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Smart Healthcare System Based on Cloud-Internet of Things and Deep Learning
2021
Journal of Healthcare Engineering
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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
2021
Neural computing & applications (Print)
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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
2022
Journal of Healthcare Engineering
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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]
2021
Ambient Intelligence and Smart Environments
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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]
2018
arXiv
pre-print
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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
2019
International Journal of Health Geographics
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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
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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
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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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
2020
IEEE Access
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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
2017
Journal of Sensor and Actuator Networks
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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
2021
Entropy
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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
2020
Figshare
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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
2020
Figshare
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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
2018
EURASIP Journal on Wireless Communications and Networking
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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
2022
International Journal for Research in Applied Science and Engineering Technology
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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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