Advanced Physiological Monitoring and Data Analysis

Module aims

The module will be an advanced level module that will focus on four core aspects of biological and clinical measurement.

1.    Data handling and fitness for purposes  - Normality of experimental data, types of error

2.   Methods for selective and sensitive detection  - Electrochemical sensors and biosensors

3.   Sampling Biomolecules form the human body  - Blood, Sweat, Tears, Urine, Saliva

4.   Invasive chemical measurement in tissue and cells. - concentration in tissue, measurement methods, interpretation of data

The topics will be supported using papers from the recent literature.

Learning outcomes

Learning Outcomes - Knowledge and Understanding

  • Explain the concepts of fitness for purpose, calibration and reliability of measurement as applied to physiological monitoring
  • Calculate measurement statistics
  • Apply the principles of bioanalytical science to the analysis of human body fluids, cells and isolated tissue and measurement in vivo 
  • Explain of the importance of temporally resolved data in the understanding of complex physiological systems
  • Critically review and make use of research papers in the area of physiological monitoring and bioanalysis

Learning Outcomes - Intellectual Skills

  • Assess whether measurement methods used in a study are fit for purpose
  • Explain features of experimental data using knowledge and understanding obtained during the course
  • Assess whether conclusions are justified by measured data

Learning Outcomes - Practical Skills

  • Journal article reading

Learning Outcomes - Transferable Skills

  • Information gathering from data - for example critical assessment of experimental data

Module syllabus

Data handling and fitness for purpose

Normality of experimental data, including types of error  

Electrochemical sensors

Physiological monitoring

Measurement in human biofluids

Measurement in tissue

The extracellular space

What determines the concentration of molecules in tissue Interpretation of graphs from journal articles in these areas

Pre-requisites

None Simple algebra / calculus only for the statistics of measurement part.

Teaching methods

Lectures: 28 hours

Study groups: 2 hours

Assessments

Examinations:

‚óŹ  Written exam: Advanced Physiological Monitoring and Data Analysis; 100% weighting

    Rubrics: Exam in May and 2.5 h long; Students choose 4 from 4 questions; two sections. A Dr O'Hare (2 Questions), B Prof Boutelle (2 Questions).

     Outline answers to past papers will be available

Feedback : Feedback to data handling problems given in catch-up session Feedback to Journal clubs given during each session

Reading list

Background

Supplementary

Module leaders

Professor Martyn Boutelle