This paper recalls the essential concern about people with disabled limbs who have difficulties moving around by themselves. Furthermore, with the COVID-19’s impact, hygiene issues have been raised and the way people use wheelchairs should be reconsidered. As eyes tell more stories than anything, we can use them to detect symptoms of sickness and understand the hidden words in people's minds. Most current commercial wheelchairs will either need the user's arm or a manual remote, which still cannot solve the aforementioned concerns. The research aims to analyze and understand human behavior from the eyes - the windows to the soul, and to create a safer wheelchair concept in the future. The novelty of this research is to apply eye tracking techniques with psychological knowledge to understand the users’ thoughts, intentions, feelings and from that, translate the data into action to support the motion. Eye tracking is capturing and analyzing the eye movements with the camera that records the patterns and positions of 3 key parts of an eye: pupil, iris and sclera. Each component’s size can shrink or expand according to the level of emotion, alertness, attentiveness and focus. Once we understand the patterns and their meanings, a deep neural network model will collect different classified samples and start learning to produce output for different variations. This outcome can further help us control the embedded system to automatically drive the motor without human interference and execute additional functions like warning messages when a sleepy condition or a patient's critical health condition is detected. Consequently, flexibility in movement can be achieved and additional assistance from helpers is no longer required. Hence, the article has depicted a way to effectively support disabled individuals without a need for additional cost, tools and ensure the performance simultaneously.