@inproceedings{3f0c6cac26a2457bb1bb7a2e8f5d6584,
title = "Identifying inverse human arm dynamics using a robotic testbed",
abstract = "We present a method to experimentally identify the inverse dynamics of a human arm. We drive a person's hand with a robot along smooth reaching trajectories while measuring the motion of the shoulder and elbow joints and the force required to move the hand. We fit a model that predicts the shoulder and elbow joint torques required to achieve a desired arm motion. This torque can be supplied by functional electrical stimulation of muscles to control the arm of a person paralyzed by spinal cord injury. Errors in predictions of the joint torques for a subject without spinal cord injury were less than 20% of the maximum torques observed in the identification experiments. In most cases a semiparametric Gaussian process model predicted joint torques with equal or less error than a nonparametric Gaussian process model or a parametric model.",
author = "Schearer, {Eric M.} and Liao, {Yu Wei} and Perreault, {Eric J.} and Tresch, {Matthew C.} and Memberg, {William D.} and Kirsch, {Robert F.} and Lynch, {Kevin M.}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 ; Conference date: 14-09-2014 Through 18-09-2014",
year = "2014",
month = oct,
day = "31",
doi = "10.1109/IROS.2014.6943064",
language = "English (US)",
series = "IEEE International Conference on Intelligent Robots and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3585--3591",
booktitle = "IROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems",
address = "United States",
}