Abstract:
This study investigates ECG features, focusing on T-wave amplitude, from a wearable ECG device as a potential method for fitness monitoring in exercise rehabilitation. An...Show MoreMetadata
Abstract:
This study investigates ECG features, focusing on T-wave amplitude, from a wearable ECG device as a potential method for fitness monitoring in exercise rehabilitation. An automatic T-peak detection algorithm is presented that uses local baseline detection to overcome baseline drift without the need for preprocessing, and offers adequate performance on data recorded in noisy environments. The algorithm is applied to 24 hour data recordings from two subject groups with different physical activity histories. Results indicate that, while mean heart rate (HR) differs most significantly between the groups, T-amplitude features could be useful depending on the disparities in fitness level, and require further investigation on an individual basis.
Published in: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Date of Conference: 26-30 August 2014
Date Added to IEEE Xplore: 06 November 2014
Electronic ISBN:978-1-4244-7929-0
ISSN Information:
PubMed ID: 25570911