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Smart Healthcare System Based on Cloud-Internet of Things and Deep Learning

Benzhen Guo, Yanli Ma, Jingjing Yang, Zhihui Wang, Enas Abdulhay
2021 Journal of Healthcare Engineering  
A deep learning model based on the convolution neural network (CNN) is constructed, in which six volunteers are selected to participate in the experiment, and their health data are marked by private doctors  ...  Smart phones are adopted as gateway devices to achieve data standardization and preprocess to generate health gray-scale map uploaded to the cloud server.  ...  With the popularity of smart phones, smart bracelets, and other devices, a variety of sensors can monitor health indicators timely and accurately [3] [4] [5] .  ... 
doi:10.1155/2021/4109102 pmid:34257851 pmcid:PMC8260290 fatcat:wt7jjifgurcw5ozivn7e4e2v2a

Deep learning-based ambient assisted living for self-management of cardiovascular conditions

Maria Ahmed Qureshi, Kashif Naseer Qureshi, Gwanggil Jeon, Francesco Piccialli
2021 Neural computing & applications (Print)  
For each theme, a detailed investigation shows (1) how these new technologies are nowadays integrated into diagnostic systems and (2) how new technologies like IoT sensors, cloud models, machine and deep  ...  The paper is divided into four main themes, including self-monitoring wearable systems, ambient assisted living in aged populations, clinician management systems and deep learning-based systems for cardiovascular  ...  2 [47]/ 2016 Wearable tracking system Personal computers, mobile phones and now smart watches Real data- based system Steps, eat, sleep data Provide big-data analytics using daily  ... 
doi:10.1007/s00521-020-05678-w fatcat:fkabjm33xza2ncgq6ecu2qifaq

Analyzing the Patient Behavior for Improving the Medical Treatment Using Smart Healthcare and IoT-Based Deep Belief Network

Rasha M. K. Mohamed, Osama R. Shahin, Nadir O. Hamed, Heba Y. Zahran, Magda H. Abdellattif, Mohamed Elhoseny
2022 Journal of Healthcare Engineering  
The deep belief neural network evaluates the patient's particulars from health data in order to determine the patient's exact health state.  ...  The proposed system comprises of a variety of medical equipment, such as mobile-based apps and sensors, which is useful in collecting and monitoring the medical information and health data of patient and  ...  )" at King Khalid University, Saudi Arabia, for funding this work under the grant number KKU/RCAMS/G013-21. e authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of  ... 
doi:10.1155/2022/6389069 pmid:35310183 pmcid:PMC8930207 fatcat:5fwatmrodndobbehjjcob6i6ki

A Self-Learning Autonomous and Intelligent System for the Reduction of Medication Errors in Home Treatments [chapter]

Rosamaria Donnici, Antonio Coronato, Muddasar Naeem
2021 Ambient Intelligence and Smart Environments  
Such patients can, nowadays, be supported by Autonomous and Intelligent Monitoring Systems (AIMSs) that may get new levels of functionalities thanks to technologies like Reinforcement Learning, Deep Learning  ...  and Internet of Things.  ...  A distributed fuzzy system able to infer in real-time critical situations by analysing data gathered from user's smart-phones about the environment and the individual is presented in [38] .  ... 
doi:10.3233/aise210093 fatcat:cf75t4srsfb57hqixgcxswpaqy

HAR-Net:Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition [article]

Mingtao Dong, Jindong Han
2018 arXiv   pre-print
The study used the data collected by gyroscopes and acceleration sensors in android smart phones. The raw sensor data was put into the HAR-Net proposed.  ...  One of the most appealing as well as challenging applications is the Human Activity Recognition (HAR) utilizing smart phones.  ...  In recent years, deep learning is rising because of the big data.  ... 
arXiv:1810.10929v1 fatcat:gt2erzxob5hizdjeldnbxxf5cq

An overview of GeoAI applications in health and healthcare

Maged N. Kamel Boulos, Guochao Peng, Trang VoPham
2019 International Journal of Health Geographics  
Internet of Things-powered smart healthy cities.  ...  There is an emerging role for GeoAI in health and healthcare, as location is an integral part of both population and individual health.  ...  For example, personal sensing collects data using the sensors embedded in mobile phones as well as through wearables such as Fitbits [34] .  ... 
doi:10.1186/s12942-019-0171-2 pmid:31043176 pmcid:PMC6495523 fatcat:sfrleigt6rhnfatwmvhuchjtbi

Design of LSTM-RNN on a Sensor Based HAR using Android Phones

2020 International journal of recent technology and engineering  
Activity Recognition (AR) is monitoring the liveliness of a person by using smart phone.  ...  This paper focuses for Activity Recognition (AR) based on smart phone by analyzing the performance of various Deep Learning (DL) approach using in-built gyroscope and accelerometers.  ...   Abstract: Activity Recognition (AR) is monitoring the liveliness of a person by using smart phone.  ... 
doi:10.35940/ijrte.e6821.018520 fatcat:hyosmstbsrgqzdkss7q2wqegsq

Health Monitoring using Edge Cognitive Computing Based Smart Health Care

Remote viewing of the data provided to the doctor will able to monitor a patients health progress aboard from hospital places. The Edge-Cognitive- Computing-based (ECC-based) smart healthcare system.  ...  The first and most important section in this process is to detecting the patient current health status using this sensors. second important thing is sending data to cloud storage and the last section is  ...  In that data cognitive engine the explicit data allude to analyzed and data analysis and processing by using data cognition engine. e.g at a same time machine learning and deep learning, the external data  ... 
doi:10.35940/ijitee.l2719.119119 fatcat:usnqrontg5cjtcqil27dpxi6vy

MEMO Box: Health Assistant for Depression with Medicine Carrier and Exercise Adjustment Driven by Edge Computing

Lixia Luan, Wenjing Xiao, Kai Hwang, M. Shamim Hossain, Ghulam Muhammad, Ahmed Ghoneim
2020 IEEE Access  
Specifically, the MEMO box system is composed of electronic medicine box and smart applications on mobile device, and electronic medicine box can collect the multi-mode data of patients, including their  ...  medication behaviors, daily activities, physical exercise data, and so on, which provide data basis for the health assistant.  ...  This research is also supported by the Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS).  ... 
doi:10.1109/access.2020.3031725 fatcat:pvjskhcvnfdfbhlicxzf2rs7ta

Big Sensed Data Meets Deep Learning for Smarter Health Care in Smart Cities

Alex Obinikpo, Burak Kantarci
2017 Journal of Sensor and Actuator Networks  
In this article, we review deep learning techniques that can be applied to sensed data to improve prediction and decision making in smart health services.  ...  With the advent of the Internet of Things (IoT) concept and its integration with the smart city sensing, smart connected health systems have appeared as integral components of the smart city services.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/jsan6040026 fatcat:u4jypthhczbtdlubg77mvbocei

Deep Learning for Walking Behaviour Detection in Elderly People Using Smart Footwear

Rocío Aznar-Gimeno, Gorka Labata-Lezaun, Ana Adell-Lamora, David Abadía-Gallego, Rafael del-Hoyo-Alonso, Carlos González-Muñoz
2021 Entropy  
For the detection of these events, a hierarchical structure of cascading binary models is designed and applied using artificial neural network (ANN) algorithms and deep learning techniques.  ...  We propose a scalable, easily modulated and live assistive technology system, based on a comfortable smart footwear capable of detecting walking behaviour, in order to prevent possible health problems  ...  the ones directly involved in the development of the shoe prototypes:  ... 
doi:10.3390/e23060777 pmid:34205259 pmcid:PMC8235668 fatcat:3qsfff7hx5hbjazumh4cgnyu2y

SIMING ZHENG - Previous Relevant Research-Multimodal Learning Model based Decision-support System with Data Fusion Analysis for Health Wearable Sensors

Siming Zheng
2020 Figshare  
My Previous Relevant Research-Multimodal Learning Model based Decision-support System with Data Fusion Analysis for Health Wearable Sensors (2019-12).  ...  Table 1 : 1 Smart wearable devices are categorized by functionality.  ...  Gradient Tree Boosting is ideal for learning and predicting raw data collected by various sensors.  ... 
doi:10.6084/m9.figshare.12059562 fatcat:hfgjtjjn35ar3i5zbdljdibxcu

Research Proposal - Machine Learning based Decision-support System with Data Fusion Analysis for Health Wearable Sensors

Siming Zheng
2020 Figshare  
This is the Research Proposal for the application of Ph.D postion.  ...  Table 1 : 1 Smart wearable devices are categorized by functionality.  ...  Gradient Tree Boosting is ideal for learning and predicting raw data collected by various sensors.  ... 
doi:10.6084/m9.figshare.12058290.v1 fatcat:pifiem6i3jdkvlahyg2oczkvxu

Wearable IoT enabled real-time health monitoring system

Jie Wan, Munassar A. A. H. Al-awlaqi, MingSong Li, Michael O'Grady, Xiang Gu, Jin Wang, Ning Cao
2018 EURASIP Journal on Wireless Communications and Networking  
of the smart phone.  ...  Secondly, the majority of existing wearable health monitoring systems requisite a smart phone as data processing, visualisation, and transmission gateway, which will indeed impact the normal daily use  ...  Availability of data and materials The datasets supporting the conclusions of this article are included within this article.  ... 
doi:10.1186/s13638-018-1308-x fatcat:bt4vxnvc4zesziu3rmcy5qzx24

A Review Paper on Health Monitoring Smart Mirror

Dikshita Badwaik, Ekta Game, Pooja Zade, Pranali Kathote, Gayatri Bhoyar
2022 International Journal for Research in Applied Science and Engineering Technology  
Keywords: Internet of Things (IoT), Smart Mirror, Arduino.  ...  Abstract: A variety of environmental factors can obstruct human health and well-being.  ...  The physiological data is collected by the biomedical sensors in the mirror and communicated to medical personnel so they can learn more about the patient's health.  ... 
doi:10.22214/ijraset.2022.41267 fatcat:6dioic4jfjdgvk7cbc6ooetkru
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