Piotr Prokopowicz

Analysis of the changes in processes using the Kosinski's Fuzzy Numbers

This paper presents the analysis of potential of the Kosinskis Fuzzy Number (KFN) idea in the modeling trends of the processes which are described imprecisely. KFNs conception is an alternative for the classical fuzzy numbers ideas as model to represent of the imprecise quantitative data. They introduces new feature into vagueness of the information - a direction. It is base for good arithmetical properties of calculations. Furthermore, a direction also extends a potential in the modeling of information by the additional interpretation, what is a subject of this article. This new potential is presented and explained basing on the example of modeling of quantity of liquid in a reservoir. The environment is changing dynamically what is described as the changes in inflow and outflow. Proposed example explains how to interpret the direction of KFN and how to understand the results of calculations and its influence.

Computational gait analysis using fuzzy logic for everyday clinical purposes – preliminary findings

Abstract Background: Proper, early, and exact identification of gait impairments and their causes is regarded as a prerequisite for specific therapy and a useful control tool to assess efficacy of rehabilitation. There is a need for simple tools allowing for quickly detecting general tendencies. Objective: The aim of this paper is to present the outcomes of traditional and fuzzy-based analysis of the outcomes of post-stroke gait reeducation using the NeuroDevelopmental Treatment-Bobath (NDT-Bobath) method. Materials and methods: The research was conducted among 40 adult people: 20 of them after ischemic stroke constituted the study group, and 20 healthy people constituted the reference group. Study group members were treated through 2 weeks (10 therapeutic sessions) using the NDT-Bobath method. Spatio-temporal gait parameters were assessed before and after therapy and compared using novel fuzzy-based assessment tool. Results: Achieved results of rehabilitation, observed as changes of gait parameters, were statistically relevant and reflected recovery. One-number outcomes from the proposed fuzzy-based estimator proved moderate to high consistency with the results of the traditional gait assessment. Conclusions: Observed statistically significant and favorable changes in the health status of patients, described by gait parameters, were reflected also in outcomes of fuzzy-based analysis. Proposed fuzzy-based measure increases possibility of the clinical gait assessment toward more objective clinical reasoning based on common use of the mHealth solutions.

Fuzzy-based computational simulations of brain functions – preliminary concept

Abstract Research on the computational models of the brain constitutes an important part of the current challenges within computational neuroscience. The current results are not satisfying. Despite the continuous efforts of scientists and clinicians, it is hard to fully explain all the mechanisms of a brain function. Computational models of the brain based on fuzzy logic, including ordered fuzzy numbers, may constitute another breakthrough in the aforementioned area, offering a completing position to the current state of the art. The aim of this paper is to assess the extent to which possible opportunities concerning computational brain models based on fuzzy logic techniques may be exploited both in the area of theoretical and experimental computational neuroscience and in clinical applications, including our own concept. The proposed approach can open a family of novel methods for a more effective and (neuro)biologically reliable brain simulation based on fuzzy logic techniques useful in both basic sciences and applied sciences.

Fuzzy System as an Assessment Tool for Analysis of the Health-Related Quality of Life for the People After Stroke

Stroke remains one of the leading causes of long-term disability in both developed and developing countries. Prevalence and impact of the stroke-related disability on Health-Related Quality of Life (HRQoL) as a recognized and important outcome after stroke is huge. Quick, valid and reliable assessment of the HRQoL in people after stroke constitutes a significant worldwide problem for scientists and clinicians - there are many tools, but no one fulfills all requirements or has prevailing advantages. This paper presents proposition of an evaluation of HRQoL based on the two-level hierarchical fuzzy system. It uses five clinical scores and scales as the inputs and gives in result value from the interval [0; 1]. It may constitute a useful semi-automated tool for supplementary initial assessment of patient functioning and further cyclic re-assessment for rehabilitation process and patient-centered goals of rehabilitation shaping purposes.

Modeling Trends in the Hierarchical Fuzzy System for Multi-criteria Evaluation of Medical Data

The paper presents the analysis and application of hierarchical fuzzy system to the problem of evaluation/measurement of the rehabilitation effects in post-stroke patients. Healthy people constitute reference group. Prevalence and impact of the stroke-related disorders on Health-Related Quality of Life (HRQoL) as a recognized and important outcome after stroke is huge. Quick, valid and reliable assessment of HRQoL in people after stroke constitutes a worldwide significant problem for scientists and clinicians - there are many tools, but no one fulfills all requirements or has prevailing advantages. Evaluation model presented here is improved version of earlier attempts and applies the potential of fuzzy systems for linguistic modeling of rules. It provides a great advantage as there are experienced clinicians working on the improvement of the rehabilitation methods but there is no intuitive formal model to measure their effects. The innovative element here is the use of Ordered Fuzzy Number model. It is a good tool for modeling the trends in information used to create the fuzzy rules of small fuzzy systems which together form a hierarchical fuzzy evaluation model.

Analysis of Temporospatial Gait Parameters

Locomotion in post-stroke patients may be severely compromised. Assessment and treatment of gait disorders after stroke are crucial. Scientists and clinicians still look for more effective diagnostic and therapeutic tools. The aim of the study was to assess a new fuzzy-based tool for measurement of observed gait parameters (velocity, cadence, and stride length, and their normalized values), both in healthy people and post-stroke patients.

OFN-Based Brain Function Modeling

A modeling approach may significantly help to explore the problem of weak understanding of the physiological and pathological central nervous system function in the most noninvasive and comprehensive way. The aim of this chapter is to assess and discuss the extent to which possible opportunities concerning computational brain models based on fuzzy logic techniques may be exploited.

Fuzzy numbers calculations as help in fatigue reliability estimation

Fuzzy numbers and fuzzy arithmetic were introduced in order to analyze and manipulate approximate numerical values. In modern complex and large-scale systems we often have to deal with imprecise data. The reasons may be: different experience of people operating the system, not well-known area of knowledge, too many parameters to get them together in short time.