Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography
There are many existing wearable devices which are just meant to measure the Systolic Blood Pressure (SBP), and worn on the wrist. However, the current trend of wearable devices is towards the head mounted wearable devices. Pulse wave transit time (PWTT) is used as a non-invasive and cuffless method...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
International Journal of Software Engineering and Technology
2018
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/82342/ http://ijset.mjiit.utm.my |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | There are many existing wearable devices which are just meant to measure the Systolic Blood Pressure (SBP), and worn on the wrist. However, the current trend of wearable devices is towards the head mounted wearable devices. Pulse wave transit time (PWTT) is used as a non-invasive and cuffless method for blood pressure estimation. In this study, ECG signals from the head will be first extracted by using a stimulus based algorithm utilizing ensemble averaging technique to compute for the 〖PWTT〗_head with reference to the Photoplethysmogram (PPG) signals from the earlobe. The chest ECG signals (lead II) and Photoplethysmogram (PPG) signals fingertip will be simultaneously recorded with the head recordings and earlobe PPG to be used as reference signal to measure the 〖PWTT〗_chest from the chest and to verify the performance of the 〖PWTT〗_head measured from the head. The results obtained are analyzed by using regression plots and difference error. The expected outcome is by using 〖PWTT〗_head , SBP can be estimated accurately within the ANSI.AAMI SP10:2002 standards for noninvasive blood pressure accuracy (±5 [mmHg] mean error, 8[mmHg] standard deviations). |
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