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| Content Provider | ACM Digital Library |
|---|---|
| Author | Yasufuku, Hiroki Terada, Tsutomu Tsukamoto, Masahiko |
| Abstract | Stress is extremely harmful to one's health. It is important to know which situations or events cause us to feel stressed: if we know the factors behind the stress, we can take corrective action. However, it is hard to perceive stress in everyday life by ourselves. Automatically detecting stress from biological information is one method for dealing with this. Stress is generally detected by using a physiological index pulse, brain activity, and breathing in order to ensure universality and accuracy. This biological information reacts to sudden stressors, not chronic stressors. However, it is difficult to use measuring devices for such data in everyday life because the devices require expertise for operation and are expensive. Our goal in this study is to develop a lifelog system featuring glass-equipped sensors that can be used on a daily basis. We detect stress by examining nasal skin temperature, which is decreased by sudden stressors. In order to investigate the recognition accuracy of the proposed system, we performed experiments at the scenes of feeling stress. Results showed that the system can distinguish factors other than stress from the change in nasal skin temperature with sufficient precision. Moreover, we investigated the optimum locations to attach temperature sensors to ensure that they have both reactivity and comfort. We also implemented an application for analyzing the measured data. The application calculates the time at which a user feels stress by analyzing the measured data and extracts a stressful scene from a video recorded from the point of view of the user. |
| Starting Page | 1 |
| Ending Page | 8 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781450336802 |
| DOI | 10.1145/2875194.2875213 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-02-25 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Life log Context awareness Wearable computing |
| Content Type | Text |
| Resource Type | Article |
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