Tremor is a neuro degenerative disease causing involuntary muscle movements in human limbs. There are many types of tremor that are caused due to thedamage of nerve cells that surrounds thalamus of the front brain chamber.
It is hard to distinguish or classify the tremors as there are many reasons behind the formation of specific category, so every tremor type is named behind its frequency type. Proper medication for the cure by physician is possible only when the disease is identified.
Because of the argument given in the above paragraph, there is a need of a device or a technique to analyze the tremor and for extracting the parameters associated with the signal. These extracted parameters can be used to classify the tremor for onward identification of the disease.
There are various diagnostic and treatment monitoring equipment are available for many neuro-muscular diseases. This thesis is concerned with the tremor analysis for the purpose of recognizing certain other neurological disorders. A recording and analysis system for human’s tremor is developed.
The analysis was performed based on frequency and amplitude parameters of the tremor. The Fast Fourier Transform (FFT) and higher order spectra were used to extract frequency parameters (e.g., peak amplitude, fundamental frequency of tremor, etc). In order to diagnose subjects’ condition, classification was implemented by statistical significant tests (t‐test).
Source: Mid Sweden University
Author: Bejugam, Santosh