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
收藏
页码：1931 / 1935
页数：5
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