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Unit information: Sensing Technologies for Diagnostics and Monitoring in 2021/22

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

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 Dr. Masullo
Open unit status Not open

Undergraduate Degree in Engineering



School/department School of Engineering Mathematics and Technology
Faculty Faculty of Engineering

Description including Unit Aims

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.


  • Introduction to sensing and biosensing to detect and monitor diseases
  • Characterisation of operation of sensors and biosensors: sensitivity, specificity, clinical range etc.
  • Principles and transduction approaches for biochemical sensors: electrochemical, MEMs, optical etc.
  • Biomarker detection and bio-receptors e.g. antibodies, enzymes, DNA
  • Sensor system development e.g. data capture, sample preparation
  • Physiological measurement e.g. ECG, EMG, EEG;
  • Basic elements of the wireless channel and radio wave propagation.
  • Low Power IoT wireless networks (IEEE 802.15.4, BLE, 6LoWPAN).
  • Reliability in data transmission
  • Efficient signal representation, compression, and ultimately classification/regression tasks.

Intended Learning Outcomes

On successful completion of this module students will be able to:

  1. Critically evaluate and discuss the role of sensors in home diagnostics and monitoring applications
  2. Evaluate a range of elements involved in constructing and operating a biosensor, and select and apply the optimum combination for a given application
  3. Analyse a diagnostic or monitoring scenario, and devise and evaluate an effective measurement system from sample/signal collection to user interface
  4. Explain the challenges of reliable communications over unreliable channels and basic IoT networking standards.
  5. Design and prototype algorithms for data analysis of sensory signals such as step counters, classification and regression

Teaching Information

Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, practical activities supported by drop-in sessions, problem sheets and self-directed exercises.

Assessment Information

Exam (January, 85%) and coursework (15%)


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How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.