Journal article
Novel Methods to Detect Impacts within Whole-Body Vibration Time Series Data
Ergonomics, Vol.65(12), pp.1609-1620
02/17/2022
DOI: 10.1080/00140139.2022.2041735
PMID: 35148664
Abstract
We present three candidate mathematical models for detecting impacts within time series accelerometer data in the context of whole-body vibration (WBV). In addition to WBV, data included recordings of erector spinae muscle activity and trunk posture collected during use of agricultural machines in a previous study. For each model, we evaluated associations between several mechanical and biomechanical variables at the time of predicted impact onset and the odds of subsequently observing a bilateral response of the erector spinae muscles. For all models, trunk posture at the time of impact onset was strongly associated with an observed bilateral muscle response; these associations were not observed when impacts were randomly assigned. Results provide a framework for describing the number and magnitudes of impacts that may help overcome ambiguities in current exposure metrics, such as the Vibration Dose Value, and highlight the importance of considering posture in the evaluation of occupational WBV exposures.
Details
- Title: Subtitle
- Novel Methods to Detect Impacts within Whole-Body Vibration Time Series Data
- Creators
- Shamus K Roeder - Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USADavid G Wilder - Department of Occupational and Environmental Health, University of Iowa, Iowa City, Iowa, USANathan B Fethke - Department of Occupational and Environmental Health, University of Iowa, Iowa City, Iowa, USA
- Resource Type
- Journal article
- Publication Details
- Ergonomics, Vol.65(12), pp.1609-1620
- DOI
- 10.1080/00140139.2022.2041735
- PMID
- 35148664
- NLM abbreviation
- Ergonomics
- eISSN
- 1366-5847
- Grant note
- DOI: 10.13039/100000125, name: National Institute for Occupational Safety and Health, award: U54OH007548, T42OH008491
- Language
- English
- Electronic publication date
- 02/17/2022
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Occupational and Environmental Health; Industrial and Systems Engineering; Injury Prevention Research Center
- Record Identifier
- 9984215126102771
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