Investigation of auto emotional detection of health professionals based on bio information data analytics
| dc.contributor.author | Kumar, Ashish | en_US |
| dc.contributor.author | Lourens, Melanie Elizabeth | en_US |
| dc.contributor.author | Tiwari, Nitin | en_US |
| dc.contributor.author | Dass, Pranav | en_US |
| dc.contributor.author | Kumar, M.V. Suresh | en_US |
| dc.contributor.author | Abdullah, Khairul Hafezad | en_US |
| dc.date.accessioned | 2022-08-26T12:59:30Z | |
| dc.date.available | 2022-08-26T12:59:30Z | |
| dc.date.issued | 2022-04-28 | |
| dc.date.updated | 2022-08-24T10:02:58Z | |
| dc.description.abstract | Emotion detection is an important aspect in healthcare industries. Effective analysis of emotion detection helps in analyses patient's mental state, psychological state, disease progression rate etcetera. Emotion detection is also required for healthcare professionals (doctors and nurses). Automatic emotion detection is usually done with different technologies such as AI technology, multimodal system, pattern recognition, signal analysis, audio-visual analysis etcetera. The present research analyses the most effective technology for auto-emotion detection among all the technologies. The survey-based statistical analysis has been done in this research with 53 participants from different healthcare sectors of the United Kingdom. The data shows that AI-based multimodal system and Pattern recognition using Electrocardiogram and Electroencephalogram are the most effective technologies for automatic-emotion detection. The analysis also showed that emotion-detection is necessary for healthcare professionals and this analysis helps in enhancing patient's recovery rate by analysing their mental state. | en_US |
| dc.format.extent | 4 p. | en_US |
| dc.identifier.citation | Kumar, A. et al. 2022. Investigation of auto emotional detection of health professionals based on bio information data analytics. 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). Presented at: 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). : 732-735. doi:10.1109/icacite53722.2022.9823706 | en_US |
| dc.identifier.doi | 10.1109/icacite53722.2022.9823706 | |
| dc.identifier.isbn | 9781665437899 | |
| dc.identifier.uri | https://hdl.handle.net/10321/4198 | |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.conference | 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) | en_US |
| dc.subject | AI-Based multimodal system | en_US |
| dc.subject | Pattern recognition | en_US |
| dc.subject | Automatic emotion detection | en_US |
| dc.subject | Electrocardiogram | en_US |
| dc.subject | Electroencephalogram | en_US |
| dc.title | Investigation of auto emotional detection of health professionals based on bio information data analytics | en_US |
| dc.type | Conference | en_US |
| local.sdg | SDG03 |