Detecting Respiratory Events with End-to-End ConvNet

Shuai, Yanping1; Li, Zhangbo2; Wang, Xingjun3; Cheng, Hanrong4

10.1145/3590003.3590098

2023

2nd Asia Conference on Algorithms, Computing and Machine Learning (CACML)

2023 2ND ASIA CONFERENCE ON ALGORITHMS, COMPUTING AND MACHINE LEARNING, CACML 2023

MAR 17-19, 2023

null,Shanghai,PEOPLES R CHINA

1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES

ASSOC COMPUTING MACHINERY

Detecting respiratory events in sleep requires much attention and is labor consuming conventionally. With the development of technology, some kinds of software that can automatically detect the respiratory events was designed to help simplify and improve this process. However, in order to ensure its accuracy of the detection, it is necessary to provide appropriate key parameters before using it. After that the interval adjustment also needs to be done manually, which still takes a lot of time and means high demands on the technicians. In this paper, an end-to-end ConvNet was used to detect the respiratory events which does not need to provide any extra parameters. Its performance was further compared with widely used events detection software, Philips Sleepware G3 with Smonolyzer. The results show that ConvNet has higher accuracy than G3 with Smonolyzer in event detection. Such a ConvNet-based analysis system is sufficiently accurate for event detection according to the AASM classification criteria.

Respiratory event End-to-End ConvNet Smonolyzer

通讯

英语

CPCI-S

Shenzhen Municipal Natural Science Foundation[WDZC20200818121348001]

Computer Science ; Mathematics

Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods ; Mathematics, Applied

WOS:001124190700083

Web of Science

1.Tsinghua Univ, Shenzhen Int Grad Sch, Shenzhen, Guangdong, Peoples R China
2.Dongguan Jianda Informat Technol Co LTD, Shenzhen, Guangdong, Peoples R China
3.Tsinghua Univ, Shenzhen, Guangdong, Peoples R China
4.Southern Univ Sci & Technol, Jinan Univ, Affiliated Hosp 1, Inst Resp Dis,Shenzhen Peoples Hosp,Clin Med Coll, Shenzhen, Guangdong, Peoples R China

Shuai, Yanping,Li, Zhangbo,Wang, Xingjun,et al. Detecting Respiratory Events with End-to-End ConvNet[C]. 1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES:ASSOC COMPUTING MACHINERY,2023.