Abstract
The monitoring of respiratory rate is a relevant factor in medical applications and day-to-day activities. Contact sensors have been used mostly as a direct solution and they have shown their effectiveness, but with some disadvantages for example in vulnerable skins such as burns patients. For this reason, contactless monitoring systems are gaining increasing attention for respiratory detection. In this paper, we present a new non-contact strategy to estimate respiratory rate based on Eulerian motion video magnification technique using Hermite transform and a system based on a Convolutional Neural Network (CNN). The system tracks chest movements of the subject using two strategies: using a manually selected ROI and without the selection of a ROI in the image frame. The system is based on the classifications of the frames as an inhalation or exhalation using CNN. Our proposal has been tested on 10 healthy subjects in different positions. To compare performance of methods to detect respiratory rate the mean average error and a Bland and Altman analysis is used to investigate the agreement of the methods. The mean average error for the automatic strategy is 3.28 ± 3.33 % with and agreement with respect of the reference of ≈98%.
Highlights
The monitoring of Respiratory Rate (RR) is a relevant factor in medical applications and day-to-day activities
The least accurate Convolutional Neural Network (CNN)-model corresponds to the one using the original video without any processing (83.33 ± 4.92% for OV approach) while the other two approaches look similar in response (97.30 ± 1.32% for magnified components video (MCV) approach and 97.66 ± 1.26% for magnified video (MV) approach)
The mean average error (MAE) obtained by the CNN proposal is 1.830 ± 1.610% and Mean Absolute Error (MAE) obtained by the image processing methods (IPM) method is 2.470 ± 2.300%
Summary
The monitoring of Respiratory Rate (RR) is a relevant factor in medical applications and day-to-day activities. Contact sensors have been used mostly as a direct solution and they have shown their effectiveness, but with some disadvantages. The main inconveniences are related to the correct and specific use of each contact sensor, the stress, pain, and irritation caused, mainly on some vulnerable skins, like neonates and burns patients [1]. For a review of contact-based methods and comparisons see [2]. Contactless breathing monitoring is a recent research interest for clinical and day-to-day applications; a review, and comparison of contactless monitoring techniques can be seen in [3]. The literature review is restricted to respiratory activity and the works concerning the detection of cardiac activity are not included voluntarily
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