Integrating mobile and cloud for PPG signal selection to monitor heart rate during intensive physical exercise

Proceedings - International Conference on Mobile Software Engineering and Systems, MOBILESoft 2016

Volumn , Issue , 2016, Pages 36-37

  Jindal, Vasu ^a  

^a UNIVERSITY OF TEXAS AT DALLAS   (United States)

Author keywords

Accelerometer; Deep belief networks; Deep learning; Heart rate monitoring; Internet of Things (IoT); PPG signals

Indexed keywords

ACCELEROMETERS; E-LEARNING; INTERNET; INTERNET OF THINGS; PATIENT MONITORING; PHOTOPLETHYSMOGRAPHY; SMARTPHONES; SOFTWARE ENGINEERING; SPORTS; WEARABLE TECHNOLOGY;

10-FOLD CROSS-VALIDATION; ACCELEROMETER SENSOR; DEEP BELIEF NETWORKS; DEEP LEARNING; HEART-RATE MONITORING; INTERNET OF THING (IOT); INTERNET OF THINGS (IOT); MOBILE APPLICATIONS;

HEART;

EID: 84983550738     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2897073.2897132     Document Type: Conference Paper

References (4)

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4. Z.Zhang, Z.Pi, B. iu, "TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise, "IEEE Trans. on Biomed. Engineering, vol. 62, pp. 522-531, 2015.