Convolutional LSTM: a deep learning approach to predict shoulder joint reaction forces-Reference-Cited by-同舟云学术

Convolutional LSTM: a deep learning approach to predict shoulder joint reaction forces

Published:2022-03-02 Issue:1 Volume:26 Page:65-77
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Mubarrat S. T.¹,Chowdhury S.¹

Affiliation:

1. Department of Industrial, Manufacturing, and Systems Engineering, Texas Tech University, Lubbock, TX, USA

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2022.2045974

Reference40 articles.

1. null

2. Andrews JR, Wilk KE, Reinold MM. 2008. The Athlete's Shoulder E-Book. 2nd ed. [London, UK]: Elsevier Health Sciences.

3. Relative performances of artificial neural network and regression mapping tools in evaluation of spinal loads and muscle forces during static lifting

4. In vivo glenohumeral contact forces—Measurements in the first patient 7 months postoperatively

5. Bureau of Labor Statistics USDoL. 2019. Number, incidence rate, and median days away from work for nonfatal occupational injuries and illnesses involving days away from work for musculoskeletal disorders by part of body and ownership, National, 2018. [accessed 2020 February 5]. https://www.bls.gov/iif/oshwc/osh/case/msd_cd_r2_00_2018.xlsx.

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