Meeting Register Page

Multimodal signal processing and learning for wearables

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

Digital wearable devices have great potential to improve health and wellbeing by monitoring physiology in daily life. A key challenge is making wearable data as rich and accurate as possible. The aim of this workshop is to equip attendees with knowledge and skills in processing wearable data, benefiting researchers in academia, device designers in industry, and ultimately the millions of people who use wearables to monitor their health and fitness.

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.

---

This event is part of AI UK 2023. The Alan Turing Institute’s national showcase of data science, machine learning and artificial intelligence research and innovation.

At a series of events between 6 – 31 March 2023, AI UK Fringe brings together leaders in academia from across the UK’s AI ecosystem to demonstrate, exhibit and update on their ground-breaking work.

We’re excited to be part of AI UK Fringe this March and can’t wait for you to join.

Find out more about AI UK at ai-uk.turing.ac.uk

---

10:00-12:00 UK time

Mar 15, 2023 10:00 AM in London