Open AccessA Machine Learning Approach for Ecg Analysis for Emotions
Author(s) -
Ms Rubina Jahangir Khan,
AUTHOR_ID,
Anjali Kulkarni,
Mr Jagannath Jadhav,
AUTHOR_ID,
AUTHOR_ID
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.a2592.099320
Subject(s) - sadness , anger , feeling , psychology , cognitive psychology , mental state , perception , computer science , social psychology , neuroscience
Emotions are feelings which one can feel and are hard to be put in a form by a person .However they reflect the mental state of a person. Emotions like joy and sadness can be somehow detected from the facial expressions or through the body language. But these emotions do have an impact upon our system. An individual’s electrocardiogram is a way through which one can know the impact of different parameters such as stress, joy, sadness, anger on the mechanism of our body. The emotions such as anger, sadness have an adverse effect on the cardio system and is seen in the form of abnormal ECG which can be a good pointer to a counselor when finding out the reasons and diagnosis. The decomposition technique along with the Hilbert transform can be used for feature retrieval. The different emotions are detected through the binary classification technique