Human Interactive Robot

Abstract

In the present age we have seen a major pandemic, COVID-19, which not only took the lives of millions of ordinary people but also brutally took away many scientists, and medical staff who were working day and night to save the humanity. This pandemic was not even over when a new disease called Monkeypox started spreading like wildfire across the globe. This also spread due to contact with the effected person. The nurse staff is prone to infections, diseases, toxic substances, and radiation but they must check the patients too. One solution was to reduce human contact, but we know one thing that Patients are more probabilistically successful in surviving any disease if the hospital has a high nurse-to-patient ratio. Therefore, we have built a medical robot that can perform repetitive tasks. The robot can navigate the hospital, interact with patients, and measure the patients' vitals. In addition to that, the robot also records the patient's data during the robot-patient interaction along with verifying the patient using a facial recognition algorithm. The whole conversation with the patient can then be accessed by the doctors or nurse staff for monitoring and diagnostic purposes. In case of emergency the robot can also be controlled by the master computer which is always accessible to the concerned medical staff. The robot asks the patient a set of predetermined questions, whose answers are recorded, processed to extract data to fill the EMR, and then refers the patient to the doctor for detailed examination. The interaction is based on supervised learning where the robot understands what the patient is saying, it then breaks the statement into chunks and narrows down the statement to find the best response using artificial neural networks. Various sensors are used to measure the vitals. To navigate the unknown environment, we have used the A-star algorithm. Our robot minimized the pre-processing time of patients before their checkup, reduced the probability of the nurse contracting any infection, and simultaneously increased the nurse-to-patient ratio. This not only modified the daily hospital environment but also instilled a sense of acceptance towards normalizing AI and robotics in daily life activities.