IoMT-Based Healthcare Framework for Ambient Assisted Living Using a Convolutional Neural Network

作     者：Waleed T.Al-Sit Nidal A.Al-Dmour Taher M.Ghazal Ghassan F.Issa 

作者机构：Department of Computer EngineeringMutah UniversityAl-KarakJordanHigher Colleges of TechnologyDubaiUAE Department of Computer EngineeringCollege of EngineeringMutah UniversityJordan School of Information TechnologySkyline University CollegeUniversity City SharjahSharjahUAE Center for Cyber SecurityFaculty of Information Science and TechnologyUKM43600BangiSelangorMalaysia 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2023年第74卷第3期

页      面：6867-6878页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Smart healthcare system neural network machine learning 

摘      要：In the age of universal computing,human life is becoming smarter owing to the recent developments in the Internet of Medical Things(IoMT),wearable sensors,and telecommunication innovations,which provide more effective and smarter healthcare *** has the potential to shape the future of clinical research in the healthcare *** sensors,patients,healthcare providers,and caregivers can connect through an IoMT network using software,information,and communication *** assisted living(AAL)allows the incorporation of emerging innovations into the routine life events of *** learning(ML)teaches machines to learn from human experiences and to use computer algorithms to“learninformation directly instead of relying on a *** the sample size accessible for learning increases,the performance of the algorithms *** paper proposes a novel IoMT-enabled smart healthcare framework for AAL to monitor the physical actions of patients using a convolutional neural network(CNN)algorithm for fast analysis,improved decision-making,and enhanced treatment *** simulation results showed that the prediction accuracy of the proposed framework is higher than those of previously published approaches.