Friday, September 15th, 2023 - 14:00 - 17:30
at Toppo Wassermann Hall, Udine, Italy

held in conjuction with ICIAP 2023

The tutorial aims to provide a comprehensive overview of the state-of-the-art techniques and applications of remote physiological sensing. Particular emphasis will be put on the image and signal processing techniques adopted to estimate Blood Volume Pulse (BVP) signals and related pulse rates (remote photoplethysmography, rPPG) as well as respiratory signals, relying solely on RGB cameras.

The tutorial will focus on the technical aspects of remote physiological sensing, including the underlying principles, signal processing techniques, and data analysis methods to perform a principled assessment of the approaches proposed in the literature and their various applications.

A particular focus will be given to the datasets and metrics available to evaluate methods, as well as software tools developed by the community.

14:00 - 15:30 First Part

I. Introduction to Remote Physiological Sensing

Camera Measurement of Physiological Signals

Overview, applications and current trends

II. Remote Photoplethysmography (rPPG)

Algorithmic Principles - Skin reflection model

Classical/knowledge-based approaches

Deep Learning Based approaches

Known limits and state of the art

15:30 - 16:00 Coffee Break

16:00 - 17:30 Second Part

III. Remote Respiration monitoring

Motion-based

rPPG-based: Respiratory induced variations (RIVs)

Deep Learning Based Methods

IV. Practical Applications

Papers

• Boccignone, G., Conte, D., Cuculo, V., d’Amelio, A., Grossi, G., & Lanzarotti, R. (2020). An open framework for remote-PPG methods and their assessment. IEEE Access, 8, 216083-216103.
  https://doi.org/10.1109/ACCESS.2020.3040936

• Boccignone, G., Conte, D., Cuculo, V., D’Amelio, A., Grossi, G., Lanzarotti, R., & Mortara, E. (2022). pyVHR: a Python framework for remote photoplethysmography. PeerJ Computer Science, 8, e929.
  https://doi.org/10.7717/peerj-cs.929
  
  

Tools

• Package pyVHR (short for Python framework for Virtual Heart Rate) is a comprehensive framework for studying methods of pulse rate estimation relying on video, also known as remote photoplethysmography (rPPG).
  https://github.com/phuselab/pyVHR

Special Issue

• Biomedical Signal Processing and Control Journal (IF: 5.1)
  Remote Physiological Measurement: Novel algorithms and application areas
  https://www.sciencedirect.com/journal/biomedical-signal-processing-and-control/about/call-for-papers#remote-physiological-measurement-novel-algorithms-and-application-areas