Application of Artificial Neural Network for Successful Prediction of Lower Limb Dynamics and Improvement in the Mathematical Representation of Knee Dynamics in Human Locomotion

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The motivating factor behind this research is the significance and demand for developing relatively affordable yet effective assistive technologies for disabled people. In the presented work, an intelligent model that predicts the lower limb joint angles for an entire gait cycle and a model that modifies the constant terms of the average value-based modeling representation of the knee dynamics are both developed through the application of artificial neural networks (ANN). Hip and knee joint angles were predicted using a model with ground reaction force (GRF) and joint angle being input parameters. The coefficients of correlation and determination values of the model were found to be close to the ideal value, while the mean square error value was determined to be within the tolerance limit. In another developed model, the linear displacement of a human gait cycle was predicted based on the inputs like angular displacement, velocity, and acceleration of the hip and knee joints. The average value-based modeling representation of the knee dynamics was more accurately represented after obtaining the modified values of the constant terms (C0, C1, C2 ). The resulting models can be used to design and develop assistive technologies for physically disabled people, thereby enabling their reintegration into society and helping them to lead normal lives.

Original languageEnglish
Title of host publicationIntelligent Control, Robotics, and Industrial Automation - Proceedings of International Conference, RCAAI 2022
EditorsSanjay Sharma, Bidyadhar Subudhi, Umesh Kumar Sahu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages921-932
Number of pages12
ISBN (Print)9789819946334
DOIs
Publication statusPublished - 2023
EventInternational Conference on Robotics, Control, Automation and Artificial Intelligence, RCAAI 2022 - Virtual, Online
Duration: 24-11-202226-11-2022

Publication series

NameLecture Notes in Electrical Engineering
Volume1066 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Robotics, Control, Automation and Artificial Intelligence, RCAAI 2022
CityVirtual, Online
Period24-11-2226-11-22

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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