Application of Support Vector Machines Arithmetic in Body Posture Detection

DOI

10.2991/icitmi-15.2015.113How to use a DOI?

Keywords

Support Vector Machines STM32F103C8T6 SMV SMA Fall

Abstract

It is very critical to detect elder people's falling down in time for it will be harmed to them even to death if they can't be found early. Body posture detection system is based on STM32F103C8T6 as controller which can detect falling down in time from the two parts of host and slave. Data transferred by Bluetooth between host and slave of this system. The slave detect human movement data by MPU6050, the host analysis and display the current human body posture. A lot of testing data shows that it can get higher accuracy from using Support Vector Machine (SVM) algorithm to posture analysis, integration of acceleration signal, analysis of Signal Magnitude Vector(SMV) and Signal Magnitude Area(SMA) signals, falling and posture judgement from the assistant of intersection angle that between body and ground on the vertical direction.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bo Du
AU  - Lu Yin
AU  - Zhuo Zhang
PY  - 2015/10
DA  - 2015/10
TI  - Application of Support Vector Machines Arithmetic in Body Posture Detection
BT  - Proceedings of the 4th International Conference on Information Technology and Management Innovation
PB  - Atlantis Press
SP  - 680
EP  - 684
SN  - 2352-538X
UR  - https://doi.org/10.2991/icitmi-15.2015.113
DO  - 10.2991/icitmi-15.2015.113
ID  - Du2015/10
ER  -