Overlapping gait pattern recognition using regression learning for elderly patient monitoring
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ORIGINAL RESEARCH
Overlapping gait pattern recognition using regression learning for elderly patient monitoring Ahmed E. Youssef1,2 · Yasser Kotb3 · Hassan Fouad4,5 · Ibrahim Mustafa5 Received: 4 July 2020 / Accepted: 27 August 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Gait recognition in elderly patient monitoring is a standard process that employs medical healthcare systems, wearable sensors, motion capturing devices, and Information and Communication Technologies (ICT). The patterns of the patient movement are observed at different time instances for identifying the abnormality in gaits to provide better assistance. In this article, a novel Overlapping Gait Pattern Recognition method based on Regression Learning (RL) is introduced. This method classifies the gait pattern based on the direction of movement and angle of deviation of the patient at the initial stage. The analyses of differentiation are performed using RL for identifying the errors and differences in gait patterns through correlation. The errors are recurrently analyzed through different iterates for approximating the recognition accuracy in a reduced time. The classification of patterns through correlation and conditional analysis of the regression helps identify the errors through intense learning and deviation identification. The proposed method is found to achieve better recognition accuracy, fewer error rates, and smaller recognition delays for different gait patterns. Keywords Conditional analysis · Gait detection · Patient monitoring · Pattern recognition · Regression learning
1 Introduction Today, technology is changing the landscape of the world and leading us to live in a more sophisticated smart environment. The telecommunication devices are now more user friendly and used by a huge population around the world which have reduced the communication gap to a zero level. Therefore, accessibility to information has become pretty easy using Information and Communication Technology (ICT). The emerging of ICT has created a huge impact on * Hassan Fouad [email protected] 1
College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia
2
Department of Computers and Systems Engineering, Faculty of Engineering at Helwan, Helwan University, Cairo, Egypt
3
Computer Science Division, Department of Mathematics, Faculty of Science, Ain Shams University, Abbassia, Cairo, Egypt
4
Applied Medical Science Department, Community College, King Saud University, Riyadh, Saudi Arabia
5
Biomedical Engineering Department, Faculty of Engineering, Helwan University, Cairo, Egypt
healthcare. By providing new and more efficient ways of accessing, communicating, and storing healthcare data, ICTs can help bridge the information between health professionals and the communities they serve using a network of smart medical sensors connected via the Internet, the so called Internet of Medical Things (IoMT). Through the development of databases and other applications, ICTs also provide the capa
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