Combination of artificial intelligence and continuous wave radar sensor in diagnosing breathing disorder

Nguyen Thi Phuoc Van*, Liqiong Tang, Syed Faraz Hasan, Subhas Mukhopadhyay, Nguyen Duc Minh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

1 Citation (Scopus)

Abstract

The combination of artificial intelligence (AI) and sensor systems enables many applications. This work shows an innovative solution to test the performance of smart Continuous Wave (CW) Doppler radar sensor system by investigating the mathematical models for receiving signals from different breathing disorder patients. CW radar sensor has many good features such as simple hardware structure, narrow bandwidth frequency, and high sensitivity in detecting the chest movement of humans remotely. Based on the developed berating theoretical models, data sets at different values of signal-to-noise ratio (SNR) are generated. The next step is to apply machine learning technique on this data set to categorize breathing disorder patterns. The results show the high potential application of smart radar sensor in diagnosing disorder sleeping problems.

Original languageEnglish
Title of host publicationIntelligent computing in engineering
Subtitle of host publicationselect proceedings of RICE 2019
EditorsVijender Kumar Solanki, Manh Kha Hoang, Zhonghyu (Joan) Lu, Prasant Kumar Pattnaik
Place of PublicationSingapore
PublisherSpringer, Springer Nature
Pages853-863
Number of pages11
ISBN (Electronic)9789811527807
ISBN (Print)9789811527791
DOIs
Publication statusPublished - 2020
Event4th International Conference on Research in Intelligent and Computing in Engineering, RICE 2019 - Hanoi, Viet Nam
Duration: 8 Aug 20199 Aug 2019

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer, Springer Nature
Volume1125
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference4th International Conference on Research in Intelligent and Computing in Engineering, RICE 2019
Country/TerritoryViet Nam
CityHanoi
Period8/08/199/08/19

Keywords

  • Continuous wave
  • Vital signs detection
  • Machine learning
  • Classification algorithm

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