Unit name | Sensing Technologies for Diagnostics and Monitoring |
---|---|
Unit code | EENGM0031 |
Credit points | 10 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Professor. Piechocki |
Open unit status | Not open |
Pre-requisites |
Undergraduate Degree in Engineering |
Co-requisites |
None |
School/department | School of Engineering Mathematics and Technology |
Faculty | Faculty of Engineering |
Low-cost, connected, digital technologies are increasingly seen as vital to the understanding, prevention, diagnosis and management of numerous health conditions over months and years in residential settings and in the community. These technologies, such as smartphone apps, wearables, blood glucose monitors – and ever growing Internet of Things (IoT) devices such as smart home systems (e.g. Echo), smart meters and connected appliances – all offer an unprecedented opportunity to characterise a person’s health condition. With the data processed by AI, they will deliver decision support to health and care professionals, predict a patient’s exacerbations, support independent living, deliver behavioural or even pharmaceutical interventions and allow the efficacy of treatments to be monitored. This unit will discuss nascent technologies and solutions for sensing human vital signs and physical behaviour encompassing entire data capture transmission/processing pipelines: from body worn and biosensors to low power wireless networks and energy constraint data processing.
Syllabus
On successful completion of this module students will be able to:
This unit will consist of a combination of teaching and learning methods
Coursework (15%): Written report based on computer laboratory experiments
Final Exam (85%): 2 hour written paper
Biosensors: An Introductory Textbook by Jagriti Narang, C.S. Pundir Jenny Stanford Publishing (2017) ISBN-13: 978-9814745949
Biosensors and Bioelectronics by Chandran Karunakaran, Kalpana Bhargava, Robson Benjamin Elsevier (2015) ISBN: 9780128031018
Biosensors for Medical Applications Edited by Séamus Higson, Woodhead publishing (2012) ISBN 978-1-84569-935-2
G.Z. Yang, Body Sensor Networks, 2nd edition, Springer, 2014.
J. Proakis, Digital Communications, 4th edition, McGraw Hill, 2000.