Open AccessOptimised band‐pass filter to ensure accurate ECG‐based identification of exercising human subjects
Author(s) -
Nobunaga T.,
Tanaka H.,
Tanahashi I.,
Watanabe T.,
Hattori Y.
Publication year - 2017
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2016.4149
Subject(s) - waveform , identification (biology) , distortion (music) , passband , identification scheme , computer science , filter (signal processing) , block (permutation group theory) , band pass filter , low pass filter , electronic engineering , engineering , mathematics , bandwidth (computing) , telecommunications , computer vision , data mining , measure (data warehouse) , amplifier , radar , botany , geometry , biology
Waveform distortions generated by exercise cause erroneous predictions in human identification based on the electrocardiogram (ECG). An approach for the ECG‐based identification to achieve accurate predictions while exercising is proposed. In the proposed scheme, passband of a band‐pass filter is optimised to compensate for the distortion. As a result, the proposed scheme archives 100% identification accuracy is revealed when the subject is resting and 99.7% during exercise. The investigation is an important building block in the development of robust ECG‐based identification systems that are consistently accurate despite significant ECG waveform variation due to exercise.