IJSR - International Journal of Scientific Research

Puja Sengupta

Volume : VII, Issue : XI, November - 2018

Continuous Monitoring System for Analysing Vegetative State and Comatose Patients with The Help of Somatosensory Evoked Potential and Deep Learning

Puja Sengupta

Abstract :

As of today’s age, growing of technologies in every field has been creating an astonishing revolution. In

the mead of medical also, technologies like robotics and AI has been creating a whole new transformation in the field of monitoring, surgeries or in an assistance. Likewise, Brain computer interface is also one of the fast growing technologies that has helped the researchers and medical practitioners to work with the electroencephalography (EEG) activity in the context of degree of consciousness of patients by means of Different types of EEG signal detecting tools. Various methods have been proposed so far for the prognosis of between a (VS /UWS) and MCS patients or a comatose patients and its level of recovery. Diagnosis for the possibility of recoveries has been mostly emphasized in the recent research work for the comatose, LIS or other vegetative state. So by implementing a continuous monitoring system for the unresponsive wakefulness syndrome(UWS) with the help of deep learning we can accelerate the pre diagnosis of the patients. In some of the cases, patients who are in Vegetative state sometimes may end up with comatose or LIS. To check continuously or monitoring the condition of the patient, we can set up a system which can track the continuous changes of the signal of the ain or the sudden recovery of the patient in aspect of continuous stimuli. So with the help of somatosensory evoked potential(SSEP) and deep learning we will set up a continuous monitoring system for the patient with the help of non–invasive(NIV) methodology.