University of Texas at El Paso
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Electrical Engineering
   
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Virginia Granda
Chad MacDonald


   
Introduction Minimize    

Hemiplegic stroke, paraparesis from spinal cord injuries, and other upper motor neuron syndromes such as multiple sclerosis and cerebral palsy cause serious neurological impairments and mobility-related disability. The complexity of the interactions of various components of human gait has been researched and documented extensively, and to date it is the experienced clinician who continues to perform functional gait assessment and training in the absence of virtually any technological assistance.

While traditional methods have involved complex statistical analysis, the aim of this research is to introduce an algorithm (the key concepts of Fuzzy Logic) to design an expert system, to improve the effectiveness of rehabilitative treatments for sensorimotor disabilities, and especially for ambulation, balance, and maintenance of physical fitness across these neurologic diagnoses.


   
Experimental Design Minimize    

Human motion analysis and neurorehablitation applications demand instrumented analytical tools for quantitative analysis of movements. This may be based on the simultaneous measurement of video data, ground reaction forces and electromyography (EMG) data. To permit simultaneous measurements of sagittal, coronal and transverse motion of the hip, knee and ankle, multiple markers are used to illustrate 3D dimensions. This method may exhibit more detailed analysis of complex patterns in the dynamic behavior during movements.




   
Gait Cycle Minimize    

A single cycle of human gait can be divided into several different phases. The first division is between the stance and swing phases. For a typical healthy subject the stance phase covers the first 60% of their gait cycle while the stance phase represents the remaining 40%. Each of these phases can then be divided into a number of sub-phases based on a series of gait events.

Stance Phase
  •  Loading Response - LR
  •  Midstance - MST
  •  Terminal Stance - TST
  •  Preswing (PSW) - PSW
Swing Phase
  •  Initial Swing - ISW
  •  Midswing - MSW
  •  Terminal Swing - TSW


   
Fuzzy Systems Minimize    

One way of dealing with real world phenomena is qualitative and non-numerical in nature. In decision-making processes as in neurorehabilitation, masses of numerical data are converted into some qualitative form and thus are dealt with only in aggregation. This form of aggregation gives rise to a set of linguistic labels and is sometimes referred to as information granules. This aggregation of information makes the partition of input space more manageable for further processing. All cognition and inference processing are then carried out at the level of the granules. This process of aggregation or granulation implies that we deal with the relationships of functions between linguistic labels rather than with numerical quantities. To cope with this style of cognition, a suitable modeling technique, the theory of fuzzy sets, may be applied since this theory deals with such granularity of perception.