TY - GEN
T1 - Modified logistic regression algorithm for accurate determination of heart beats from noisy passive RFID tag data
AU - Vora, Shrenik
AU - Kurzweg, Timothy
PY - 2016/4/18
Y1 - 2016/4/18
N2 - Passive RFID tags provide a promising way to create wireless and battery-free heart rate monitors. However, the reliability of these tags is limited in the presence of common noise sources in their environment. In this paper, we propose an algorithm to improve the beat detection for RFID based heart rate monitors in noisy environments. To achieve this, a logistic regression model is first employed to determine data points that have a very high probability of being actual heart beats. These data points are then used as features to remove the ambiguity in detection of other heart beats. The algorithm is trained using features from a single heart rate measurement and the obtained parameters are used for determining various other heart rates. Using our algorithm, we achieve an F1-score of 0.98 for correct heart beat detection, and completely eliminate an error of over 75% in mean heart rate calculation.
AB - Passive RFID tags provide a promising way to create wireless and battery-free heart rate monitors. However, the reliability of these tags is limited in the presence of common noise sources in their environment. In this paper, we propose an algorithm to improve the beat detection for RFID based heart rate monitors in noisy environments. To achieve this, a logistic regression model is first employed to determine data points that have a very high probability of being actual heart beats. These data points are then used as features to remove the ambiguity in detection of other heart beats. The algorithm is trained using features from a single heart rate measurement and the obtained parameters are used for determining various other heart rates. Using our algorithm, we achieve an F1-score of 0.98 for correct heart beat detection, and completely eliminate an error of over 75% in mean heart rate calculation.
UR - http://www.scopus.com/inward/record.url?scp=84968547867&partnerID=8YFLogxK
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U2 - 10.1109/BHI.2016.7455827
DO - 10.1109/BHI.2016.7455827
M3 - Conference contribution
AN - SCOPUS:84968547867
T3 - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
SP - 29
EP - 32
BT - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
Y2 - 24 February 2016 through 27 February 2016
ER -