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Holter Monitor: 24-Hour Monitoring

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Related Experiment Video

Updated: Jul 10, 2026

Multi-Modal Home Sleep Monitoring in Older Adults

Multi-Modal Home Sleep Monitoring in Older Adults

Published on: January 26, 2019

Towards automated sleep state estimation using a Holter-oximeter.

C-P Chua¹, J Garvey, S Redmond

¹School of Electrical, Electronic and Mechanical Engineering, University College Dublin, Ireland. echua@ee.ucd.ie

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|November 16, 2007

Summary

This study shows that a Holter-oximeter can estimate sleep states in obstructive sleep apnea patients with 77% accuracy. Pulse arrival time also correlated with sleepiness scores.

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Area of Science:

Cardiology
Sleep Medicine
Biomedical Engineering

Background:

Obstructive sleep apnea (OSA) diagnosis often requires polysomnography.
Non-invasive, accessible monitoring for OSA is needed.
Estimating sleep states can aid in OSA assessment.

Purpose of the Study:

To evaluate the feasibility of using a Holter-oximeter for sleep state estimation in OSA patients.
To assess the correlation between autonomic arousal detection and subjective sleepiness.

Main Methods:

Utilized single-channel ECG and finger photoplethysmogram from overnight Holter-oximeter recordings.
Analyzed parameters: RR interval, photoplethysmogram amplitude/rise time, and pulse arrival time.
Employed a Hidden Markov Model classifier to differentiate Wake, REM, and Sleep states.

Main Results:

Achieved an overall accuracy of 77% and Cohen's kappa of 0.54 for sleep state estimation.
Demonstrated baseline usefulness of Holter-oximeter data for sleep staging.
Identified a strong correlation between autonomic arousals (via pulse arrival time) and Epworth Sleepiness Scale scores.

Conclusions:

Holter-oximeter monitoring shows potential for sleep state estimation in suspected OSA.
Pulse arrival time may serve as a useful indicator for autonomic disturbances related to sleepiness.
Further research can refine this method for improved OSA management.