TY  - JOUR
T1  - Fall Detection with Support Vector Machine for Elderly Care using
Pressure Sensor Grid
AU - Lim, Way-Soong AU - Kumar, Viknesh AU - Yeo, Boon-Chin 
JO  - Journal of Engineering and Applied Sciences
VL  - 15
IS  - 2
SP  - 636
EP  - 642
PY  - 2020
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2020.636.642
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2020.636.642
KW  - Fall detection
KW  -pressure sensor
KW  -support vector machine
KW  -elderly care
KW  -postures
KW  -objective
AB  - Generally, falling is prevalent in elderly of age 65 and above due to age-related biological changes.
Falls can be life-threatening if noticed late. Hence, a fall detection and surveillance device was developed to
monitor elderly living alone. The primary objective is to build a pressure sensitive mat capable of detecting fall
through image processing. The subjects tested resembled the stature of elderly. The accuracy of the system in
detecting fall is 93% while the accuracies for the other postures such as standing and sitting yield 93.5 and
81.5%, respectively.
ER  -