Mechanical Sensors for Cardiovascular Monitoring: From Battery-Powered to Self-Powered

Abstract

Cardiovascular disease is one of the leading causes of death worldwide. Long-term and real-time monitoring of cardiovascular indicators is required to detect abnormalities and conduct early intervention in time. To this end, the development of flexible wearable/implantable sensors for real-time monitoring of various vital signs has aroused extensive interest among researchers. Among the different kinds of sensors, mechanical sensors can reflect the direct information of pressure fluctuations in the cardiovascular system with the advantages of high sensitivity and suitable flexibility. Herein, we first introduce the recent advances of four kinds of mechanical sensors for cardiovascular system monitoring, based on capacitive, piezoresistive, piezoelectric, and triboelectric principles. Then, the physio-mechanical mechanisms in the cardiovascular system and their monitoring are described, including pulse wave, blood pressure, heart rhythm, endocardial pressure, etc. Finally, we emphasize the importance of real-time physiological monitoring in the treatment of cardiovascular disease and discuss its challenges in clinical translation.

Implantable Triboelectric Nanogenerators for Self‐Powered Cardiovascular Healthcare

“…[69][70][71] Endocardial pressure is commonly monitored by invasive and expensive catheterization, which is not feasible for long-term and continuous data collection and is not optimal for the patient's quality of life. [72][73][74] Highlighted in the research conducted in Liu et al, a TENG based self-powered endocardial pressure sensor (SEPS) was developed to act as a miniature and flexible implantable device to be integrated with a surgical catheter for minimally invasive implantation. [72] To achieve electron flow, a vertical-contact separation-modebased TENG was applied to this implantable device.…”

Implantable Sensors for Post‐Surgical Monitoring of Vascular Complications

“…[21][22][23] The proximity of these types of sensors to the blood vessel allows them to recognize the change in mechanical signal and subsequently convert changes in resistance, capacitance, or induced charge under pressure or strain into an electrical signal output. [24,25]…”

Predicting Heart Disease Using Sensor Networks, the Internet of Things, and Machine Learning: A Study of Physiological Sensor Data and Predictive Models

“…Many wearable sensor-based systems have been recently proposed to enhance the process of predicting heart disease. Tang, C. et al [1] used mechanical sensors that allowed the monitoring of heart diseases. Their objective was to check pulse waves, heart rhythms, and BP.…”