the sensors generated by the volumetric changes of the underlying musculo-tendinous complex. Each of nine nondisabled subjects donned the FMG cuff and applied grip forces to a cylindrical dynamometer; grip forces ranged from 0% to 100% of the subjects' maximum voluntary contraction. The cuff was positioned with seven force sensors located on both the anterior and posterior surfaces of the proximal forearm, but no attempt was made to match sensor placement with particular muscles or sites. Grip prediction was simply encoded as the rectified sum of the FMG sensor outputs. During grip and release cycles, the FMG waveforms of each subject correlated closely with his or her force waveforms (r > 0.89). FMG also correlated highly with the timing of grip onset and release (intraclass correlation coefficient (ICC(A,2)) = 0.99) and time to peak (ICC(A,2) = 0.91), with negligible lag. These results demonstrate that when applied to the forearm, FMG represents a grip force signature that may be useful for near-real-time proportional control of upper-limb prosthetic devices.

摘要

我们使用力肌电图(FMG)研究了非残疾受试者握力与前臂外部压力之间的关系。FMG使用围绕前臂的传感袖带记录分布的机械力,检测由潜在的肌肉肌腱复合体体积变化在传感器上产生的压力。九名非残疾受试者每人佩戴FMG袖带,并对圆柱形测力计施加握力;握力范围为受试者最大自主收缩力的0%至100%。袖带的位置是在前臂近端的前后表面各有七个力传感器,但没有尝试将传感器位置与特定肌肉或部位相匹配。握力预测简单地编码为FMG传感器输出的整流和。在握力和释放周期中,每个受试者的FMG波形与其力波形密切相关(r>0.89)。FMG与握力开始和释放的时间(组内相关系数(ICC(A,2))=0.99)以及达到峰值的时间(ICC(A,2)=0.91)也高度相关,滞后可忽略不计。这些结果表明,当应用于前臂时,FMG代表一种握力特征,可能有助于上肢假肢装置的近实时比例控制。

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