Muscle Is Electrically Inexcitable in Acute Quadriplegic Myopathy

Document Type

Article

Publication Date

3-1-1996

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Abstract

Parkinson Disorder is a gradually increasing neurodegenerative disorder of motor and non-motor symptoms can impact on human basic functions to a wide variety of range. This computational study describes the essential 4 features of the arm to predict the actual result of Parkinson disorder computationally. Vector velocity and dimension reduction, these two mathematical evaluations are analyzed to detect joints and Mean Instantaneous Velocity is calculated to predict the actual Parkinson Disease of the affected patients. Many scientists used different classification models for predicting the disorder but as this is an abnormality in the neurons creates an effect on positional change, so we consider velocity as the most important evaluating parameter. DNN classifier has been used for the intermediate result to get the sensitivity, specificity and accuracy of the analysis. Randomly 30Hz sampling frequency was chosen to capture the whole data but a proper prediction technique to analyze the Parkinson Disorder in certain frequency always not shows a satisfactory result. The analysis in different sampling frequency is required to improve the prediction and for clarification of the result.

DOI

10.1212/WNL.46.3.731

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