DocumentCode :
3415962
Title :
Vital signs from inside a helmet: A multichannel face-lead study
Author :
von Rosenberg, Wilhelm ; Chanwimalueang, Theerasak ; Looney, David ; Mandic, Danilo P.
Author_Institution :
Electr. & Electron. Eng., Imperial Coll. London, London, UK
fYear :
2015
fDate :
19-24 April 2015
Firstpage :
982
Lastpage :
986
Abstract :
It is essential to measure physiological parameters such as heart rate variability and respiratory rate of drivers to evaluate their performance. The results from this measurement can be used to assess the state of body and mind, for instance concentration and stress. However, current systems only work in controlled environments, or sensors obstruct and interfere with operations of the driver. In this study, a face-lead ECG is placed inside a helmet to enhance comfort and convenience in racing scenarios. Multiple electrodes were attached to facial locations, which exhibit good contact with a helmet, and bipolar configurations were examined between the left and right side of the subject´s face. Standard and data-driven filtering algorithms were employed to improve the extraction of R peaks from the ECG data. The so-extracted R peaks were subsequently used to estimate heart activity and respiration effort, and the results were compared with standard recording protocols. It is shown that ECG recordings obtained from locations on the lower jaw match closely with conventional recording paradigms (limb-lead ECG), highlighting the potential of vital sign monitoring from within a racing helmet.
Keywords :
electrocardiography; feature extraction; medical signal processing; R peaks extraction; face-lead ECG; filtering algorithms; heart rate variability; helmet; limb-lead ECG; multichannel face-lead; respiration; respiratory rate; vital signs; Conferences; Electrocardiography; Electrodes; Empirical mode decomposition; Heart rate; Standards; Electrocardiogram ECG; MEMD; racing helmet; respiratory rate; vital signs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
Type :
conf
DOI :
10.1109/ICASSP.2015.7178116
Filename :
7178116
Link To Document :
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