Artificial Intelligence-based Remote Diagnosis of Sleep Apnea using Instantaneous Heart Rates

Prabodh Panindre, Vijay Gandhi, Sunil Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Prolonged Sleep Apnea is a sleeping disorder that can cause arrhythmia, hypertension, and other serious health conditions leading to cardiovascular diseases and fatal strokes. Most widely used current clinical techniques for sleep apnea diagnosis are expensive, time-consuming, and cannot be performed remotely. Wearable watch-style health trackers continuously track sleep behavior, physiological data, and physical activity that can enable real-time remote diagnosis of sleep apnea. Recently, the application of Artificial Intelligence (AI) techniques within the field of medicine and remote diagnosis is gaining popularity. In this paper, several Artificial Intelligence (AI) models have been trained and tested to classify sleep apnea condition in real-time using sequential data of Instantaneous Heart Rates (IHR). Using the confusion matrix, the accuracy, precision, recall, specificity, Fl Score, sensitivity, and area under the receiver operating characteristic curve of each model are computed and compared. The Bi-directional Long Short-Term Memory (LSTM) was found to be the best AI technique for classifying sleep apnea. The approach depicted in this study for diagnosing sleep apnea can allow the telemedicine, telehealth, and mHealth applications to detect several health risk factors in real-time using data streaming from the health trackers.

Original languageEnglish (US)
Title of host publicationProceedings of the Confluence 2021
Subtitle of host publication11th International Conference on Cloud Computing, Data Science and Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages169-174
Number of pages6
ISBN (Electronic)9780738131603
DOIs
StatePublished - Jan 28 2021
Event11th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2021 - Virtual, Nodia, India
Duration: Jan 28 2021Jan 29 2021

Publication series

NameProceedings of the Confluence 2021: 11th International Conference on Cloud Computing, Data Science and Engineering

Conference

Conference11th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2021
CountryIndia
CityVirtual, Nodia
Period1/28/211/29/21

Keywords

  • Artificial Neural Network
  • Deep Learning
  • Health Trackers
  • Machine Learning
  • Sleep Apnea

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Software
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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