AIMC Topic: Lifting
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Evaluating adaptiveness of an active back exosuit for dynamic lifting and maximum range of motion.
Ergonomics
Jul 23, 2023
Back exosuits deliver mechanical assistance to reduce the risk of back injury, however, minimising restriction is critical for adoption. We developed the adaptive impedance controller to minimise restriction while maintaining assistance by modulating...
A deep learning approach for lower back-pain risk prediction during manual lifting.
PloS one
Feb 19, 2021
Occupationally-induced back pain is a leading cause of reduced productivity in industry. Detecting when a worker is lifting incorrectly and at increased risk of back injury presents significant possible benefits. These include increased quality of li...
Mitigation of ocular artifacts for EEG signal using improved earth worm optimization-based neural network and lifting wavelet transform.
Computer methods in biomechanics and biomedical engineering
Nov 27, 2020
An Electroencephalogram (EEG) is often tarnished by various categories of artifacts. Numerous efforts have been taken to improve its quality by eliminating the artifacts. The EEG involves the biological artifacts (ocular artifacts, ECG and EMG artifa...
A novel vision-based real-time method for evaluating postural risk factors associated with musculoskeletal disorders.
Applied ergonomics
May 4, 2020
Real-time risk assessment for work-related musculoskeletal disorders (MSD) has been a challenging research problem. Previous methods such as using depth cameras suffered from limited visual range and wearable sensors could cause intrusiveness to the ...
Measuring Biomechanical Risk in Lifting Load Tasks Through Wearable System and Machine-Learning Approach.
Sensors (Basel, Switzerland)
Mar 11, 2020
Ergonomics evaluation through measurements of biomechanical parameters in real time has a great potential in reducing non-fatal occupational injuries, such as work-related musculoskeletal disorders. Assuming a correct posture guarantees the avoidance...
A Deep Neural Network-based method for estimation of 3D lifting motions.
Journal of biomechanics
Dec 19, 2018
The aim of this study is developing and validating a Deep Neural Network (DNN) based method for 3D pose estimation during lifting. The proposed DNN based method addresses problems associated with marker-based motion capture systems like excessive pre...
Artificial neural networks to predict 3D spinal posture in reaching and lifting activities; Applications in biomechanical models.
Journal of biomechanics
Jul 15, 2016
Spinal posture is a crucial input in biomechanical models and an essential factor in ergonomics investigations to evaluate risk of low back injury. In vivo measurement of spinal posture through the common motion capture techniques is limited to equip...
Robot-supported upper limb training in a virtual learning environment : a pilot randomized controlled trial in persons with MS.
Journal of neuroengineering and rehabilitation
Jul 23, 2015
BACKGROUND: Despite the functional impact of upper limb dysfunction in multiple sclerosis (MS), effects of intensive exercise programs and specifically robot-supported training have been rarely investigated in persons with advanced MS.
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