Document Detail

Assessment of waist-worn tri-axial accelerometer based fall-detection algorithms using continuous unsupervised activities.
MedLine Citation:
PMID:  21095967     Owner:  NLM     Status:  MEDLINE    
This study aims to evaluate a variety of existing and novel fall detection algorithms, for a waist mounted accelerometer based system. Algorithms were tested against a comprehensive data-set recorded from 10 young healthy subjects performing 240 falls and 120 activities of daily living and 10 elderly healthy subjects performing 240 scripted and 52.4 hours of continuous unscripted normal activities.
Alan K Bourke; Pepijn van de Ven; Mary Gamble; Raymond O'Connor; Kieran Murphy; Elizabeth Bogan; Eamonn McQuade; Paul Finucane; Gearoid Olaighin; John Nelson
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  2010     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2010  
Date Detail:
Created Date:  2010-11-24     Completed Date:  2011-03-30     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2782-5     Citation Subset:  IM    
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MeSH Terms
Accidental Falls / prevention & control*
Activities of Daily Living
Aged, 80 and over
Biomechanical Phenomena
Biomedical Engineering / methods
Equipment Design
False Positive Reactions
Monitoring, Ambulatory / methods*
Sensitivity and Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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