Overindulgence of harmful substances such as drugs or alcohol, called substance abuse, can directly affect a person's health and their day-to-day activities. The younger population become more vulnerable to such use of psychoactive substances due to lack of awareness of the long-term hazardous effects these substances can have on their health. Additionally, these individuals tend to develop severe mental disorders as they grow older. With the boom of Internet of Things (IoT), the use of wearable sensors such as smartwatches and smartphones has tremendously increased. These wearables help in monitoring a person's physiological signal and keep them informed of one's health. In this research, we propose an edge-intelligent IoT-based wearable that can assist in substance-abuse detection by monitoring their physiological signals on daily basis. The proposed system helps in monitoring the substance abuse and craving of the individual and help the healthcare provider to start an early intervention as required. The proposed system is validated using a custom-built wearable, i-SAD, which was developed as a dedicated substance abuse wearable using commercially available off-the-shelf components. The proposed wearable design was validated using medical quality wearable and yielded a correlation of 0.89 for accelerometer values and 0.92 for average heart rate values.
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Poster: Towards Edge-Intelligent Wearable for early Drowning Detection
This research aims to develop a wearable monitoring system that can help in monitoring respiratory distress. Drowning-related accidents are 3rd leading cause of unintentional death. Among the victims most of them are children and world statistics state that there are 4000 fatalities per day in children due to drowning. In this research project, we propose a wearable system that can help in monitoring the heart rate, oxygen level, and body temperature variability, along with the accelerometer. Our proposed framework is designed as an anklet that can help detect drowning incidents early
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- Award ID(s):
- 1924117
- PAR ID:
- 10451155
- Date Published:
- Journal Name:
- 16th International Conference on Underwater Networks and Systems
- Page Range / eLocation ID:
- 1-2
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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