TY - GEN
T1 - Survey and evaluation of real-time fall detection approaches
AU - Perry, James T.
AU - Kellog, Scott
AU - Vaidya, Sundar M.
AU - Youn, Jong Hoon
AU - Ali, Hesham
AU - Sharif, Hamid
PY - 2009
Y1 - 2009
N2 - As we grow old, our desire for independence does not diminish; yet our health increasingly needs to be monitored. Injuries such as falling can be a serious problem for the elderly. If a person falls and is not able to get assistance within an hour, casualties arising from that fall can result in fatalities as early as 6 months later [1]. It would seem then that a choice between safety and independence must be made. Fortunately, as health care technology advances, simple devices can be made to detect or even predict falls in the elderly, which could easily save lives without too much intrusion on their independence. Much research has been done on the topic of fall detection and fall prediction. Some have attempted to detect falls using a variety of sensors such as: cameras, accelerometers, gyroscopes, microphones, or a combination of the like. This paper is aimed at reporting which existing methods have been found effective by others, as well as documenting the findings of our own experiments. The combination of which will assist in the progression towards a safe, unobtrusive monitoring system for independent seniors.
AB - As we grow old, our desire for independence does not diminish; yet our health increasingly needs to be monitored. Injuries such as falling can be a serious problem for the elderly. If a person falls and is not able to get assistance within an hour, casualties arising from that fall can result in fatalities as early as 6 months later [1]. It would seem then that a choice between safety and independence must be made. Fortunately, as health care technology advances, simple devices can be made to detect or even predict falls in the elderly, which could easily save lives without too much intrusion on their independence. Much research has been done on the topic of fall detection and fall prediction. Some have attempted to detect falls using a variety of sensors such as: cameras, accelerometers, gyroscopes, microphones, or a combination of the like. This paper is aimed at reporting which existing methods have been found effective by others, as well as documenting the findings of our own experiments. The combination of which will assist in the progression towards a safe, unobtrusive monitoring system for independent seniors.
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U2 - 10.1109/HONET.2009.5423081
DO - 10.1109/HONET.2009.5423081
M3 - Conference contribution
AN - SCOPUS:77951063482
SN - 9781424459957
T3 - 6th International Symposium on High Capacity Optical Networks and Enabling Technologies, HONET '09
SP - 158
EP - 164
BT - 6th International Symposium on High Capacity Optical Networks and Enabling Technologies, HONET '09
T2 - 6th International Symposium on High Capacity Optical Networks and Enabling Technologies, HONET '09
Y2 - 28 December 2009 through 30 December 2009
ER -