Traditional Chinese Medicine (TCM)‐Inspired Fully Printed Soft Pressure Sensor Array with Self‐Adaptive Pressurization for Highly Reliable Individualized Long‐Term Pulse Diagnostics
Reliable, non-invasive, continuous monitoring of pulse and blood pressure is essential for the prevention and diagnosis of cardiovascular diseases. However, the pulse wave varies drastically among individuals or even over time in the same individual, presenting significant challenges for the existing pulse sensing systems. Inspired by pulse diagnosis methods in traditional Chinese medicine (TCM), this work reports a self-adaptive pressure sensing platform (PSP) that combines the fully printed flexible pressure sensor array with an adaptive wristband-style pressure system can identify the optimal pulse signal. Besides the detected pulse rate/width/length, "Cun, Guan, Chi" position, and "floating, moderate, sinking" pulse features, the PSP combined with a machine learning-based linear regression model can also accurately predict blood pressure such as systolic, diastolic, and mean arterial pressure values. The developed diagnostic platform is demonstrated for highly reliable long-term monitoring and analysis of pulse and blood pressure across multiple human subjects over time. The design concept and proof-of-the-concept demonstrations also pave the way for the future developments of flexible sensing devices/systems for adaptive individualized monitoring in the complex practical environments for personalized medicine, along with the support for the development of digital TCM.
Authors
- Fei Lv (ORCID: https://orcid.org/0000-0001-9124-9044)
- Xin Wang (ORCID: https://orcid.org/0000-0002-7464-3565)
- Xueli Nan (ORCID: https://orcid.org/0000-0001-6269-6574)
- Huanyu Cheng (ORCID: https://orcid.org/0000-0001-6075-4208)
- Libo Gao (ORCID: https://orcid.org/0000-0002-5964-2337)
- Chenyang Xue
- Zekun Yang (ORCID: https://orcid.org/0009-0001-2462-6513)
- Xikuan Zhang
- Zengxing Zhang
- Guirong Wu
Institutions
- Pennsylvania State University (US)
- North University of China (CN)
- Shanxi University (CN)
- Xiamen University (CN)
- Xiamen University of Technology (CN)
Publication Details
- Journal
- Advanced Materials
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1002/adma.202410312
- Citations
- 74
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 13.65
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Fundamental Research Funds for the Central Universities