Research Article
Virtual Cuff: Multisensory Non-Intrusive Blood Pressure Monitoring
@INPROCEEDINGS{10.4108/icst.bodynets.2014.257046, author={Kyeong Hoon Jung and Vinh Tran and Victor Gabrielian and Ani Nahapetian}, title={Virtual Cuff: Multisensory Non-Intrusive Blood Pressure Monitoring}, proceedings={9th International Conference on Body Area Networks}, publisher={ICST}, proceedings_a={BODYNETS}, year={2014}, month={11}, keywords={body area networks blood pressure (bp) ecg pulse oximetery sensor fusion wireless health wearable computing}, doi={10.4108/icst.bodynets.2014.257046} }- Kyeong Hoon Jung
Vinh Tran
Victor Gabrielian
Ani Nahapetian
Year: 2014
Virtual Cuff: Multisensory Non-Intrusive Blood Pressure Monitoring
BODYNETS
ACM
DOI: 10.4108/icst.bodynets.2014.257046
Abstract
A key challenge in wearable health systems is obtaining continuous blood pressure (BP) information, bypassing intermittent and intrusive cuff inflation. In this paper, we explore the fusion of heterogeneous sensors, notably electrocardiogram (ECG) signals and photoplethysmogram (PPG) pulse oximeter readings, along with activity and location information, for blood pressure information classification and continuous monitoring. We present the Virtual Cuff prototype, a wireless body sensor network for continuous cuff-less blood pressure monitoring, which we use to validate the BP classification approach. The experimental results demonstrate that with over 200 test segments and four BP classes over 86.1% accuracy in classification can be achieved with the Virtual Cuff.
