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3 Journal of Medical Informatics & Technologies

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The interference spectrum extraction of a gait characteristics data record

Chandzlik S., Piecha J.

Journal of Medical Informatics & Technologies

2004

Vol. 7

KB23--32

The paper shows several aspects of the gait data record analysis describing neurological diseases. The diagnosis of the gait abnormalities concerns interferences level of the patient physiological records. The disease source and level can be classified by the relevant interference functions. These functions were used for artificial records creation to multiply the necessary set of data needed for neural network training.

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.