Details:

Alternative Title:
Proc Hum Factors Ergon Soc Annu Meet
Personal Author:
Lim, Sol ; D’Souza, Clive ;
Lim, Sol ; D’Souza, Clive ; Less -
Description:
This study explored the use of body posture kinematics derived from wearable inertial sensors to estimate force exertion levels in a two-handed isometric pushing and pulling task. A prediction model was developed grounded on the hypothesis that body postures predictably change depending on the magnitude of the exerted force. Five body postural angles, viz., torso flexion, pelvis flexion, lumbar flexion, hip flexion, and upper arm inclination, collected from 15 male participants performing simulated isometric pushing and pulling tasks in the laboratory were used as predictor variables in a statistical model to estimate handle height (shoulder vs. hip) and force intensity level (low vs. high). Individual anthropometric and strength measurements were also included as predictors. A Random Forest algorithm implemented in a two-stage hierarchy correctly classified 77.2% of the handle height and force intensity levels. Results represent early work in coupling unobtrusive, wearable instrumentation with statistical learning techniques to model occupational activities and exposures to biomechanical risk factors |.
Subject:
[+]
Article

Source:
Proc Hum Factors Ergon Soc Annu Meet. 61(1):1031-1035 ;
Pubmed ID:
29276370
Pubmed Central ID:
PMC5740231
Document Type:
Journal Article ;
Funding:
T42 OH008455/OH/NIOSH CDC HHS/United States ;
Collection(s):
CDC Public Access
Main Document Checksum:
[+]
urn:sha256:b4fc433aae84bb1489d2006a35e2bd525e88917a8ac46dce21a64a8782987b46
File Type:

Supporting Files

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