BCI provisions humans beings to control various devices with the help of brain waves. It is quite useful for the people who are totally paralysed from neuromuscular diseases such as spinal cord injury, brain stem stoke. BCI permits a muscular free channel for conveying the user intent into action which helps the people with motor disabilities to control their surroundings. Various non-invasive technologies like electroencephalogram (EEG), magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), etc. are available for capturing the brain signal. In this article, various non-invasive BCI devices are analysed and nature of signals captured by it are reported. We also explore the use of signals for diseases diagnosis, their features and availability of those devices in the market.

Agriculture is the backbone of any developing or developed country that makes any living to survive. To make food available throughout the year, it is necessary to know about agriculture and the work and strategies involved. Hence, agricultural courses have to be introduced to higher education students. Additionally, agriculture-related methods are available in many higher education institutions for longer. However, students and teachers will face difficulties in real-time practical classes during certain challenging circumstances. These situations require the teacher to utilize trending technologies to improve the teaching and learning process and to make it more manageable. In this study, for this process, a novel neural network-based recognition algorithm (NN-RA) is implemented that works similarly to a backpropagation neural network (BP-NN) to provide a practical agriculture course. The proposed BP-NN is compared with the existing NN-RA, I-SC, and I-VDT algorithms based on the data transfer and signal-to-noise ratio. From the results, it can be observed that the proposed BP-NN attains a higher accuracy in data transfer of 99%.

The term “Heart disease” refers to different types of heart conditions. Even when there is slow flow of blood in the heart it can cause a heart attack. There are many such aspects that can raise the risk for heart disease called risk factors. Lots of researchers have been discovering new technologies to predict the disease early before it’s too late for helping people suffering from heart disease. In our project we are helping out the users to predict their risk of heart attack by using the UCI Repository Heart Disease dataset that is used to train the model.

Many people around the world are affected by motor function disabilities. These people cannot communicate with others as they have met with accidents or they are under some trauma. It is nearly impossible for such paralyzed people to communicate with others. This system permits various physically handicapped patients to convert their intent to text using their eye-blink in order to use a computing system motor capability. However, people under paralysis can use their eyes. A natural motion of the eye is an eye-blink. This eye-blink can be efficiently used to communicate information.