This paper presents an integrated and easy methodology for bibliometric analysis. The proposed methodology is evaluated on recent research activities to highlight the role of the Internet of Things in healthcare applications. Different tools are used for bibliometric studies to explore the breadth and depth of different research areas. However, these Methods consider only the Web of Science or Scopus data for bibliometric analysis. Furthermore, bibliometric analysis has not been fully utilised to examine the capabilities of the Internet of Things for medical devices and their applications. There is a need for an easy methodology to use for a single integrated analysis of data from many sources rather than just the Web of Science or Scopus. A few bibliometric studies merge the Web of Science and Scopus to conduct a single integrated piece of research. This paper presents a methodology that could be used for a single bibliometric analysis across multiple databases. Three freely available tools, Excel, Perish or Publish and the R package Bibliometrix, are used for the purpose. The proposed bibliometric methodology is evaluated for studies related to the Internet of Medical Things (IoMT) and its applications in healthcare settings. An inclusion/exclusion criterion is developed to explore relevant studies from the seven largest databases, including Scopus, Web of Science, IEEE, ACM digital library, PubMed, Science Direct and Google Scholar. The study focuses on factors such as the number of publications, citations per paper, collaborative research output, h-Index, primary research and healthcare application areas. Data for this study are collected from the seven largest academic databases for 2012 to 2022 related to IoMT and their applications in healthcare. The bibliometric data analysis generated different research themes within IoMT technologies and their applications in healthcare research. The study has also identified significant research areas in this field. The leading research countries and their contributions are another output from the data analysis. Finally, future research directions are proposed for researchers to explore this area in further detail.

Purpose: This study aims to evaluate the usability of the augmented reality-based Evoke Education System (EES) to improve service operations in educational settings. The EES uses an animated character (Moe) to interact with children in a classroom by reproducing their teacher's movements and speech.Design/methodology/approach: This study uses a quantitative approach for the system usability evaluation. The ESS was evaluated by 71 children aged 6–8 years old, from two primary schools. After interacting with the EES, they completed a system usability questionnaire and participated in a knowledge acquisition test.Findings: The knowledge acquisition test undertaken on the initial day showed statistically significant improvements for children taught with the EES, compared to children taught through traditional teaching approaches. However, the retest nine days later was not statistically significant (as only one school participated) due to low power. This study used confirmatory factor analysis (CFA), resulting in the identification of five essential factors (likeability, interactiveness, retention, effectiveness/attractiveness and satisfaction) that contribute to the EES's usability. The comparison with existing literature shows that these factors are consistent with the definition of system usability provided by the International Organization for Standardization and current academic literature in this field.Research limitations/implications: The findings presented in this study are based on the data from only two schools. The research can be extended by involving children from a greater number of schools. Mixed methods and qualitative research approaches can be used for future research in this area to generalise the results.Originality/value: This study proposes an innovative augmented reality-based education system to help teachers deliver their key messages to the children in a fun way that can potentially increase their knowledge retention.

Human skills are a critical factor in the success or failure of a digital project. Limited studies have been conducted to identify the industry demand for skills of scrum roles (product owner, scrum master, web developer) and levels (entry, associate, mid-senior). The evaluation of skills over time benefits both decision-makers and associated team members, which leads to successful project completions. The aim of this research is to improve decision making concerning the level-specific skills of selected scrum roles for digital projects. The study identifies major and minor skills, patterns, and relationships between levels, and formulates the mathematical equations as the most important inputs to the skill-driven model’s implementation and evaluation. Both qualitative and quantitative research methods were used to analyse 900 surveyed job advertisements published on LinkedIn in Europe. Descriptive analysis was used to analyse quantitative data while the deductive approach was followed with thematic analysis. There are required skill sets for each level of roles, level-specific skills, industry-demanded skills, and formulas related to the initial and individual skill ratings that are investigated. A new mechanism for evaluation is introduced based on “the time spent with skills”. As a result, the proposed model is implemented by feeding research findings into the Mendix programming platform. The skill-driven model is a decision-support solution in software project management to evaluate skills which assist in assigning the right person to the right digital project. Further investigation on different job portals can help to improve the accuracy of industry standards and reduce the lack of progression skills by overcoming limitations identified in this paper.

This paper gives insights into recent research developments in the field of digital solutions for people with aphasia and tries to analyse its impact on their rehabilitation. A bibliometric research approach is used for data collection. Relevant studies were extracted from seven major academic databases from years 2000 to 2019 inclusive. The systematic process resulted in 986 studies. The average growth in this field is 4%, which is less compared to other research areas. However, the average citations per paper is 7.27, which represents a medium level of publication quality. Scopus and Web of Science are leading databases for the number of studies (379 and 264) and quality of publications (P-Index: 49.26 and 32.85), respectively. The USA, with 42% of publications, leads this research field, followed by the UK with 15%. Both countries have national aphasia strategies in place through charities (not government level strategies), which potentially contributed to their research leadership. The results show that recent advances in digital solutions have the potential to support people with aphasia. However, further work is needed at both academic and government levels to deliver more research contributions and funding for the rehabilitation of people with aphasia.