scholarly journals Epilepsy Detecting and Halting Mechanism Using Wireless Sensor Networks

2018 ◽  
Vol 22 (1) ◽  
pp. 34
Author(s):  
Sayantani Basu ◽  
Ananda Kumar S. ◽  
Bhuvana Shanmugam

Epilepsy is a condition that affects thousands of people worldwide. In the laboratory setting, it becomes difficult to monitor patients and analyze when the next seizure would recur. Although algorithms have been proposed for deriving when the next seizure is probable, it is difficult to generalize such models for the various types of epilepsy that are occurring every day. A more promising solution is the use of Wireless Sensor Networks (WSNs) that is proposed to simulate small electrodes used in EEG that will be placed on the scalp of the patient as a wearable device along with a portable kit that is capable of monitoring the patient in both ambulatory and resting condition. As much as a detection system is required for epilepsy, a halting mechanism is also needed to prevent such high flow of bio-electrical signals in the brain during seizures. It is estimated that millions of brain cells die during epileptic seizures, which can prove detrimental or even fatal in some cases. In order to overcome this, an IoTbased epilepsy detection and halting system with wireless sensor networks and focal cooling mechanism has been proposed in order to regionally cool the regions of the brain when a seizure is probable or suddenly occurs.

Author(s):  
Asfandyar Khan ◽  
Azween Abdullah ◽  
Nurul Hasan

Wireless sensor networks (WSANs) are increasingly being used and deployed to monitor the surrounding physical environments and detect events of interest. In wireless sensor networks, energy is one of the primary issues and requires the conservation of energy of the sensor nodes, so that network lifetime can be maximized. It is not recommended as a way to transmit or store all data of the sensor nodes for analysis to the end user. The purpose of this “Event Based Detection” Model is to simulate the results in terms of energy savings during field activities like a fire detection system in a remote area or habitat monitoring, and it is also used in security concerned issues. The model is designed to detect events (when occurring) of significant changes and save the data for further processing and transmission. In this way, the amount of transmitted data is reduced, and the network lifetime is increased. The main goal of this model is to meet the needs of critical condition monitoring applications and increase the network lifetime by saving more energy. This is useful where the size of the network increases. Matlab software is used for simulation.


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