# Exploiting Weak Head Movements for Camera-based Respiration Detection

## TL;DR

This paper investigates using subtle head movements, caused by chest respiration, as an alternative non-contact method to estimate respiratory rate from video, especially when chest or skin signals are hard to detect.

## Contribution

It introduces a novel approach exploiting weak head movements induced by respiration for camera-based respiratory detection, validated through experimental study.

## Key findings

- Head movements can be correlated with chest respiration signals.
- The method provides a feasible alternative when traditional rPPG or chest movement detection fails.
- Experimental results confirm the potential of head movement analysis for respiration monitoring.

## Abstract

In recent years, considerable progress has been made in the non-contact based detection of the respiration rate from video sequences. Common techniques either directly assess the movement of the chest due to breathing or are based on analyzing subtle color changes that occur as a result of hemodynamic properties of the skin tissue by means of remote photoplethysmography (rPPG). However, extracting hemodynamic parameters from rPPG is often difficult especially if the skin is not visible to the camera. In contrast, extracting respiratory signals from chest movements turned out to be a robust method. However, the detectability of chest regions cannot be guaranteed in any application scenario, for instance if the camera setting is optimized to provide close-up images of the head. In such a case an alternative method for respiration detection is required. It is reasonable to assume that the mechanical coupling between chest and head induces minor movements of the head which, like in rPPG, can be detected from subtle color changes as well. Although the strength of these movements is expected to be much smaller in scale, sensing these intensity variations could provide a reasonably suited respiration signal for subsequent respiratory rate analysis. In order to investigate this coupling we conducted an experimental study with 12 subjects and applied motion- and rPPG-based methods to estimate the respiratory frequency from both head regions and chest. Our results show that it is possible to derive signals correlated to chest movement from facial regions. The method is a feasible alternative to rPPG-based respiratory rate estimations when rPPG-signals cannot be derived reliably and chest movement detection cannot be applied as well.