Neurological Tremor simulation using a skin tissue model and Tremor classification using Fiber Bragg grating sensors

Abstract

In the diagnosis of neurological disorders multiple sensing and analysis technologies have been developed. In this work effort is to synthesize tremor signals on modal and harmonic analysis workbench and classify the smokers and non-smokers tremor signals in the perspective of optical sensing. Associated objective is to analyse and extract performance parameters using the skin-tissue models of smokers and non-smokers classes in modal/harmonic analysis tool boxes and to inspect the force effects on Fiber Bragg grating sensor. The novelty lies in the fact that a biophysical computational model on deep layers of human skin is implemented on which tremor analysis have been carried out. Further the model is employed to inspect effects which are mechanical on Fibre Bragg grating sensors subjected to tremor motions indicating subtle changes in skin deformation. The developed models correlates tremor induced frequencies and disorders of neurology as the zones of frequencies deployed for synthesis are in the clinical tremor zones of frequencies.