1. Artificial Intelligence Techniques
Applications of Neural Networks

2. Example Applications Analysis of data Classifying in EEG
Pattern recognition in ECG
EMG disease detection.

3. To produce a model of risk facts in heart disease. MLP used
Gueli N et al (2005) The influence of lifestyle on cardiovascular risk factors analysis using a neural network Archives of Gerontology and Geriatrics –172
To produce a model of risk facts in heart disease.
MLP used
The accuracy was relatively good for chlorestremia and triglyceremdia:
Training phase around 99%
Testing phase around 93%
Not so good for HDL

5. Electroencephalography (EEG)
Subasi A (in press) Automatic recognition of alertness level from EEG by using neural network and wavelet coefficients Expert Systems with Applications xx (2004) 1–11
Electroencephalography (EEG)
Recordings of electrical activity from the brain.
Classifying operation
Awake
Drowsy
Sleep

6. Input is normalise to be within the range 0 to 1.
MLP
Hidden layer – log-tanh function
Output layer – log-sigmoid function
Input is normalise to be within the range 0 to 1.

7. Accuracy
95%+/-3% alert
93%+/-4% drowsy
92+/-5% sleep
Feature were extracted and form the input to the network, from wavelets.

8. ECG – electrocardiographs – electrical signals from the heart.
Karsten Sternickel (2002) Automatic pattern recognition in ECG time series Computer Methods and Programs in Biomedicine –115
ECG – electrocardiographs – electrical signals from the heart.
Wavelets again.
Classification of patterns
Patterns were spotted

11. EMG – Electromyography – muscle activity.
Abel et al (1996) Neural network analysis of the EMG interference pattern Med. Eng. Phys. Vol. 18, No. 1. pp. 12-l 7
EMG – Electromyography – muscle activity.
Interference patterns are signals produce from various parts of a muscle- hard to see features.
Applied neural network to EMG interference patterns.

12. Applied various different ways of presenting the pattern to the ANN.
Classifying
Nerve disease
Muscle disease
Controls
Applied various different ways of presenting the pattern to the ANN.
Good for less serve cases, serve cases can often be see by the clinician.

13. Example Applications Wave prediction Controlling a vehicle
Image processing
Condition monitoring

14. Wave prediction
Raoa S, Mandal S(2005) Hindcasting of storm waves using neural networks Ocean Engineering 32 (2005) 667–684
MLP used to predict storm waves.
2:2:2 network
Good correlation between ANN model and another model

16. ANN replaces a mathematical model of the system.
van de Ven P, Flanagan C, Toal D (in press) Neural network control of underwater vehicles Engineering Applications of Artificial Intelligence
Semiautomous vehicle
Control using ANN
ANN replaces a mathematical model of the system.

19. Kuo RJ, et al (in press) Part family formation through fuzzy ART2 neural network Decision Support Systems
Image recognition of part
Deals with the shifting of the part

21. Combines ANN with other AI (Expert systems)
Silva et al (2000) THE ADAPTABILITY OF A TOOL WEAR MONITORING SYSTEM UNDER CHANGING CUTTING CONDITIONS Mechanical Systems and Signal Processing (2000) 14(2),
Modelling tool wear
Combines ANN with other AI (Expert systems)
Self organising Maps (SOM) and ART2 investigated
SOM better for extracting the required information.