TY - JOUR
T1 - Unobtrusive monitoring and identification of fall accidents
AU - Van De Ven, Pepijn
AU - O'Brien, Hugh
AU - Nelson, John
AU - Clifford, Amanda
N1 - Publisher Copyright:
© 2015 IPEM.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - Falls are a societal and economic problem of great concern with large parts of the population, in particular older citizens, at significant risk and the result of a fall often being grave. It has long been established that it is of importance to provide help to a faller soon after the event to prevent complications and this can be achieved with a fall monitor. Yet, the practical use of currently available fall monitoring solutions is limited due to accuracy, usability, cost, and, not in the least, the stigmatising effect of many solutions. This paper proposes a fall sensor concept that can be embedded in the user's footwear and discusses algorithms, software and hardware developed. Sensor performance is illustrated using results of a series of functional tests. These show that the developed sensor can be used for the accurate measurement of various mobility and gait parameters and that falls are detected accurately.
AB - Falls are a societal and economic problem of great concern with large parts of the population, in particular older citizens, at significant risk and the result of a fall often being grave. It has long been established that it is of importance to provide help to a faller soon after the event to prevent complications and this can be achieved with a fall monitor. Yet, the practical use of currently available fall monitoring solutions is limited due to accuracy, usability, cost, and, not in the least, the stigmatising effect of many solutions. This paper proposes a fall sensor concept that can be embedded in the user's footwear and discusses algorithms, software and hardware developed. Sensor performance is illustrated using results of a series of functional tests. These show that the developed sensor can be used for the accurate measurement of various mobility and gait parameters and that falls are detected accurately.
KW - Accelerometry
KW - Ambient assisted living
KW - Fall sensing
KW - Falls prevention
KW - Mobile health
UR - http://www.scopus.com/inward/record.url?scp=84928215461&partnerID=8YFLogxK
U2 - 10.1016/j.medengphy.2015.02.009
DO - 10.1016/j.medengphy.2015.02.009
M3 - Article
C2 - 25769224
AN - SCOPUS:84928215461
SN - 1350-4533
VL - 37
SP - 499
EP - 504
JO - Medical Engineering and Physics
JF - Medical Engineering and Physics
IS - 5
ER -