@inbook{76c341d881a34581a7426a7a051caf38,
title = "Linear prediction model for joint movement of lower extremity",
abstract = "Human gait analysis is an emerging area that has a wide application in medical science specially exoskeleton-based rehabilitation robots. In this paper, a linear time-series-based prediction models have been proposed for joint movement for the lower extremity. The joint movement data is collected at RAMAN Lab, MNIT Jaipur. Experimental results indicate that this approach is better than feedforward neural network in the case of linearly correlated data, considering mean absolute percentage error as an evaluation measure. The proposed prediction model could be used for efficient control of lower extremity robot-assisted device for a smooth gait for the patients.",
keywords = "Gait analysis, Joint angles, Lower extremities kinematics, Neural network, Time-series-based prediction",
author = "Chandra Prakash and A. Sujil and Rajesh Kumar and Namita Mittal",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2019",
year = "2019",
doi = "10.1007/978-981-10-8639-7_24",
language = "English",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "235--243",
booktitle = "Advances in Intelligent Systems and Computing",
address = "Germany",
}