A method for the classification of corrective activity in context dependent postural controlling tasks

Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Menière's disease, can cause instability in walking and standing. Regardless of the origin of the problem in the balance system, it has to be detected in a meaningful, easily interpretable way. When detected, a suitable rehabilitation method can be proposed. In this paper we present a method which extracts a scalar feature from a stabilogram signal, which well describes the differences between young and elderly people's swaying processes. When our feature is applied to the K nearest neighbour algorithm the correct recognition accuracy is over 70% in cases where the purpose is to predict whether an unknown test feature is measured from a young or an elderly subject.