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A 3D human-machine integrated design and analysis framework for squat exercises with a Smith machine

Title: A 3D human-machine integrated design and analysis framework for squat exercises with a Smith machine
Authors: Lee, H
Jung, M
Lee, K-K
Lee, SH
Item Type: Journal Article
Abstract: In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human–machine–environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines.
Issue Date: 6-Feb-2017
Date of Acceptance: 29-Jan-2017
URI: http://hdl.handle.net/10044/1/66767
DOI: https://dx.doi.org/10.3390/s17020299
ISSN: 1424-2818
Publisher: MDPI AG
Journal / Book Title: Sensors
Volume: 17
Issue: 2
Copyright Statement: © 2017 The Authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0 - https://creativecommons.org/licenses/by/4.0/).
Keywords: Science & Technology
Physical Sciences
Technology
Chemistry, Analytical
Electrochemistry
Instruments & Instrumentation
Chemistry
squat
biomechanical analysis
musculoskeletal model
Gaussian process regression
motion generation
digital human modeling
INVERSE KINEMATICS
HUMAN MOTION
BIOMECHANICAL ANALYSIS
KNEE BIOMECHANICS
FORCE
ENVIRONMENTS
SIMULATION
RESISTANCE
WALKING
MODELS
0301 Analytical Chemistry
0906 Electrical And Electronic Engineering
Analytical Chemistry
Publication Status: Published
Article Number: 299
Online Publication Date: 2017-02-06
Appears in Collections:Bioengineering
Faculty of Engineering