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IJSTR >> Volume 9 - Issue 6, June 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Different Attack Patterns For Deep Brain Implants By Using Cnn

[Full Text]

 

AUTHOR(S)

Aarthi.R, Akash.R, Anish.V

 

KEYWORDS

Convolutional Neural Network, Deep Brain Stimulators, Deep Learning, Implantable Medical Devices, Machine Learning, Neural Network, Security.

 

ABSTRACT

Deep Brain Stimulation (DBS) is a neuro surgical procedure that is a neuro stimulator (brain pacemaker) is placed which can send the electrical impulses, through implanted electrodes, to specific targets of brain for the treatment of neurological disorders such as Parkinson, movement disorder, epilepsy, and psychiatric disorders. The device must be fully secured since it directly affects the mental, emotional and physical state of human bodies which may lead to patient’s death. The adversary can impair the motor functions, or modify the emotional pattern of patient by stimulating fake signals by Deep Brain Stimulators (DBSs). This project uses deep learning methodology to predict different attack stimulations in DBSs. This proposed work uses a long short-term memory, a type of Convolutional Neural Network (CNN) which is a class of deep neural network commonly applied for visual imaginary for forecasting and predicting rest tremor velocity (characteristic used to evaluate intensity of neurological disorder) which helps in diagnosing fake versus original stimulations. This methodology was used to detect different attack patterns efficiently.

 

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