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Where is Maths & Engineering research heading? 2 author insights

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Hindawi Article of the Year merit image next to 'mathematics and engineering' text

We highlight two winning research papers in mathematics and engineering, featuring an impactful study on a low-energy fall detection and warning system for the elderly in nursing homes, and another on medical data clustering.


Article of the Year showcased some incredible research. Here, we celebrate two of our winning mathematics and engineering authors, with work covering a new low-energy fall detection and warning system for elderly people, and medical data clustering. Plus, authors Dr. Jo Verhaevert and Dr. A Jaya Mabel Rani share insights into their work, highlighting challenges, opportunities, and where they see their fields heading next. 

 

  1. Jump to the winning article from Journal of Sensors

  1. Jump to the winning article from Advances in Fuzzy Systems

 
1. ‘Bluetooth-Low-Energy-Based Fall Detection and Warning System for Elderly People in Nursing Homes’ by Nick De Raeve, Jo Verhaevert, et. al 

This study published in Journal of Sensors, was selected as an Article of the Year by the Chief Editor. The paper was chosen due to presenting research that can assist in preventing falls among senior citizens and having great impact. 

 

What is the article about? 

This article addresses the rising incidence of fall accidents among the elderly due to a growing aging population, presenting a novel Bluetooth low energy (BLE) based fall detection and warning system for nursing homes. The findings include: 

  • The introduction of a BLE-based wearable fall detection sensor for the elderly, ensuring good room coverage with low energy consumption. 

  • A proposed algorithm exhibiting a high accuracy score, meeting design requirements for reliable fall detection and comparable performance to convolutional neural networks. 

  • The presentation of a wearable device that achieves reliable fall detection without false alerts, incorporating an orientation confirmation system, and operating autonomously for 100 days on a standard coin-cell battery. 

Celebrating the author 

Dr. Jo Verhaevert

Dr. Jo Verhaevert is an Associate Professor at the Faculty of Engineering Sciences and Architecture, Ghent University. He has published over 80 papers, and currently conducts research in Computer Communications (Networks), Algorithms, and Communication Engineering. 

We asked Dr. Jo Vernhaevert a couple of questions about the article. 

What was the most interesting, challenging, or exciting aspect of working on this paper? 
“We proposed a novel fall detection and warning system for nursing homes, relying on Bluetooth Low Energy wireless communication. This paper focuses on the hardware design of a fall-acceleration sensing wearable for the elderly and on a novel algorithm for real-time filtering of the measurement data as well as on a strategy to confirm the detected fall events, based on changes in the person’s orientation.” 

 
What, in your opinion, is the next big opportunity or challenge in your field? 
“Vital sign monitoring” 

 

Read more about the novel fall detection and warning system in the full article>> 

Discover the other selected engineering articles >> 

 

2. ‘Clustering by Hybrid K-Means-Based Rider Sunflower Optimization Algorithm for Medical Data' by A. Jaya Mabel Rani and A. Pravin 

This study published in Advances in Fuzzy Systems, was selected as an Article of the Year by the Chief Editor, because of its significance and interest within the research community, and having the potential to have real-world impact with increased visibility. 

What is the article about? 

The research introduces a hybrid optimization technique, the K-means-based rider sunflower optimization (RSFO) algorithm, for medical data clustering. The proposed approach involves data preprocessing to clean input medical data, selection of important features using the Tversky index with holoentropy, and clustering through the hybrid RSFO algorithm.  
The findings include: 

  • The proposed clustering algorithm effectively analyzes the risk factor of heart disease by producing an optimal centroid-based clustering solution for heart disease-based medical data. 

  •  The achieved performance of the proposed K-means-based rider sunflower optimization (RSFO) algorithm is noteworthy, with an accuracy of 90.0236%.  

  •  The hybrid clustering algorithm, combining rider optimization and sunflower optimization techniques, demonstrates advantages such as protecting against premature convergence. 

 

Celebrating the author 

Dr. A Jaya Mabel Rani is an Assistant Professor in the Department of Computer Science and Engineering at Saveetha School of Engineering. Her research interests include Artificial Intelligence, Data Mining, and Machine Learning. 

We asked Dr. A Jaya Mabel Rani a couple of questions about the article. 

What was the most interesting, challenging, or exciting aspect of working on this paper? 
“Clustering of medical data based on hybrid clustering algorithm” 
 
What, in your opinion, is the next big opportunity or challenge in your field? 
“To work with big data” 

 

Read more about using K-Means clustering algorithm to cluster the medical data by using an optimum centroid in the full article>> 

Discover the other selected mathematics articles >> 

 


This blog post is distributed under the Creative Commons Attribution License (CC-BY). Illustration by David Jury.

Article of the Year Award: Impactful research contributions of 2022, as selected by our Chief Editors. Discover the winning articles.