Automatic individual calibration in fall detection – an integrative ambulatory measurement framework

Jian Liu and Thurmon E. Lockhart

Computer Methods in Biomechanics and Biomedical Engineering, 2013, vol. 16, issue 5, 504-510

Abstract: The objective of the current study was to demonstrate the utility of a new integrative ambulatory measurement (IAM) framework by developing and evaluating an individual calibration function in fall detection application. Ten healthy elderly persons were involved in a laboratory study and tested in a protocol comprising various types of activities of daily living and slip-induced backward falls. Inertial measurement units attached to the trunk and thigh segments were used to measure trunk angular kinematics and thigh accelerations. The effect of individual calibration was evaluated with previously developed fall detection algorithm. The results indicated that with individual calibration, the fall detection performance achieved approximately the same level of sensitivity (100% vs. 100%) and specificity (95.25% vs. 95.65%); however, response time was significantly lower than without (249 ms vs. 255 ms). It was concluded that the automatic individual calibration using the IAM framework improves the performance of fall detection, which has a greater implication in preventing/minimising injuries associated with fall accidents.

Date: 2013
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2011.627329 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:16:y:2013:i:5:p:504-510

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255842.2011.627329

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().