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Primary syllabus: Physics and statistics

Created: 7/9/2004
Updated: 7/3/2007

Trainees should understand the physical principles upon which methods of clinical measurement are based. Knowledge of clinical measurement techniques should be limited to principles and basic methods.

Mathematical concepts: sinusoids, exponentials and parabolas. Exponential functions and logarithms

Basic measurement concepts: linearity, drift, hysteresis, signal:noise ratio, dynamic response

SI units. Fundamental and derived units

Simple mechanics: mass, force, work and power

Heat: simple calorimetry. Conduction, convection, radiation. Mechanical equivalent of heat: laws of thermodynamics

Physics of gases. Absolute and relative pressure. The gas laws. Triple point: critical temperature. Density and viscosity of gases. Laminar and turbulent flow. The Bernoulli principle

Freezing point, melting point. Latent heat. Vapour pressure. Colligative properties; osmometry

Basic concepts of electricity and magnetism. Capacitance, inductance and impedance. Amplifiers. Band width, filters. Amplification of biological potentials: ECG, EMG, EEG. Sources of electrical interference

Processing, storage and display of physiological measurements. Bridge circuits

Basic principles of lasers

Principles of cardiac pacemakers and defibrillators

Electrical hazards: causes and prevention. Electrocution, fires and explosions. Diathermy and its safe use

Principles of pressure transducers.

Resonance and damping, frequency response

Measurement of pressure. Direct and indirect methods of blood pressure measurement. Pulmonary artery pressure

Measurement of volume and flow in gases and liquids. The pneumotachograph and other respirometers. Peak flow measurement. Spirometry. Cardiac output

Measurement of temperature and humidity

Measurement of gas concentrations, especially oxygen, carbon dioxide, nitrogen, nitrous oxide, volatile anaesthetic agents

Measurement of pH, pCO2, pO2

Simple tests of pulmonary function


Pulse oximetry

Measurement of neuromuscular blockade

Measurement of pain


Candidates will be required to demonstrate understanding of basic statistical concepts, but will not be expected to have practical experience of statistical methods. Emphasis will be placed on methods by which data may be summarised and presented, and on the selection of statistical measures for different data types. Candidates will be expected to understand the statistical background to measurement error and statistical uncertainty.

Descriptive statistics

Categories of data. Statistical distributions (Gaussian, chi-squared, binomial) and their parameters. Non-parametric measures of location and variability. Graphical presentation of data

Deductive and inferential statistics

Simple probability theory. Confidence intervals. Linear regression. Linear correlation

The null hypothesis. Type I and type II errors. Probability of error occurrence, and the power of a test to detect a significant difference, Bland-Altman plot. Choice of simple statistical tests for different data types

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