Improving patient safety, health data accuracy, and remote self-management of health through the establishment of a biometric-based global UHID

Healthcare systems globally continue to face challenges surrounding patient identification. Consequences of misidentification include incomplete and inaccurate electronic patient health records potentially jeopardizing patients\u27 safety, a significant amount of cases of medical fraud because of inadequate identification mechanisms, and difficulties affiliated with the value of remote health self-management application data being aggregated accurately into the user\u27s Electronic Health Record (EHR). We introduce a new technique of user identification in healthcare capable of establishing a global identifier. Our research has developed algorithms capable of establishing a Unique Health Identifier (UHID) based on the user\u27s fingerprint biometric, with the utilization of facial-recognition as a secondary validation step before health records can be accessed. Biometric captures are completed using standard smartphones and Web cameras in a touchless method. We present a series of experiments to demonstrate the formation of an accurate, consistent, and scalable UHID. We hope our solution will aid in the reduction of complexities associated with user misidentification in healthcare resulting in lowering costs, enhancing population health monitoring, and improving patient-safety

Analysis and detection of fingerprint creases

Fingerprint is a biometric trait that is widely used for human identification and verification. Most fingerprint biometric systems make use of certain salient features on the fingerprint, including minutiae points, pores, and singular points, for comparing two fingerprint images. In this work, we explore the possibility of using fingerprint creases for comparing two fingerprints. Creases can be described as white lines or scars on a fingerprint image. Recent studies have determined that some creases are genetically influenced although the origin of creases has not been completely characterized. While no published work exists for crease matching, some studies have explored the problem of automated crease detection. In this thesis, we study the possibility of using creases for fingerprint matching. We also suggest two techniques to automatically extract creases from an input fingerprint image. Finally, we study the correlation between fingerprint creases and age of an individual

Usability analysis of a novel biometric authentication approach for android-based mobile devices

Mobile devices are widely replacing the standard personal computers thanks to their small size and user-friendly use. As a consequence, the amount of information, often confidential, exchanged through these devices is raising. This makes them potential targets of malicious network hackers. The use of simple passwords or PIN are not sufficient to provide a suitable security level for those applications requiring high protection levels on data and services. In this paper a biometric authentication system, as a running Android application, has been developed and implemented on a real mobile device. A system test on real users has been also carried out in order to evaluate the human-machine interaction quality, the recognition accuracy of the proposed technique, and the scheduling latency of the operating system and its degree of acceptance. Several measures, such as system usability, users satisfaction, and tolerable speed for identification, have been carried out in order to evaluate the performance of the proposed approach

Biometrics

Biometrics-Unique and Diverse Applications in Nature, Science, and Technology provides a unique sampling of the diverse ways in which biometrics is integrated into our lives and our technology. From time immemorial, we as humans have been intrigued by, perplexed by, and entertained by observing and analyzing ourselves and the natural world around us. Science and technology have evolved to a point where we can empirically record a measure of a biological or behavioral feature and use it for recognizing patterns, trends, and or discrete phenomena, such as individuals' and this is what biometrics is all about. Understanding some of the ways in which we use biometrics and for what specific purposes is what this book is all about

Biometrics

Biometrics uses methods for unique recognition of humans based upon one or more intrinsic physical or behavioral traits. In computer science, particularly, biometrics is used as a form of identity access management and access control. It is also used to identify individuals in groups that are under surveillance. The book consists of 13 chapters, each focusing on a certain aspect of the problem. The book chapters are divided into three sections: physical biometrics, behavioral biometrics and medical biometrics. The key objective of the book is to provide comprehensive reference and text on human authentication and people identity verification from both physiological, behavioural and other points of view. It aims to publish new insights into current innovations in computer systems and technology for biometrics development and its applications. The book was reviewed by the editor Dr. Jucheng Yang, and many of the guest editors, such as Dr. Girija Chetty, Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park, Dr. Sook Yoon and so on, who also made a significant contribution to the book