Non-Contact Respiration Measurement Method Based on RGB Camera Using 1D Convolutional Neural Networks.

ABSTRACT: Conventional respiration measurement requires a separate device and/or can cause discomfort, so it is difficult to perform routinely, even for patients with respiratory diseases. The development of contactless respiration measurement technology would reduce discomfort and help detect and prevent fatal diseases. Therefore, we propose a respiration measurement method using a learning-based region-of-interest detector and a clustering-based respiration pixel estimation technique. The proposed method consists of a model for classifying whether a pixel conveys respiration information based on its variance and a method for classifying pixels with clear breathing components using the symmetry of the respiration signals. The proposed method was evaluated with the data of 14 men and women acquired

SUBMITTER: Hwang HS 

PROVIDER: S-EPMC8157066 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature