1. Monitoring breathing rate by fusing the physiological impact of respiration on video-photoplethysmogram with head movements
- Author
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Davide Silvestri, Eduardo Gil, Pablo Laguna, Jesus Lazaro, Luca Mainardi, Luca Iozza, and Luca Cerina
- Subjects
Respiratory rate ,Contactless system ,Physiology ,Computer science ,0206 medical engineering ,Biomedical Engineering ,Biophysics ,Breathing rate ,02 engineering and technology ,Signal ,03 medical and health sciences ,0302 clinical medicine ,Respiratory Rate ,Physiology (medical) ,Photoplethysmogram ,Respiration ,Camera ,PPG ,Range (statistics) ,Humans ,Computer vision ,Respiratory system ,Photoplethysmography ,Monitoring, Physiologic ,Signal processing ,business.industry ,Signal Processing, Computer-Assisted ,020601 biomedical engineering ,Healthy Volunteers ,Head Movements ,Head movements ,Artificial intelligence ,business ,030217 neurology & neurosurgery - Abstract
Objective: The simple observation of breathing rate (BR) remains the first and often the most sensitive marker of acute respiratory dysfunction. In fact, there are evidences that drastic changes in BR are a predictive indicator of adverse events (i.e. cardiac arrest). The aim of this study is to develop a camera-based technology that may provide near-continuously estimation of BR considering the effect of respiration on videoPPG (vPPG). Approach: The technology has been tested in two different experimental settings, including controlled BR and more challenging scenarios with spontaneous breathing pattern. Video data were processed offline to derive the vPPG signal. The method derives respiration from beat-to-beat PPG rate and morphology changes in amplitude and width driven by the physiological relationships between vPPG and respiration. Moreover, respiratory-induced head movements were used as additional source of information for the vPPG system. A combination of these methods has been exploited to estimate the respiratory rate every 10 second. Main Results: According to the results, respiratory frequencies in the central range (0.2-0.4 Hz) may be estimated using vPPG system with low relative error, eR < 2 % and interquartile range of order IQR < 5 %. However, the vPPG system showed a drop in performance at respiratory range boundaries, around 0.1 Hz and 0.5 Hz. Significance: This camera-based technology can be used as ubiquitous BR monitoring system. However, vPPG-based systems should consider the effect of the BR in the estimation, mainly in applications where respiratory rate is out of the range 0.2-0.4 Hz.
- Published
- 2019