A Data Analytic End-to-End Framework for the Automated Quantification of Ergonomic Risk Factors Across Multiple Tasks Using a Single Wearable Sensor

Details

• Personal Author:
  Cavuoto LA ; Hajifar S ; Kang J ; Lamooki SR ; Megahed FM ; Sun H
• Description:
  Existing ergonomic risk assessment tools require monitoring of multiple risk factors. To eliminate the direct observation, we investigated the effectiveness of an end-to-end framework that works with the data from a single wearable sensor. The framework is used to identify the performed task as the major contextual risk factor, and then estimate the task duration and number of repetitions as two main indicators of task intensity. For evaluation of the framework, we recruited 37 participants to complete 10 simulated work tasks in a laboratory setting. In testing, we achieved an average accuracy of 92% for task identification, 7.3% error in estimation of task duration, and 7.1% error for counting the number of task repetitions. Moreover, we showed the utility of the framework outputs in two ergonomic tools to estimate the risk of injury. Overall, we indicated the feasibility of using data from wearable sensors to automate the ergonomic risk assessment in workplaces. [Description provided by NIOSH]
• Subjects:
  Ergonomics Occupational Health Safety Safety Management
• Keywords:
  Author Keywords: Change Point Detection End-to-end Learning Ergonomic Risk Assessment Human Performance Modeling Monitoring Systems Risk Assessment Safety Monitoring Sensors Wavelets Wearable Sensors Wearable Technologies

  More +
• ISSN:
  0003-6870
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  New York ; Ohio ; OSHA Region 2 ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  102
• NIOSHTIC Number:
  nn:20067943
• Citation:
  Appl Ergon 2022 Jul; 102:103732
• Contact Point Address:
  Lora A. Cavuoto, Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY, 14260, USA
• Email:
  loracavu@buffalo.edu
• Federal Fiscal Year:
  2022
• Performing Organization:
  State University of New York at Buffalo
• Peer Reviewed:
  True
• Start Date:
  20200930
• Source Full Name:
  Applied Ergonomics
• End Date:
  20220929
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:7ca12072a74a2bf22e67cdac975d11eb5800778217a6cbed9287de00f798756bcb43fa348e4b0f6cbd29935e8d24f2f8eecd90b9a8fc7fb5ec0fb1ea1042277f
• Download URL:
  https://stacks.cdc.gov/view/cdc/230176/cdc_230176_DS1.pdf
• File Type:
  [PDF - 13.11 MB ]