Paper Info
Title
Wearable Ppg Sensor Based Alertness Scoring System
Abstract
Quantifying mental alertness in today's world is important as it enables the person to adopt lifestyle changes for better work efficiency. Miniaturized sensors in wearable devices have facilitated detection/monitoring of mental alertness. Photoplethysmography (PPG) sensors through Heart Rate Variability (HRV) offer one such opportunity by providing information about one's daily alertness levels without requiring any manual interference from the user. In this paper, a smartwatch based alertness estimation system is proposed. Data collected from PPG sensor of smartwatch is processed and fed to machine learning based model to get a continuous alertness score. Utility functions are designed based on statistical analysis to give a quality score on different stages of alertness such as awake, long sleep and short duration power nap. An intelligent data collection approach is proposed in collaboration with the motion sensor in the smartwatch to reduce battery drainage. Overall, our proposed wearable based system provides a detailed analysis of alertness over a period in a systematic and optimized manner. We were able to achieve an accuracy of 80.1% for sleep/awake classification along with alertness score. This opens up the possibility for quantifying alertness levels using a single PPG sensor for better management of health related activities including sleep.
Year
DOI
Venue
2017
10.1109/EMBC.2017.8037345
2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Data collection,Quality Score,Simulation,Computer science,Wearable computer,Photoplethysmogram,Wearable technology,Power nap,Smartwatch,Alertness
Conference
2017
ISSN
Citations 
PageRank 
1094-687X
0
0.34
References 
Authors
1
4
Name
Order
Citations
PageRank
Jishnu Dey101.01
Tanmoy Bhowmik200.68
Saswata Sahoo300.34
Vijay Narayan Tiwari402.03