Overview¶
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. This book:
provides an introduction to the signals measured by wearables;
outlines key techniques for processing wearable signals; and
gives readers hands-on experience in applying signal processing and machine learning techniques to wearable data.
Aims¶
The aim of this book is to equip attendees with knowledge and skills to apply best practices to process wearable data, benefiting researchers in academia, device designers in industry, clinicians, and ultimately the millions of people who use wearables to monitor their health and fitness.
The Learning objectives are:
To understand the different types of signals acquired by wearables.
To learn fundamental techniques for processing wearable signals.
To gain hands-on experience of signal processing and machine learning with wearable data.
Teaching¶
This book is designed as a teaching resource which can either be used by individuals for self-study, or to structure teaching sessions.
The resource has supported the following events:
IEEE Engineering in Medicine and Biology Conference 2022 Workshop, titled ‘Open research in Biomedical Signal Processing: Cuffless Blood Pressure Estimation Using the MIMIC-IV Database’. Further details here.
AI UK 2023 Event, titled ‘Multimodal signal processing and learning for wearables’. Further details here.
VascAgeNet 2023 Training School, titled ‘Hands-on: analysing cardiovascular signals to assess vascular age’. Further details here.