A CUFFLESS BLOOD PRESSURE MONITORING EPIDERMAL PATCH ENABLED BY DEEP LEARNING

被引：0

作者：

Sharma, Sudeep ^{[1
]}

Pradhan, Gagan Bahadur ^{[1
]}

Jeong, Seonghoon ^{[1
]}

Park, Jae Yeong ^{[1
]}

机构：

[1] Kwangwoon Univ, Dept Elect Engn, Seoul, South Korea

来源：

2024 IEEE 37TH INTERNATIONAL CONFERENCE ON MICRO ELECTRO MECHANICAL SYSTEMS, MEMS | 2024年

关键词：

Epidermal patch; cuffless blood pressure monitoring; ballistocardiogram; electrocardiogram; deep learning;

D O I：

10.1109/MEMS58180.2024.10439507

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this work, a wrist-wearable epidermal patch comprising a piezoresistive ballistocardiogram (BCG) and an electrocardiogram (ECG) sensor for continuous and cuffless blood pressure (BP) monitoring has been developed and demonstrated. Specially designed electrode patterns were printed onto a flexible PET substrate for miniaturization and multimodal sensing. The BCG sensor showed a high sensitivity of -0.093 kPa(-1) at a low-pressure range (0-5 kPa). Simultaneous measurement allowed BP estimations through Convolutional Neural Network - Long Short-Term Memory (CNN-LSTM) based deep learning algorithm with an accuracy of MAE 7.798 for DBP and 3.540 for SBP which eliminated the need for traditional cuff-based systems.

引用

页码：90 / 93

页数：4

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