PhD forum abstract: Non-intrusive blood glucose monitor by multi-task deep learning

Proceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017

Volumn , Issue , 2017, Pages 249-250

  Gu, Weixi ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DEEP LEARNING; GLUCOSE; HEALTH RISKS; INSULIN; SENSOR NETWORKS; SMARTPHONES;

BLOOD GLUCOSE; BLOOD GLUCOSE CONCENTRATION; BLOOD GLUCOSE MONITORING; BLOOD-GLUCOSE MONITORS; OCULAR FUNDUS; PANCREATIC FUNCTIONS; PERSONAL HEALTH; PHYSICAL ACTIVITY;

BLOOD;

EID: 85019034197     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/3055031.3055049     Document Type: Conference Paper

References (7)

1. Carlos Eduardo Ferrante do Amaral and Benhard Wolf. 2008. Current development in non-invasive glucose monitoring. Medical engineering & physics 30, 5 (2008), 541-549.
2. DCCT Research Group and others. 1991. Epidemiology of severe hypoglycemia in the Diabetes Control and Complications Trial. The American Journal of Medicine 90, 4 (1991), 450-459.
3. Weixi Gu, Ming Jin, Zimu Zhou, Costas J Spanos, and Lin Zhang. 2016. MetroEye: Smart Tracking Your Metro Trips Underground. In Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. ACM, 84-93.
4. Weixi Gu, Longfei Shangguan, Zheng Yang, and Yunhao Liu. 2016. Sleep hunter: Towards fine grained sleep stage tracking with smartphones. IEEE Transactions on Mobile Computing 15, 6 (2016), 1514-1527.
5. Weixi Gu, Zheng Yang, Longfei Shangguan, Wei Sun, Kun Jin, and Yunhao Liu. 2014. Intelligent sleep stage mining service with smartphones. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 649-660.
6. Ronald Klein. 1995. Hyperglycemia and microvascular and macrovascular disease in diabetes. Diabetes Care 18, 2 (1995), 258-268.
7. Jennifer R Kwapisz, Gary M Weiss, and Samuel A Moore. 2011. Activity recognition using cell phone accelerometers. ACM SigKDD Explorations Newsleter 12, 2 (2011), 74-82.