Skip to content
Research Article Open access CC BY 4.0

Development of an Improved Electronic Patient Health Record Management System with Speech Recognition

Justice O. Emuoyibofarhe, Keji K. Adewuyi, Elizabeth A. Amusan

Journal of Advances in Mathematics and Computer Science · pp. 1–15 · Published 1 Dec 2018

10.9734/JAMCS/2018/44344

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.

Electronic health record health patient speech recognition

Cited by 1

Implementation of Stomatological Hospital Information

Ying Li, Yibo Yang, Ziyi Yang · Advances in Intelligent Systems and Computing · 2020

Article metrics

Real usage data collected on this platform.

11

Page views

0

PDF downloads

0

Outbound clicks

1

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.