People Lifting Patterns—A Reference Dataset for Practitioners

Kluwak, Konrad; Klempous, Ryszard; Chaczko, Zenon; Rozenblit, Jerzy W.; Kulbacki, Marek

doi:10.3390/s21093142

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…Data from OptiTrack were streamed to the Python interface through the Motive 2.0 Optical Motion Capture Software and OptiTrack’s NatNet SDK. The conventional full-body biomechanical model with 39 markers ( Fig 1 , right) was used to capture joint trajectories (see Figure 2 in [ 34 ] for the placement of the entire marker set). The collected data did not contain any identifiable personal information of the participants.…”

Section: Methodsmentioning

confidence: 99%

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A webcam-based machine learning approach for three-dimensional range of motion evaluation

Wang,

Smith,

Zhu

2023

PLoS ONE

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Background Joint range of motion (ROM) is an important quantitative measure for physical therapy. Commonly relying on a goniometer, accurate and reliable ROM measurement requires extensive training and practice. This, in turn, imposes a significant barrier for those who have limited in-person access to healthcare. Objective The current study presents and evaluates an alternative machine learning-based ROM evaluation method that could be remotely accessed via a webcam. Methods To evaluate its reliability, the ROM measurements for a diverse set of joints (neck, spine, and upper and lower extremities) derived using this method were compared to those obtained from a marker-based optical motion capture system. Results Data collected from 25 healthy adults demonstrated that the webcam solution exhibited high test-retest reliability, with substantial to almost perfect intraclass correlation coefficients for most joints. Compared with the marker-based system, the webcam-based system demonstrated substantial to almost perfect inter-rater reliability for some joints, and lower inter-rater reliability for other joints (e.g., shoulder flexion and elbow flexion), which could be attributed to the reduced sensitivity to joint locations at the apex of the movement. Conclusions The proposed webcam-based method exhibited high test-retest and inter-rater reliability, making it a versatile alternative for existing ROM evaluation methods in clinical practice and the tele-implementation of physical therapy and rehabilitation.

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Section: Methodsmentioning

confidence: 99%

“…Overall, there were only four trials (or 0.13% of the total trials) that contained joints relevant to the ROM calculation that had frames with a visibility index of 0.5 or below. 2 in [34] for the placement of the entire marker set). The collected data did not contain any identifiable personal information of the participants.…”

Section: Fig 1 (Left)mentioning

confidence: 99%

A webcam-based machine learning approach for three-dimensional range of motion evaluation

Wang,

Smith,

Zhu

2023

PLoS ONE

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A new approach to assessing the obstetrician's posture and movement during an instrumental forceps delivery

Sorel,

Fradet,

Coste-Mazeau

et al. 2023

Journal of Gynecology Obstetrics and Human Reproduction

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Overcoming Barriers: Sex Disparity in Surgeon Ergonomics

Jacovides,

Guetter,

Crandall

et al. 2024

Journal of the American College of Surgeons

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Background: Musculoskeletal discomfort is widely experienced by surgeons across multiple surgical specialties. Developing technologies and new minimally invasive techniques add further complexity and ergonomic stressors. These stressors differentially affect male and female surgeons, but little is known about the role these gender disparities play in surgical ergonomic stress. We reviewed existing literature to better understand how ergonomic stress varies between male and female surgeons. Study design: A literature search was performed via Pubmed including but not limited to the topics: ergonomics, surgeons, female surgeons, women surgeons, pregnancy, operating room. A review of available quantitative data was performed. Results: Female surgeons endure more pronounced ergonomic discomfort than their male counterparts, with added ergonomic stress associated with pregnancy. Conclusions: A four-fold method is proposed to overcome ergonomic barriers: 1) improved education on prevention and treatment of ergonomic injury for active surgeons and for trainees; 2) increased departmental and institutional support for ergonomic solutions for surgeons; 3) partnerships with industry to study innovative ergonomic solutions; and 4) additional research on the nature of surgical ergonomic challenges and the differential effects of surgical ergonomics on female surgeons.

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People Lifting Patterns—A Reference Dataset for Practitioners

Cited by 4 publications

References 19 publications

A webcam-based machine learning approach for three-dimensional range of motion evaluation

A webcam-based machine learning approach for three-dimensional range of motion evaluation

A new approach to assessing the obstetrician's posture and movement during an instrumental forceps delivery

Overcoming Barriers: Sex Disparity in Surgeon Ergonomics

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