%0 Journal Article
	%A Ahyoung Jeon and  Geunchul Park and  Jung-Hoon Ro and  Gye-rok Geon
	%D 2012
	%J International Journal of Biomedical and Biological Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 61, 2012
	%T Development of the Algorithm for Detecting Falls during Daily Activity using 2 Tri-Axial Accelerometers
	%U https://publications.waset.org/pdf/2993
	%V 61
	%X Falls are the primary cause of accidents in people over
the age of 65, and frequently lead to serious injuries. Since the early
detection of falls is an important step to alert and protect the aging
population, a variety of research on detecting falls was carried out
including the use of accelerators, gyroscopes and tilt sensors. In
exiting studies, falls were detected using an accelerometer with
errors. In this study, the proposed method for detecting falls was to
use two accelerometers to reject wrong falls detection. As falls are
accompanied by the acceleration of gravity and rotational motion, the
falls in this study were detected by using the z-axial acceleration
differences between two sites. The falls were detected by calculating
the difference between the analyses of accelerometers placed on two
different positions on the chest of the subject. The parameters of the
maximum difference of accelerations (diff_Z) and the integration of
accelerations in a defined region (Sum_diff_Z) were used to form the
fall detection algorithm. The falls and the activities of daily living
(ADL) could be distinguished by using the proposed parameters
without errors in spite of the impact and the change in the positions
of the accelerometers. By comparing each of the axial accelerations,
the directions of falls and the condition of the subject afterwards
could be determined.In this study, by using two accelerometers
without errors attached to two sites to detect falls, the usefulness of
the proposed fall detection algorithm parameters, diff_Z and
Sum_diff_Z, were confirmed.
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