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Year | Number of Results |
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2019 | 1 |
2020 | 1 |
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A comparison of augmented feedback and didactic training approaches to reduce spine motion during occupational lifting tasks.
Appl Ergon. 2022 Feb;99:103612. doi: 10.1016/j.apergo.2021.103612. Epub 2021 Oct 29.
Appl Ergon. 2022.
PMID: 34743974
The role of machine learning in the primary prevention of work-related musculoskeletal disorders: A scoping review.
Chan VCH, Ross GB, Clouthier AL, Fischer SL, Graham RB.
Chan VCH, et al.
Appl Ergon. 2022 Jan;98:103574. doi: 10.1016/j.apergo.2021.103574. Epub 2021 Sep 20.
Appl Ergon. 2022.
PMID: 34547578
Free article.
Review.
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A Subject-Specific Approach to Detect Fatigue-Related Changes in Spine Motion Using Wearable Sensors.
Chan VCH, Beaudette SM, Smale KB, Beange KHE, Graham RB.
Chan VCH, et al.
Sensors (Basel). 2020 May 6;20(9):2646. doi: 10.3390/s20092646.
Sensors (Basel). 2020.
PMID: 32384664
Free PMC article.
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Using visual aids to influence manual lifting techniques: acute effects of viewing static images on spine motion.
Chan VCH, Welsh TN, Frost DM, Beach TAC.
Chan VCH, et al.
Int J Occup Saf Ergon. 2021 Jun;27(2):605-612. doi: 10.1080/10803548.2019.1620489. Epub 2019 Jul 7.
Int J Occup Saf Ergon. 2021.
PMID: 31112070
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