Alarm System using Image Processing to Prevent a Patient with Nasogastric Tube Feeding from Removing Tube

Abstract

A removal nasogastric (NG) tube of a patient is a critical problem especially the patients resist swallowing. To solve this problem, the conventional approach using a personal caretaker is a time-consuming and intense focus on the patient’s hands. However, visual technology can decrease the intense focus of a personal caretaker by using image processing to evaluate the patient’s gesture and warn the personal caretaker when the patient acts in a risky pose. This work illustrates the feasible solution to prevent a patient with nasogastric tube feeding on removing tube by applied the face detection using Haar and Fiducial markers which consist of color marker and ArUco marker. An image processing can evaluate the patient’s gesture and warn the personal caretaker when the subject acts the risky pose. A Raspberry Pi 3 Model B and a Camera module with Python and Open CV package are applied to detect and evaluate the warning gestures with 648 measurements. Six detection methods to evaluate and warn when the patient on bed tries to remove a nasal feeding tube were performed and the results were analyzed. The results show that the detection method using ArUco marker is found to be a good candidate for the alarm system preventing nasogastric (NG) tube removal of a patient.