Detection of Brain Tumor Using Internet of Things

Abstract

The amount of brain tumor patients are increasing indescribably in the recent years and it has become a dangerous problem. For both men and women, brain tumor placed in 10th position of the leading cause of death. If it is possible to detect any disease before it started to damage, the chance of recovery from diseases gets the increase. Previous state-of-the-art techniques based on magnetic resonance images (MRI), provide fast and robust detection of tumor on the brain. But due to use of MRI images the complexity of these techniques become high. All these existing techniques classify the MRI images and detect the brain tumor, which is computationally expensive. We have proposed a stochastic method for automatic detection of brain tumor using Internet of Things (IoT). The proficiency of the method is scrumptious, because it measures the probability of brain tumor from our daily activities. In our experiment, we have used a portable wrist wearable device and two extra sensors, which can track our daily activities. Some common symptoms of brain tumor are used here to detect the brain tumor. We have proposed some equations, which can easily measure these symptoms from our daily activities. Experimental result for brain tumor patients‘ group and normal persons‘ group show the ability of the proposed technique in automatic detection of brain tumor. In this paper, we show the effectiveness of our method in automatic detection of brain tumor is demonstrated and it produces a better accuracy with the comparison to previous state-of-the-art brain tumor detection techniques.