# Radar-based inspiratory-to-expiratory time ratio estimation: a validation study

**Authors:** Thanh Trúc Trần, Marie Oesten, Stefan G. Griesshammer, Anke Malessa, Kilin Shi, Maria Heckel, Bjoern M. Eskofier, Alexander Koelpin, Christoph Ostgathe, Tobias Steigleder

PMC · DOI: 10.1038/s41598-026-42517-9 · Scientific Reports · 2026-03-04

## TL;DR

This study validates radar as a non-contact method to measure respiratory metrics like inspiratory-to-expiratory time ratio, showing high accuracy compared to traditional sensors.

## Contribution

The novel contribution is demonstrating radar's viability for non-contact respiratory monitoring with strong agreement against impedance pneumography.

## Key findings

- Radar-derived metrics showed high correlation with impedance pneumography for TI, TE, RR, and I:E ratio.
- Over 77-97% of radar measurements fell within predefined bounds for each respiratory parameter.
- Findings suggest radar is suitable for continuous monitoring in clinical settings requiring minimal patient burden.

## Abstract

Respiration is a key indicator of health and wellbeing, with metrics such as respiratory rate (RR), inspiratory time (TI), expiratory time (TE), and the inspiratory-to-expiratory time (I:E) ratio offering insights into conditions ranging from acute life-threatening and chronic diseases to symptom management. While traditional methods already measure these parameters with high accuracy, they still require contact-based sensors, limiting their practicality for continuous monitoring. This study evaluates radar as a non-contact alternative by validating multiple radar-derived respiratory metrics against impedance pneumography measurements in 30 healthy volunteers at rest. Synchronous recordings from both modalities were analysed to assess agreement across methods using descriptive statistics, scatter plots, modified Bland-Altman plots, and equivalence testing (TI: ±0.3 s, TE: ±0.3 s, RR: ±2 brpm, I:E ratio: ±0.2). Equivalence testing indicated high correlation (p ≤ 0.001***) across all metrics, with 81.8% (TI), 77.6% (TE), 97.2% (RR), and 85.7% (I:E ratio) of values within predefined bounds. These findings highlight radar’s potential for continuous respiratory monitoring, particularly in medical fields where minimizing patient burden is essential as in palliative, post anaesthesia, and intensive care settings.

The online version contains supplementary material available at 10.1038/s41598-026-42517-9.

## Full-text entities

- **Diseases:** respiratory depression (MESH:D012131), respiratory distress (MESH:D012128), metabolic imbalances (MESH:D008659), skin irritation (MESH:D012871), respiratory complications (MESH:D012140), Cancer (MESH:D009369), heart failure (MESH:D006333), TI (MESH:D000377), sleep apnoea (MESH:D012891), abnormal (MESH:D000014), infections (MESH:D007239), cardiovascular illnesses (MESH:D002318)
- **Chemicals:** oxygen (MESH:D010100), carbon dioxide (MESH:D002245), ICG (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12963625/full.md

## References

5 references — full list in the complete paper: https://tomesphere.com/paper/PMC12963625/full.md

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Source: https://tomesphere.com/paper/PMC12963625