Novel methods to detect impacts within whole-body vibration time series data

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.

Practitioner summary: Common metrics of exposure to whole-body vibration do not quantify the number or magnitudes of impacts within time series accelerometer data. Three candidate impact detection methods are presented and evaluated using real-world data collected during use of agricultural machines. Results highlight the importance of considering posture when evaluating vibration exposure.

Keywords:

• Whole-body vibration
• mechanical shocks
• impact detection
• electromyography
• posture

Acknowledgements

We would like to dedicate this work to the memory of Donald E. Wasserman, a friend, a colleague, and from 1971 to 1984, the first Chief of the NIOSH Occupational Vibration Group where he was responsible for both developing and implementing the United States’ first program in occupational vibration. Early in his role there, he was concerned that ‘the world isn’t sinusoidal.’ He was an early explorer of the effects on people of more complex signals that included combined waveforms and repetitive mechanical shocks. Our work is a direct outgrowth of his early ideas (Cohen et al. 1977). Thank you Don.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was supported by the US Centere for Disease Control and Prevention (CDC)/ National Institute for Occupational Safety and Health (NIOSH) through a cooperative agreement with the Great Plains Center for Agricultural Health [CDC/NIOSH grant no: U54 OH007548]. The Heartland Center for Occupational Health and Safety [CDC/NIOSH grant no: T42 OH008491] provided additional support.