Development and Evaluation of a Prior-to-Impact Fall Event Detection Algorithm

Details

• Personal Author:
  Liu J ; Lockhart TE
• Description:
  Automatic fall event detection has attracted research attention recently for its potential application in fall alarming system and wearable fall injury prevention system. Nevertheless, existing fall detection research is facing various limitations. The current study aimed to develop and validate a new fall detection algorithm using 2-D information (i.e., trunk angular velocity and trunk angle). Ten healthy elderly were involved in a laboratory study. Sagittal trunk angular kinematics was measured using inertial measurement unit during slip-induced backward falls and a variety of daily activities. The new algorithm was, on average, able to detect backward falls prior to impact, with 100% sensitivity, 95.65% specificity, and 255 ms response time. Therefore, it was concluded that the new fall detection algorithm was able to effectively detect falls during motion for the elderly population. [Description provided by NIOSH]
• Subjects:
  Accidental Falls Accidents Aging Biomechanical Phenomena Musculoskeletal System Occupational Health Safety
• Keywords:
  Age Groups Author Keywords: Fall Detection Biomechanics Fall Intervention Falls Injury Prevention Muscle Function Slips And Falls Wearable Technologies
• ISSN:
  0018-9294
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  OSHA Region 3 ; Virginia ; West Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  61
• Issue:
  7
• NIOSHTIC Number:
  nn:20055426
• Citation:
  IEEE Trans Biomed Eng 2014 Jul; 61(7):2135-2140
• Contact Point Address:
  Jian Liu, Marshall University, Huntington, WV 25755 USA
• Email:
  liuji@marshall.edu
• Federal Fiscal Year:
  2014
• NORA Priority Area:
  Construction ; Services
• Performing Organization:
  Virginia Polytechnic Institute and State University
• Peer Reviewed:
  True
• Start Date:
  20090901
• Source Full Name:
  IEEE Transactions on Biomedical Engineering
• End Date:
  20140831
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:dc781187088cda4e8d192afc14ce3a228b2b7a1a884862a1583e2b6a04663840a43e0d605896a0c3902f39b42e558afe50c1c0495d9a0687e9d318e8af8ab13b
• Download URL:
  https://stacks.cdc.gov/view/cdc/213283/cdc_213283_DS1.pdf
• File Type:
  [PDF - 394.23 KB ]