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Published on: April 19, 2019
Emerging sensing and modeling technologies for wearable and cuffless blood pressure monitoring
Lei Zhao1,2,3, Cunman Liang1,3, Yan Huang1
1Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China.
Insights
Wearable, cuffless blood pressure (BP) monitoring is crucial for cardiovascular disease (CVD) management. This review explores flexible sensors and algorithms for accurate, continuous BP tracking, advancing mobile healthcare.
Area of Science:
- Biomedical Engineering
- Cardiovascular Research
- Wearable Technology
Background:
- Cardiovascular diseases (CVDs) are a major global health concern, necessitating frequent blood pressure (BP) monitoring for early detection and management.
- Continuous, real-time BP monitoring outside clinical settings, particularly during daily activities and sleep, is highly desirable for effective CVD care.
- Wearable and cuffless BP monitoring technologies are emerging as key components of the mobile healthcare initiative.
Purpose of the Study:
- To review the enabling technologies for wearable and cuffless BP monitoring platforms.
- To cover emerging flexible sensor designs and BP extraction algorithms for continuous BP monitoring.
- To highlight interdisciplinary research opportunities for next-generation BP measurement devices.
Main Methods:
- Classification of sensing devices into electrical, optical, and mechanical sensors based on signal type.
- Review of state-of-the-art materials, fabrication methods, and performance of various sensor types.
- Introduction and comparison of contemporary algorithmic BP estimation methods, including pulse transit time-based models and machine learning approaches.
Main Results:
- Flexible sensors are being developed using diverse materials and fabrication techniques for wearable BP monitoring.
- Both analytical and machine learning algorithms show promise for beat-to-beat BP estimation and continuous BP waveform extraction.
- Comparison of mainstream methods based on input modalities, features, algorithms, and performance metrics.
Conclusions:
- Advancements in flexible sensor technology and signal processing algorithms are paving the way for cuffless BP monitoring.
- Integration of innovations in sensor design and signal processing is crucial for developing accurate and reliable wearable BP devices.
- Future research should focus on interdisciplinary collaboration to enhance the wearability, reliability, and accuracy of next-generation cuffless BP measurement systems.
Abstract:
Cardiovascular diseases (CVDs) are a leading cause of death worldwide. For early diagnosis, intervention and management of CVDs, it is highly desirable to frequently monitor blood pressure (BP), a vital sign closely related to CVDs, during people's daily life, including sleep time. Towards this end, wearable and cuffless BP extraction methods have been extensively researched in recent years as part of the mobile healthcare initiative. This review focuses on the enabling technologies for wearable and cuffless BP monitoring platforms, covering both the emerging flexible sensor designs and BP extraction algorithms. Based on the signal type, the sensing devices are classified into electrical, optical, and mechanical sensors, and the state-of-the-art material choices, fabrication methods, and performances of each type of sensor are briefly reviewed. In the model part of the review, contemporary algorithmic BP estimation methods for beat-to-beat BP measurements and continuous BP waveform extraction are introduced. Mainstream approaches, such as pulse transit time-based analytical models and machine learning methods, are compared in terms of their input modalities, features, implementation algorithms, and performances. The review sheds light on the interdisciplinary research opportunities to combine the latest innovations in the sensor and signal processing research fields to achieve a new generation of cuffless BP measurement devices with improved wearability, reliability, and accuracy.
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