Estimation of Lower Limb Joint Angular Velocity From BMI and Walking Speed Using Regression and Neural Network Models for Personalized Gait Control

This paper presents a regression- and neural network-based framework for estimating lower limb joint angular velocity using Body Mass Index (BMI) and walking speed as predictors, aimed at supporting personalized gait control in rehabilitation robotics. Gait data from 24 healthy adults were segmented...

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Главные авторы: Dimas Adiputra, Annisa Salsabila, Helisyah Nur Fadhilah, Rifdatun Ni'Mah, Bahrudin, Kadek Heri Sanjaya, Chaironi Latif
Формат: Artigo
Язык:Inglês
Опубликовано: IEEE 2025-01-01
Серии:IEEE Access
Предметы:
Angular velocity estimation
neural network
regression model
BMI
walking speed
rehabilitation robot
Online-ссылка:https://ieeexplore.ieee.org/document/11248814/
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