Development of an Improved Electronic Patient Health Record Management System with Speech Recognition
Justice O. Emuoyibofarhe
Department of Computer Science and Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria and Center for Excellence in Mobile e – Services, University of Zululand, South Africa and Hasso Plattner Institute, University of Potsdam, Germany.
Keji K. Adewuyi
Department of Computer Science and Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria.
Elizabeth A. Amusan *
Department of Computer Science and Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Electronic Patient Health Record (EPHR) is an individual official patient health document shared among multiple facilities and agencies. However, most existing EPHR systems are dependent on keyboard and mouse only and do not support human speech interaction. This study, therefore, developed an improved EPHR management system, characterized by human speech interaction. Oral interview was conducted, the information acquired was used to design the improved system whose components are speech recognition architecture, speech recognition algorithm and voice command algorithm. The improved EPHR system database was developed using Microsoft SQL server 2016, Legacy ActiveX Data Objects (ADO.net) with Object Relational Mapping. Microsoft speech library was used for the speech recognition module. The improved EPHR system was implemented using C# programming language (.NET 4.5) and Visual Studio 2017. The performance of the improved EPHR system with speech recognition was evaluated with 50, 100, 150 and 200 words using correctness, accuracy and Word Error Rate (WER). The performance of the improved EPHR system yielded correctness, accuracy and WER values of (96, 96 and 4.0%), (96, 95 and 4.0%), (95, 95 and 5.0%) and (93, 94 and 6.0%) for 50, 100, 150 and 200 words respectively. This study developed an improved EPHR management system with speech recognition and voice command which can improve user interactivity and help in disabilities or hands-free environment.
Keywords: Electronic health record, health, patient, speech recognition