Smart medical chatbot with integrated contactless vital sign monitor

• Main Authors: Zaki, W. M. A. W., Shakhih, M. F. M., Ramlee, M. H., Wahab, A. A.
• Format: Conference or Workshop Item
• Language: English
• Published: 2019
• Subjects: Q Science (General)
• Online Access: http://eprints.utm.my/id/eprint/91432/1/AsnidaAbWahab2019_SmartMedicalChatbot.pdf; http://eprints.utm.my/id/eprint/91432/; http://www.dx.doi.org/10.1088/1742-6596/1372/1/012025
• Institution: Universiti Teknologi Malaysia

Artificial intelligence is one of the important fields in modern technologies to help us strive for better life. Healthcare industries nowadays spend a lot of money researching on how artificial intelligence can help improve their services and give the highest satisfaction to their customers. Most healthcare organisations have a passive relationship to their patients when it comes to communication and this situation is often worsened because of a lack of inter-operability between client and provider. Mobile applications on the other hand have become one of the effective strategies in bridging the interaction between provider and end user. In this study, an automated self-learning system is designed to provide conversational healthcare for personalised proactive experience. This system is developed along with the in cooperation of contactless monitoring device using a vision-based real-time monitoring of vital signs which allow patients to monitor their oxygen level, heart rate and respiration rate. This system is also automatically calibrated across patients, allowing precise measurement using highest probability method and natural language processing. Results obtained from the comparative analysis show a promising result with an error of 1.16 for pulse sensor and 2.917 for ECG which are below the threshold error. This allows user to accurately measure vital signs in a non-obtrusive way, and to provide them with the data required to determine to the right timing for any intervention procedure needed. The developed system would also help to bridge the gap of interoperability between client and medical provider.