New progress in wearable blood pressure monitoring enabled by flexible electronics and machine learning
Cardiovascular disease remains the leading cause of death globally, with hypertension posing a significant risk factor for its high incidence. Preventing hypertension is vital for reducing the risk of cardiovascular disease. In clinical practice, traditional cuff sphygmomanometers are commonly used for blood pressure monitoring. However, discomfort during inflation and deflation of the cuff, as well as the limitation of providing intermittent measurements under static conditions, can be challenging.
To address these limitations, wearable cuffless blood pressure monitoring has emerged as a more comfortable and continuous monitoring solution. In a recent review published in the Wearable Electronics journal, researchers from Nanjing University’s Collaborative Innovation Center of Advanced Microstructures examined the advancements in wearable cuffless blood pressure monitoring.
The study highlighted the significance of flexible electronics in enhancing the portability, skin-friendliness, and comfort of health monitoring devices. Wearable cuffless blood pressure monitoring integrates sensors, signal processing, and algorithms to estimate blood pressure accurately in real-time. Flexible electrodes and sensors, including mechanical, optical, and ultrasonic sensors, offer diverse options for monitoring blood pressure effectively.
Moreover, the integration of machine learning techniques, such as artificial neural networks, plays a crucial role in developing more precise blood pressure estimation models. Combining textile triboelectric sensors, flexible strain sensor arrays, graphene electronic tattoos, and machine learning enables personalized monitoring in wearable cuffless blood pressure monitoring, expanding the application of flexible electronics in healthcare.
Despite significant breakthroughs in flexible sensors and systems for wearable cuffless blood pressure monitoring, further advancements are essential to overcome existing limitations before clinical applications can be realized. The research was supported by grants from the National Key Research and Development Program of China, the National Science Fund for Distinguished Young Scholars, and the National Natural Science Foundation of China.
In conclusion, wearable cuffless blood pressure monitoring, enabled by flexible electronics and machine learning, offers a promising solution for continuous and comfortable blood pressure monitoring. With ongoing research and technological advancements, the integration of wearable devices in healthcare holds great potential for improving cardiovascular health outcomes.
