Motor Neuron Disease is a medical condition where the motor neurons of the patient are paralyzed, due to which none of the voluntary actions can be performed. The main problem faced by these patients is that they cannot communicate. Thus in order to help these patients to communicate, this project develops an algorithm for the real time video Oculography system. The camera focuses on the eye of the patient and records the eye blink.
The algorithm is written for the same and to convert eye blink to speech. The algorithm for converting eye blink to sentences is implemented in python software. The code is then fed to a Raspberry pi 3 microprocessor. The eye blink is detected using the web cam and the respective output is obtained as speech. Thus, the patient is able to communicate his basic needs with the outside world. The reason for using Raspberry Pi 3 is because of the WiFi /Bluetooth facility, CPU/GPU pair. This enables the implementation of the wireless Bluetooth speaker which can be placed anywhere around the patient. The caretaker need not be with the patient throughout. The use of currently trending components and coding makes it portable and user friendly.
The future scope of this prototype is to implement in IOT. Along with the speech output, the operation will be performed in real time. This reduces the effort of the caretaker to assist the patient as he can perform the activities that he intends to on his own.