Physical Activity Classification in A-ECG Signals Using Neuro-fuzzy Classifiers

被引：0

作者：

Kher, Rahul ^{[1
]}

Pawar, Tanmay ^{[2
]}

Thakar, Vishvjit ^{[3
]}

Shah, Hitesh ^{[1
]}

机构：

[1] GH Patel Coll Engn & Tech, Vv Nagar, India

[2] BVM Engn Coll, Vv Nagar, India

[3] AD Patel Inst Tech, New Vv Nagar, India

来源：

2015 2ND INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM) | 2015年

关键词：

Ambulatory ECG (A-ECG); Physical activities (PA); Gabor transform; Neuro-fuzzy classifier (NFC); Wearable ECG recorder; LESIONS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Wearable ambulatory ECG (A-ECG) signals obtained using wearable ECG recorders inherently contain the motion artifacts due to various physicals activities of the subject. Classification of four such physical activities (PAs) left arm up-down, right arm up-down, waist twisting and walking of five healthy subjects has been performed using neuro-fuzzy classifier (NFC). The Gabor energy feature vectors have been used to train the NFC. The overall PA classification accuracy achieved by the NFC classifier is almost 95% for single-fold as well as ten-fold experiments.

引用

页码：1931 / 1935

页数：5

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