ADOPTION OF AN INTEGRATED NEAR FIELD COMMUNICATION AND NATURAL LANGUAGE PROCESSING SYSTEM TOWARD IMPROVEMENT OF TELEHEALTH SOLUTIONS

Abstract

Telehealth is the usage of digital medical data and telecommunication technologies to aid long-distance clinical healthcare. Proper maintenance of a patient’s medical record has been a hindrance toward the growth of Telehealth services. The patient’s data, particularly emergency data, must be available to medical personnel within a short time frame and independent of potential interruption of network connections. In this paper, we propose a Near Field Communication (NFC) wristband that provides access to the medical details, history and contact details of a patient. By this, the doctor or the paramedical officer can provide the patient with the best treatment within a short period of time. This system comes in handy even if the patient is unconscious/unable to answer. The doctor or the paramedical officer can quickly draft a patient’s report and send it to the hospital. The proposed framework consists of the following four stages: (i) obtaining emergency medical data with the help of NFC chips, (ii) converting medical report into digital text using Optical Character Recognition (OCR), (iii) structuring the narrative medical text into organized data using NLP and (iv) comparative analysis of the selected content. An image database with 1200 medical case histories has been utilized for the algorithm development and validation. The OCR algorithms for converting images to text produced more than 98% on average and NLP algorithm produced around 94.1% accuracy. Overall, the performance of the system from NFC reader till analysis of the specific field is more than 95%. The developed OCR and NLP integrated software helps the doctor or the health officer to immediately convert it into text format and the unstructured text is quickly organized into the respective fields.