Contents

Workshop - March 2023

Welcome

Welcome to this workshop, which will provide an introduction to the fundamentals of biomedical signal processing and learning for wearable signals of multiple modalities.

Organisers

This workshop is co-organised by:

The workshop was designed and run by researchers from several universities across Europe:

  • Kelly Ding, University of Cambridge

  • Elisa Mejia-Mejia, City, University of London

  • Serena Zanelli, University Sorbonne Paris Nord

  • Marton Goda, Technion - Israel Institute of Technology

  • Peter Charlton, University of Cambridge

Outline

This is an interactive, online workshop providing an introduction to the fundamentals of biomedical signal processing and learning for wearable signals of multiple modalities.

The workshop will consist of three parts:

  • Participants will be introduced to the signals measured by wearables, including photoplethysmogram and electrocardiogram signals.

  • Participants will learn fundamental techniques for processing wearable signals through interactive tutorials.

  • Participants will gain hands-on experience of signal processing and machine learning with wearable data through a group exercise, applying data analysis to real-world problems.

The workshop will use pre-prepared teaching materials consisting of online Jupyter notebooks running Python code on the cloud, so no installation is required on participants’ computers. The teaching materials are designed to be highly accessible to the non-specialist, while also providing opportunity for people with experience in the field to explore the topic more deeply.

Schedule

The workshop will last 2 hours.

Time

Content

5 mins

Welcome and overview

15 mins

Introduction to wearables

40 mins

Interactive Tutorials

5 mins

Overview of case studies

45 mins

Group work

5 mins

Group feedback

5 mins

Summary

Preparation

You must register for the workshop here.

Whilst no preparation is required for the workshop, attendees are encouraged to:

  1. Familiarise yourself with these resources.

  2. Ensure that you can run the tutorials and case study in Google Colab.

Introductory presentation

The slides from the introductory presentation are available here.

Acknowledgment

Thanks to the Institute of Physics and Engineering in Medicine, who helped publicise this event.