{"title":"Patient Identification using Facial Recognition","authors":"V. Verma, Vanika Kansal, P. Bhatnagar","doi":"10.1109/ICFCR50903.2020.9250002","DOIUrl":null,"url":null,"abstract":"The medical history of patients and previous meetings to a doctor have been traditionally recorded and maintained using paper and pen. This research is done with an aim to throw some light on the field of Computer Vision that can potentially revolutionise the way that prescriptions are given to patients since ages. In this paper, an implementable idea of using the advanced Computer Vision Technology to eliminate printed prescriptions and physical components like RFID, Record Files has been proposed. The results of having a Universal Medical Face Identification for every patient have been properly showcased that take several factors into consideration like reducing the inefficiency, amount of time taken at reception and efforts of medical staff in recognising a patient and drawing out subtleties of the patient's medical history, previous visits to the specialist, and prescriptions. A database linked to the patient's face image can be deployed on a secure platform that can be updated from time to time and will be universally considered as the basis of the identity of patients available to the doctors at all certified medical centres for studying and taking immediate action. Facial recognition can be utilized in hospitals for staff and patient tracking efficiently and practically faster than the current record based approach. Finally, the comparison of wait time and technical challenges of current methods, implementation and privacy are highlighted.","PeriodicalId":165947,"journal":{"name":"2020 International Conference on Futuristic Technologies in Control Systems & Renewable Energy (ICFCR)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Futuristic Technologies in Control Systems & Renewable Energy (ICFCR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFCR50903.2020.9250002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The medical history of patients and previous meetings to a doctor have been traditionally recorded and maintained using paper and pen. This research is done with an aim to throw some light on the field of Computer Vision that can potentially revolutionise the way that prescriptions are given to patients since ages. In this paper, an implementable idea of using the advanced Computer Vision Technology to eliminate printed prescriptions and physical components like RFID, Record Files has been proposed. The results of having a Universal Medical Face Identification for every patient have been properly showcased that take several factors into consideration like reducing the inefficiency, amount of time taken at reception and efforts of medical staff in recognising a patient and drawing out subtleties of the patient's medical history, previous visits to the specialist, and prescriptions. A database linked to the patient's face image can be deployed on a secure platform that can be updated from time to time and will be universally considered as the basis of the identity of patients available to the doctors at all certified medical centres for studying and taking immediate action. Facial recognition can be utilized in hospitals for staff and patient tracking efficiently and practically faster than the current record based approach. Finally, the comparison of wait time and technical challenges of current methods, implementation and privacy are highlighted.