AutiLife: A Healthcare Monitoring System for Autism Center in 5G Cellular Network using Machine Learning Approach

M. Mamun, Afroza Rahman, M. A. Khaleque, Md. Abdul Hamid, M. Mridha
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引用次数: 7

Abstract

Autism is a complex and developmental neurobehavioral disorder which indicates difficulties with communication skills and social interactions. Because of various types of symptoms, this condition is also refers to as autism spectrum disorder (ASD). There are many autism centers to help and facilitate children with autism. To make an autism center automatic and capable of responsive in real time, the next generation of cellular network, i.e. 5G can play a vital role. We have found minor contribution towards healthcare monitoring system for autism centers in a network that offers ultra-reliable and low-latency communication (uRLLC), higher data rates and massive connectivity of devices in Internet of Things (IoT) and Internet of Medical things (IoMT). Therefore, we have proposed "AutiLife"- an impeccable healthcare monitoring system for autism centers in 5G cellular network using Machine Learning algorithm, Support Vector Machine (SVM). Our proposed system model will collect health related data (Blood Pressure, Heart Rate, Body Temperature, Body Motion, Speech Signals) using various sensors and devices from autistic children. Then using ML algorithm the system will accomplish some course of actions and alert the controllers and nearby hospitals if any health falling issues are found. We resolutely believe, our proposed system "AutiLife" may handle any emergency issues for example epilepsy, heart stroke, heart attack, anxiety, hysteria that can occur on any sudden moment in an autism center and may save inestimable life of children with autism.
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AutiLife:基于机器学习方法的5G蜂窝网络自闭症中心医疗监测系统
自闭症是一种复杂的发育性神经行为障碍,表现为沟通技巧和社会互动方面的困难。由于各种类型的症状,这种情况也被称为自闭症谱系障碍(ASD)。有许多自闭症中心帮助和促进自闭症儿童。为了使自闭症中心实现自动化并能够实时响应,下一代蜂窝网络,即5G可以发挥至关重要的作用。我们发现,在一个提供超可靠和低延迟通信(uRLLC)、更高数据速率和物联网(IoT)和医疗物联网(IoMT)中设备的大规模连接的网络中,自闭症中心的医疗监测系统有很小的贡献。因此,我们提出了“AutiLife”——一个在5G蜂窝网络中使用机器学习算法,支持向量机(SVM)的自闭症中心的完美医疗监控系统。我们提出的系统模型将使用来自自闭症儿童的各种传感器和设备收集健康相关数据(血压、心率、体温、身体运动、语音信号)。然后,使用ML算法,系统将完成一些动作,并在发现任何健康下降问题时向控制器和附近的医院发出警报。我们坚信,我们提出的“AutiLife”系统可以处理任何紧急问题,例如癫痫,心脏病,心脏病发作,焦虑,歇斯底里,可能发生在自闭症中心的任何时刻,并可能挽救自闭症儿童的宝贵生命。
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