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

Sunny, Sithara Mary; Sivanandan, K. S.; Parameswaran, Arun P.; Baiju, T.; Shyamasunder Bhat, N.

doi:10.1007/978-981-99-4634-1_72

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Intelligent Control, Robotics, and Industrial Automation

2023

DOI: 10.1007/978-981-99-4634-1_72

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

Sithara Mary Sunny,

K. S. Sivanandan,

Arun P. Parameswaran

et al.

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2024

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Cited by 1 publication

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Analyzing Lower Limb Dynamics in Human Gait Using Average Value-Based Technique

Sunny,

Sivanandan,

Parameswaran

et al. 2024

Mathematical Problems in Engineering

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The motivation of this study is to develop effective and economical assistive technologies for people with physical disabilities. The novelty in this manuscript is the application of the average value-based technique to accurately represent the involved biomechanics of the lower limb joints during the human gait cycle. This mathematical formulation of lower limb joints’ biomechanics forms the first objective for modeling and final exoskeleton prototype development. To account for modeling the characteristics of human locomotion, the nth-order linear differential equation with constant coefficients is considered with appropriate modification. The physical characteristics of an individual are represented by the constant coefficients (P0, P1, P2, and P3) of the modified infinite series, which are obtained by processing experimental data collected using an optical technique. The differential terms of the infinite series are replaced by difference terms (δbavg, δ2bavg, and δ3bavg) since the data were captured as a set of digital values. The work presented here is based on the experimental results of individuals suitably categorized according to their physical nature like age and other physical structure. The optically monitored positional values of the lower limb joints of the individual subjects while they are completing the gait cycles are used for getting values of different terms of the model. The data collected through the conduct of experiments are used for finding the values of the terms of the differential equation. The model is effectively validated through experimental results. It was determined that the representation’s accuracy fell within the ±5% acceptable tolerance limit. The model is prepared for healthy as well as disabled persons, through which the disability is quantified. The resulting model can be used to develop assistive devices for people with physical disabilities. This results in the rehabilitation process and thereby helps the reintegration into society, subsequently allowing them to lead a normal life.

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Analyzing Lower Limb Dynamics in Human Gait Using Average Value-Based Technique

Sunny,

Sivanandan,

Parameswaran

et al. 2024

Mathematical Problems in Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

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

Cited by 1 publication

References 15 publications

Analyzing Lower Limb Dynamics in Human Gait Using Average Value-Based Technique

Analyzing Lower Limb Dynamics in Human Gait Using Average Value-Based Technique

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