Abstract
The SIMCA (soft independent modelling of class analogy) method of pattern recognition has been used to classify four muscle fibre types: I, IIA, IIB and IIC. The samples were histochemically stained human skeletal sections from biopsy material. Disjoint (separate) class modelling gave information about variables, i.e., the combinations of alkaline, acidic and Ca2+-containing preincubation procedures with appropriate discrimination power, and showed satisfactory separation of the classes (fibre types). Two serial stained muscle sections represent a minimum for a proper classification of the four fibre groups. A comparison of biopsy samples from two different persons showed significant variation in the data structure between similar fibre types, probably caused by intermuscle variations. It is suggested that the introduction of computer-assisted classification by the application of such multivariate analytical techniques both facilitates the classification of muscle fibres and improves the precision and reliability of fibre typing.
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