A Machine Learning Approach for Ecg Analysis for Emotions
| Main Authors: | Rubina Jahangir Khan, Raj Kulkarni, Jagannath Jadhav |
|---|---|
| Other Authors: | Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP) |
| Format: | Article Journal |
| Bahasa: | eng |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/5842953 |
Daftar Isi:
- 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