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3 Journal of Medical Informatics & Technologies

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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.

Modelling the data record of a patient walk by langrange-polynomial method

Chandzlik S., Piecha J.

Journal of Medical Informatics & Technologies

2002

Vol. 3

MI143--152

Various options available in PSW footprint and walking characteristics measuring equipment [6], [7], give the user many aims in putting diagnosis. A Conclusion-Making Unit (CMU) that has been described in this paper supports the diagnosis automation procedures. Due to simplifying the CMU training process some affords in a field of the input record length reduction have been undertaken. The paper describes an analytical method of the data record description that allows converting discrete data samples into continuous function. This way a redigitalisation of the record can be done, where sampling period is matched with the walk length. This normalization allows reducing the data record length used for fast training of the CMU.

A patient walk-data-record modelling using a spline interpolation method

Chandzlik S., Piecha J.

Journal of Medical Informatics & Technologies

2002

Vol. 3

MI153--159

The paper describes an analytical method of data record description that allows converting samples of discrete data record into continuous function. This operation allows re-sampling the data record with a sampling rate that is adequate to step duration. The record length is limited to an efficient size for training the Conclusion-Making Unit (CMU). Various options available in the PSW equipment [6], [7] give the user many aims in putting diagnosis anyhow, due to simplification of the CMU training process several methods for data records modifications are considered.