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Ehsan Rashedi
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Assessing the influence of a passive, upper extremity exoskeletal vest for tasks requiring arm elevation: Part I–“Expected” effects on discomfort, shoulder muscle activity, and …
S Kim, MA Nussbaum, MIM Esfahani, MM Alemi, S Alabdulkarim, ...
Applied ergonomics 70, 315-322, 2018
2852018
Assessing the influence of a passive, upper extremity exoskeletal vest for tasks requiring arm elevation: Part II–“Unexpected” effects on shoulder motion, balance, and spine …
S Kim, MA Nussbaum, MIM Esfahani, MM Alemi, B Jia, E Rashedi
Applied ergonomics 70, 323-330, 2018
2372018
Ergonomic evaluation of a wearable assistive device for overhead work
E Rashedi, S Kim, MA Nussbaum, MJ Agnew
Ergonomics 57 (12), 1864-1874, 2014
2092014
Risk assessment of occupational injuries using Accident Severity Grade
N Azadeh-Fard, A Schuh, E Rashedi, JA Camelio
Safety science 76, 160-167, 2015
892015
Using a motion sensor to categorize nonspecific low back pain patients: a machine learning approach
M Abdollahi, S Ashouri, M Abedi, N Azadeh-Fard, M Parnianpour, ...
Sensors 20 (12), 3600, 2020
662020
A review of occupationally–relevant models of localised muscle fatigue
E Rashedi, MA Nussbaum
International journal of human factors modelling and simulation 5 (1), 61-80, 2015
542015
A forecasting framework for predicting perceived fatigue: Using time series methods to forecast ratings of perceived exertion with features from wearable sensors
S Hajifar, H Sun, FM Megahed, LA Jones-Farmer, E Rashedi, LA Cavuoto
Applied Ergonomics 90, 103262, 2021
522021
Trunk motion system (TMS) using printed body worn sensor (BWS) via data fusion approach
MI Mokhlespour Esfahani, O Zobeiri, B Moshiri, R Narimani, M Mehravar, ...
Sensors 17 (1), 112, 2017
502017
A systematic review on evaluation strategies for field assessment of upper-body industrial exoskeletons: Current practices and future trends
PM Kuber, M Abdollahi, MM Alemi, E Rashedi
Annals of Biomedical Engineering 50 (10), 1203-1231, 2022
462022
Cycle time influences the development of muscle fatigue at low to moderate levels of intermittent muscle contraction
E Rashedi, MA Nussbaum
Journal of Electromyography and Kinesiology 28, 37-45, 2016
452016
Smartphone-based human fatigue level detection using machine learning approaches
S Karvekar, M Abdollahi, E Rashedi
Ergonomics 64 (5), 600-612, 2021
442021
Product ergonomics in industrial exoskeletons: potential enhancements for workforce efficiency and safety
PM Kuber, E Rashedi
TheoreTical issues in ergonomics science 22 (6), 729-752, 2020
432020
Impact of task design on task performance and injury risk: case study of a simulated drilling task
S Alabdulkarim, MA Nussbaum, E Rashedi, S Kim, M Agnew, R Gardner
Ergonomics 60 (6), 851-866, 2017
392017
Design and development of a hand robotic rehabilitation device for post stroke patients
E Rashedi, A Mirbagheri, B Taheri, F Farahmand, GR Vossoughi, ...
2009 Annual International Conference of the IEEE Engineering in Medicine and …, 2009
372009
How does the central nervous system address the kinetic redundancy in the lumbar spine? Three-dimensional isometric exertions with 18 Hill-model-based muscle fascicles at the …
E Rashedi, K Khalaf, MR Nassajian, B Nasseroleslami, M Parnianpour
Proceedings of the Institution of Mechanical Engineers, Part H: Journal of …, 2010
35*2010
The influence of mechanical vibration on local and central balance control
H Ehsani, J Mohler, V Marlinski, E Rashedi, N Toosizadeh
Journal of biomechanics 71, 59-66, 2018
322018
A systematic review of fall risk factors in stroke survivors: towards improved assessment platforms and protocols
M Abdollahi, N Whitton, R Zand, M Dombovy, M Parnianpour, K Khalaf, ...
Frontiers in bioengineering and biotechnology 10, 910698, 2022
292022
Mathematical models of localized muscle fatigue: sensitivity analysis and assessment of two occupationally-relevant models
E Rashedi, MA Nussbaum
PloS one 10 (12), e0143872, 2015
272015
Kinematic analysis of 360 turning in stroke survivors using wearable motion sensors
M Abdollahi, PM Kuber, M Shiraishi, R Soangra, E Rashedi
Sensors 22 (1), 385, 2022
232022
A data-driven model to identify fatigue level based on the motion data from a smartphone
S Karvekar, M Abdollahi, E Rashedi
BioRxiv, 796854, 2019
212019
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Artiklar 1–20