Non-Contact Vital Prediction Using rPPG Signals

Title

Non-Contact Vital Prediction Using rPPG Signals

Creator

Madhu M.; Gurudas V.R.; Manjunath C.; Naik P.; Kulkarni P.

Description

In this paper, we present the clinical significance of various cardiac symptoms with the use of heart rate detection, ongoing monitoring and present emotions. The development of algorithms for remote photoplethysmography has drawn a lot of interest during the past decade (rPPG). As a result, using data gathered from the video feed, we can now precisely follow the heart rate of individuals who are still seated. rPPG algorithms have also been developed, in addition to technique based on hand-crafted characteristics. Deep learning techniques often need a lot of data to train on, but biomedical data frequently lacks real-world examples. The experiment described in this work, we looked at how illumination affected the rPPG signals' SNR. The findings show that the SNR in each RGB channel varies depending on the colour of the light source. Paper describes development in video filtering for recognising the comprehending human face emotions. In our method, emotions are deduced by identifying facial landmarks and analysing their placement. 2023 IEEE.

Source

Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Convolutional neural networks; Deep learning; Facial expression recognition; Machine learning; Remote photoplethysmography

Coverage

Madhu M., CHRIST(Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, India; Gurudas V.R., CHRIST(Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, India; Manjunath C., CHRIST(Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, India; Naik P.; Kulkarni P., Dayananda Sagar University, Department of Computer Science and Engineering, Bangalore, India

Rights

Restricted Access

Relation

ISBN: 979-835033577-4

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/InC457730.2023.10263027

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174676842&doi=10.1109%2fInC457730.2023.10263027&partnerID=40&md5=1cce7af802d499de9ed7ebf73fb153f7