• Bhagyesha Manishkumar Pandhi

Epilepsy harms lives of suffering patients and their families. In some cases, we can detect with analysis, predict and avoid it. Epilepsy varies from a brief loss of awareness to longer periods of a loss of sense combined by the muscle stiffening and jerking. General symptoms of epilepsy are unresponsive and uncontrollable movements such as repetitive jerking, loss of consciousness which might include loss of bowel or bladder control and unusual behaviour such as continuous mood swings. Internet of Things (IoT) has been growing rapidly due to recent advancements in communications and sensor technologies. Interfacing an every object together through internet looks very difficult, but within a frame of time Internet of Things will change the it in the data . The enormous data captured by the Internet of Things (IoT) are considered of high business as well as social values and extracting hidden information from raw data, various data mining algorithm can be applied to IoT data. In this paper, We use iot device as data capturing device for EEG signals, which will be further processed with ML algorithm from EEG signals. Preprocessing of EEG signals for noise removal and features extraction are two major issues that have an adverse effect on both anticipation time and true positive prediction rate. To recover it, we have proposed HHT (hilbert-Huang Transform) for preprocessing in less time for signals and min-max classification will be performed for data classification. The parameter to evaluate results of prediction are time and sensitivity.

Epilepsy attack, Ardinouno - ESP8266, Deep neural network

"An AI enabled algorithm for detecting excessive and abnormal brain cell activity for Epilepsy attack ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 4, page no.263-270, April 2020, Available :http://www.jetir.org/papers/JETIR2004529.pdf

"An AI enabled algorithm for detecting excessive and abnormal brain cell activity for Epilepsy attack ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 4, page no. pp263-270, April 2020, Available at : http://www.jetir.org/papers/JETIR2004529.pdf