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Title: i-SAD: An Edge-Intelligent IoT-Based Wearable for Substance Abuse Detection
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.  more » « less
Award ID(s):
1924117
NSF-PAR ID:
10157991
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
2019 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS)
Page Range / eLocation ID:
117 to 122
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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