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The diseases classification method on gait abnormalities characteristic contributions

Chandzlik S., Piecha J.

Journal of Medical Informatics & Technologies

2005

Vol. 9

187--194

Present medicine uses computers in various applications, especially in a field of a diseases level classification and diagnosis. In many cases an automatic conclusion making units are the main goal of the computer systems usage. The software units are developed for the diseases classification or for monitoring of the disease medical treatment. An example application was described in this paper. It concerns a gait abnormalities level analysis that is described by a data records gathered by insoles of Parotec System for Windows (PSW) [17,18]. The PSW software package is used for visualisation of the gait characteristic static and dynamic characteristic features. In the authors' works many additional data components were distinguished. The field of the applications is located within the neurological gait characteristics also the source applications concern orthopaedics [16,18]. Careful analysis of the data provided the developers with new areas the PSW applications [4,11,13]. For conclusion making units the artificial networks theory was implemented [2,4,11,13]. For more effective training of the neural networks specific characteristic measures were introduced [4,5]. They allow controlling the training process more precisely, avoiding mistakes in current records classification.

The body balance measures for neurological disease estimation and classification

Chandzlik S., Piecha J.

Journal of Medical Informatics & Technologies

2003

Vol. 6

IT87--94

The paper describes body balance characteristics needed for neurological diseases classification and for rehabilitation processes controlling during patient recovery processes. These diagnosis factors allow simplify the PSW (Parotec System for Windows) records recognition [1, 2] then a walk-motor disturbances level estimation. The discussed clinical experiments illustrate new methods for Parkinson disease and stroke progress monitoring. This study was based on many observations of patient walk disturbances recorded in PSW files describing the pressure distribution on an insole set of sensors [1, 2, 8]. The gait regular asymmetry in a data spectrum has been noticed as an independent factor from the disease duration and its severity. In majority of analysed cases for Parkinson disease a gravity centre of the body moved into a heel region. Trajectories of foot gravity centre elongation, their irregularities, a floor-contact time and paresis limb loading values increase also were observed. The PSW system has successfully been used for recognition and quantification of walk-motor disturbances, marking the neurological diseases level. Options available in PSW [1, 2] give the user many aims in putting proper diagnosis anyhow, due to simplify the training process of conclusion making unit several methods for data records modifications and the diagnosis factors extraction were also considered.