ACADSTAFF UGM
| Title | : | Physiological Pattern of Emotion in Elderly Based on Pulse Rate Variability Features: A preliminary study of e-Health monitoring system |
| Author | : |
Adhi Dharma Wibawa (1) Lutfi Hakim (2) Ari Widyanti (3) Khoirul Muslim (4) Dr. Eng. Ir. Titis Wijayanto, S.T., M.Des., IPM., ASEAN Eng. (5) Ir. Fitri Trapsilawati, S.T., Ph.D., IPM., ASEAN Eng. (6) Ir. Hilya Mudrika Arini, S.T., M.Sc., M.Phil., Ph.D., IPM., ASEAN Eng. (7) |
| Date | : | 31 2019 |
| Keyword | : | e-Health monitoring,Pulse rate sensor,human emotion stimulation,physiological pattern of emotion,negative emotion e-Health monitoring,Pulse rate sensor,human emotion stimulation,physiological pattern of emotion,negative emotion |
| Abstract | : | e-Health monitoring systems have been developed widely in many forms of applications. Monitoring physical condition of patients from a distance is the basic definition of e-health. However, there have been only few studies that explored the implementation of e-health in monitoring human emotions. It's been widely known that emotion is one of the fundamental aspects that affecting human health conditions, especially the negative emotions such as sad and angry. In a health monitoring system, the influence of emotion to the human health can be monitored by using physiological signals such as heartbeat data, Oxygen in blood level, Galvanic skin level, pulse rate or blood pressure. Due to that reason, this study aimed to analyze physiological patterns of emotion in elderly based on pulse rate variability features by using pulse sensor as a form of e-health monitoring system in a lab scale. In this study, 25 elderly participants were involved and were stimulated by a video that conveys happiness, sadness, and anger content. The experiment was done in three phases: the baseline phase, video stimulation phase, and recovery phase. Pulse sensor was applied to capture the physiological signal of 25 participants during those 3 phases. Statistical feature extraction was used to calculated mean, maximum, minimum and standard deviation values from pulse rate signals. Furthermore, the paired t-test was used to analyze mean value between baseline and video stimulation phase. The results showed that sad emotion increased pulse rate significantly compared to happy and angry emotions. It was reported that 9 participants reached the pulse rate level more than 100 bpm when experiencing sadness. It implies that sad emotion has a higher potential for Sinus Tachycardia to happen to elderly people. |
| Group of Knowledge | : | |
| Level | : | Internasional |
| Status | : |
Published
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