Performance Analysis of Triaxial Accelerometer for Activity Recognition

被引：0

作者：

Poorani, M. ^{[1
]}

Vaidehi, V. ^{[2
]}

Varalakshmi, P. ^{[3
]}

机构：

[1] Anna Univ, MIT, Dept Elect, Madras, Tamil Nadu, India

[2] VIT, Sch Comp & Engn, Madras, Tamil Nadu, India

[3] Anna Univ, MIT, Dept Comp Technol, Madras, Tamil Nadu, India

来源：

2016 EIGHTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING (ICOAC) | 2017年

关键词：

Human Activity Recognition(HAR); Adaptive Neuro Fuzzy Inference System(ANFIS); Hidden Markov Model(HMM); Fuzzification; Defuzzification;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Human Activity Recognition (HAR) based on accelerometer has become an important mobile application. Activity recognition however depends on X, Y, Z the Cartesian coordinate parameters. There are several approaches for activity recognition. Popular methods of activity recognition using accelerometer reading includes machine learning approach, rule based data mining approach, fuzzy inference approach etc. This paper compares activity recognition based on temporal pattern mining and ANFIS method for wearable sensor accelerometer and mobile accelerometer readings. Though the existing activity recognition using body worn accelerometer gives better accuracy it is found to be costly and consume more power. Hence this paper proposes an ANFIS based activity recognition with the available accelerometer in mobile phone.

引用

页码：170 / 175

页数：6

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