Summary: | Background/Aim. Postural impairments and gait disorders in Parkinson's
disease (PD) affect limits of stability, impaire postural adjustment, and
evoke poor responses to perturbation. In the later stage of the disease, some
patients can suffer from episodic features such as freezing of gait (FOG).
Objective gait assessment and monitoring progress of the disease can give
clinicians and therapist important information about changes in gait pattern
and potential gait deviations, in order to prevent concomitant falls. The aim
of this study was to propose a method for identification of freezing episodes
and gait disturbances in patients with PD. A wireless inertial sensor system
can be used to provide follow-up of the treatment effects or progress of the
disease. Methods. The system is simple for mounting a subject, comfortable,
simple for installing and recording, reliable and provides high-quality
sensor data. A total of 12 patients were recorded and tested. Software
calculates various gait parameters that could be estimated. User friendly
visual tool provides information about changes in gait characteristics,
either in a form of spectrogram or by observing spatiotemporal parameters.
Based on these parameters, the algorithm performs classification of strides
and identification of FOG types. Results. The described stride classification
was merged with an algorithm for stride reconstruction resulting in a useful
graphical tool that allows clinicians to inspect and analyze subject’s
movements. Conclusion. The described gait assessment system can be used for
detection and categorization of gait disturbances by applying rule-based
classification based on stride length, stride time, and frequency of the
shank segment movements. The method provides an valuable graphical interface
which is easy to interpret and provides clinicians and therapists with
valuable information regarding the temporal changes in gait. [Projekat
Ministarstva nauke Republike Srbije, br. 175016 i br. 175090]
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