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Tremor is a neuro degenerative disease causing involuntary musclemovements in human limbs. There are many types of tremor that arecaused due to the damage of nerve cells that surrounds thalamus of thefront brain chamber. It is hard to distinguish or classify the tremors asthere are many reasons behind the formation of specific category, soevery tremor type is named behind its frequency type. Propermedication for the cure by physician is possible only when the disease isidentified.Because of the argument given in the above paragraph, there is a needof a device or a technique to analyze the tremor and for extracting theparameters associated with the signal. These extracted parameters canbe used to classify the tremor for onward identification of the disease.There are various diagnostic and treatment monitoring equipment areavailable for many neuromuscular diseases. This thesis is concernedwith the tremor analysis for the purpose of recognizing certain otherneurological disorders. A recording and analysis system for human’stremor is developed.The analysis was performed based on frequency and amplitudeparameters of the tremor. The Fast Fourier Transform (FFT) and higherorderspectra were used to extract frequency parameters (e.g., peakamplitude, fundamental frequency of tremor, etc). In order to diagnosesubjects’ condition, classification was implemented by statisticalsignificant tests (t‐test).