@article{de_pessemier_heart_2018,
	title = {Heart rate monitoring, activity recognition, and recommendation for e-coaching},
	issn = {1380-7501},
	url = {https://link.springer.com/article/10.1007/s11042-018-5640-2},
	doi = {10.1007/s11042-018-5640-2},
	abstract = {Equipped with hardware, such as accelerometer and heart rate sensor,
wearables enable measuring physical activities and heart rate. However,
the accuracy of these heart rate measurements is still unclear and the
coupling with activity recognition is often missing in health apps. This
study evaluates heart rate monitoring with four different device types: a
specialized sports device with chest strap, a fitness tracker, a smart
watch, and a smartphone using photoplethysmography. In a state of rest,
similar measurement results are obtained with the four devices. During
physical activities, the fitness tracker, smart watch, and smartphone
measure sudden variations in heart rate with a delay, due to movements of
the wrist. Moreover, this study showed that physical activities, such as
squats and dumbbell curl, can be recognized with fitness trackers. By
combining heart rate monitoring and activity recognition, personal
suggestions for physical activities are generated using a tag-based
recommender and rule-based filter.},
	urldate = {2018-02-08},
	journal = {Multimed. Tools Appl.},
	author = {De Pessemier, Toon and Martens, Luc},
	month = jan,
	year = {2018},
	note = {Publisher: Springer US},
	pages = {1--18},
}

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