Wearable Technologies (867H1)
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Wearable Technologies
Module 867H1
Module details for 2024/25.
15 credits
FHEQ Level 7 (Masters)
Module Outline
In this module, you will learn about the fundamentals of wearable technologies, including technological (computing, communication, sensing, energy, exoskeleton, exosuits), algorithmic (signal processing and machine learning) and applicative aspects through a combination of theoretical analysis and hands-on experimentation. You will learn what are the unique characteristics offered by wearable technologies, such as accurate sensing of body and physiological parameters, which enables a "smart assistant" capable of reacting to the user's activities and needs. You will also learn about the unique challenges posed by their development alongside the choice of technologies and human factors.
The syllabus covers the following AHEP4 learning outcomes: M2, M4, M5, M6, M7, M16
Module learning outcomes
Evaluate critically the unique characteristics of wearable technologies and the novel possibilities they offer from a theoretical and practical perspective; including ethical implications, social impact, and sustainability.
Design wearable devices from requirement gathering to their evaluation, evaluate the implementation challenges, and design trade-offs, working effectively as individuals and as part of a team.
Employ state of the art approaches to realise sensor-based context-aware wearable systems within power, memory, speed, latency and performance targets
Describe and analyse the signal processing and applied machine learning techniques used for activity and context awareness
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 100.00% | |
| Coursework components. Weighted as shown below. | ||
| Essay | A2 Week 1 | 100.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Spring Semester | Laboratory | 2 hours | 01111111111 |
| Spring Semester | Lecture | 2 hours | 11111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Carlo Tiseo
Assess convenor
/profiles/555178
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