EOG Based Text and Voice Controlled Remote Interpreter for Quadriplegic Patients

Abstract

Electrooculography is considered as one of the significant electro-physiological signals. These signals carry data of eye movements which can be employed in human-computer interface (HCL) as a control signal. This project focuses on creating a text and voice-based interpreter for quadriplegic patients using electrooculography (EOG) signals. EOG is a technique that measures the electrical activity of the eye muscles responsible for eye movements and can be used to track changes in eye location to reveal information about human eye activities. The EOG signal is commonly used in human-computer interface (HCI) systems as an alternative input for patients suffering from quadriplegia, ALS, and locked-in syndrome. The BioAmp EXG Pill Sensor is used to acquire EOG signals of left and right eye movement, as well as up and down eye movement. The signals are processed using an ESP32 microcontroller and Arduino IDE, and an algorithm is created to analyze the observed ranges and generate text and voice-based outputs. The accuracy of the system was tested by asking 10 healthy participants to perform each of the four types of motions ten times, and the results showed an overall accuracy of 81.04%. The system involves detecting EOG signals using sensors that are placed around the patient's eyes, and the text-based output is displayed on an LCD screen, while the voice-based output is played on an MP3 player. The output is then displayed on an application enabling communication with the patient remotely, potentially improving the quality of care and increasing the patient’s sense of security. Future developments could include increasing the degrees of motion and addition of an eye-blink sensor for more convenient user experience. This project provides a valuable solution for quadriplegic patients, enabling them to communicate effectively and empowering them with a sense of independence. However, further research and testing are needed to fully evaluate the efficacy of the system on actual quadriplegic patients.