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Published on: December 22, 2016
Apnea-hypopnea index estimation using overnight chest-wall accelerometry
Fons Schipper1,2, Pedro Fonseca1,2, Angela Grassi1
1Philips Sleep and Respiratory Care, Eindhoven, Netherlands.
Frontiers in Sleep
|August 4, 2026
Summary
Chest-worn accelerometers can reliably estimate the apnea-hypopnea index (AHI) for diagnosing obstructive sleep apnea (OSA). This method also aids in monitoring treatment effectiveness, such as with positional therapy.
Area of Science:
- Biomedical Engineering
- Sleep Medicine
- Wearable Technology
Background:
- Obstructive sleep apnea (OSA) diagnosis relies on polysomnography (PSG), which is resource-intensive.
- There is a need for accessible methods for OSA diagnosis and long-term treatment monitoring.
Purpose of the Study:
- To develop and validate a method for estimating the apnea-hypopnea index (AHI) using chest-worn accelerometry.
- To assess the potential of this method for OSA diagnosis and monitoring positional therapy effectiveness.
Main Methods:
- A neural network was adapted to estimate AHI from chest-wall accelerometry data, incorporating heart rate and respiratory effort.
- The model was trained and validated on data from 413 participants undergoing overnight PSG.
- Performance was evaluated by comparing accelerometry-derived AHI with PSG-derived AHI across different sleep positions.
Main Results:
- Sleep staging using accelerometry achieved substantial agreement with PSG (Cohen's kappa = 0.67).
- AHI estimation demonstrated high reliability, with an intraclass correlation coefficient of 0.90 compared to PSG.
- The method showed consistent performance in both supine and non-supine positions, with strong diagnostic likelihood ratios.
Conclusions:
- Chest-wall accelerometry provides a reliable method for estimating AHI.
- This approach shows promise for both diagnosing OSA and assessing residual AHI during treatments like positional therapy.
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