A sequential algorithm for recognition of a developing pattern with application in orthotic engineering

This paper describes an algorithm for the recognition of the type of grip being formed by a subject wearing an intelligent orthotic glove. The signal is a growing multivariate sequence to be correctly classified as soon as the data permit, so the task may be called one of sequential classification or sequential discrimination. The algorithm uses a variant of the ‘kk nearest neighbours’ principle with the dissimilarity measure being an exponentially weighted moving average of distances of the Mahalanobis type. The approach taken seems suitable for other problems of this kind.