A Wireless Pulse Diagnostic Device Utilizing MEMS Pressure Sensor Array for Sleep Apnea Detection

Inspired by traditional Chinese medicine pulse diagnosis, a wireless pulse diagnostic device, based on a Micro Electro Mechanical Systems (MEMS) pressure sensor array, was designed to detect sleep apnea. The arrayed MEMS pressure sensor configuration within a silica gel casing, capturing multidimensional pulse signals at the radial artery positions. Pulse signals were collected from volunteers during normal breathing and breath-holding scenarios to establish a comprehensive sleep apnea recognition database. A feature vector incorporating the pulse contour characteristic K-value, Reflection Index (RI), Power Ratio (PR), and Heart Rate (HR) was created for classification model training using a Support Vector Machine (SVM). Experimental results showed that the accuracy of pulse wave signal feature vector classification is 99.33% and the sensitivity is 98%. Overall, this device offers innovative technical support and significant application potential to advance modernized traditional Chinese diagnostic methods and intelligent medical devices.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3573009
Citations
3
Primary Topic
Obstructive Sleep Apnea Research
Type
article
Field-Weighted Citation Impact
3.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Wireless Pulse Diagnostic Device Utilizing MEMS Pressure Sensor Array for Sleep Apnea Detection

Zhiming Long, Haoyu Tan, Yuanlin Xia, Yubo Huang et al.
3 citations
IEEE Transactions on Instrumentation and Measurement
Obstructive Sleep Apnea Research
3.49
article

A Wireless Pulse Diagnostic Device Utilizing MEMS Pressure Sensor Array for Sleep Apnea Detection

Zhiming Long, Haoyu Tan, Yuanlin Xia, Yubo Huang, Zhuqing Wang, Cao Xia, Xin Cheng, Theresa Liang
article en
3 citations

Abstract

Inspired by traditional Chinese medicine pulse diagnosis, a wireless pulse diagnostic device, based on a Micro Electro Mechanical Systems (MEMS) pressure sensor array, was designed to detect sleep apnea. The arrayed MEMS pressure sensor configuration within a silica gel casing, capturing multidimensional pulse signals at the radial artery positions. Pulse signals were collected from volunteers during normal breathing and breath-holding scenarios to establish a comprehensive sleep apnea recognition database. A feature vector incorporating the pulse contour characteristic K-value, Reflection Index (RI), Power Ratio (PR), and Heart Rate (HR) was created for classification model training using a Support Vector Machine (SVM). Experimental results showed that the accuracy of pulse wave signal feature vector classification is 99.33% and the sensitivity is 98%. Overall, this device offers innovative technical support and significant application potential to advance modernized traditional Chinese diagnostic methods and intelligent medical devices.

IEEE Transactions on Instrumentation and MeasurementVol. 74
Tohoku University (JP), Sichuan University (CN)
National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 8%
Obstructive Sleep Apnea Research
3.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.