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A Deep Learning Framework using Passive WiFi Sensing for Respiration Monitoring [article]

U. M. Khan, Z. Kabir, S. A. Hassan, S. H. Ahmed
2017 arXiv   pre-print
This paper presents an end-to-end deep learning framework using passive WiFi sensing to classify and estimate human respiration activity.  ...  Based on the results, we conclude that deep learning techniques coupled with passive radars offer great potential for end-to-end human activity recognition.  ...  Specifically, this research introduces a vital health wireless device and makes the following contributions: • Proposes a deep learning framework for classifying various activities using passive WiFi sensing  ... 
arXiv:1704.05708v1 fatcat:6owynzhx7rbv5l5pabtefhagce

Contactless WiFi Sensing and Monitoring for Future Healthcare - Emerging Trends, Challenges and Opportunities

Yao Ge, Ahmad Taha, S.A Shah, Kia Dashtipour, Shuyuan Zhu, Jonathan M. Cooper, Qammer Abbasi, Muhammad Imran
2022 IEEE Reviews in Biomedical Engineering  
WiFi sensing has recently received significant interest from academics, industry, healthcare professionals and other caregivers (including family members) as a potential mechanism to monitor our aging  ...  The interest in such WiFi-based sensing systems stems from its practical deployments in indoor settings and compliance from monitored persons, unlike other sensors such as wearables, camera-based, and  ...  Such monitoring systems can also be combined with deep learning and can be used to monitor behavior, including emotional states and mental wellbeing.  ... 
doi:10.1109/rbme.2022.3156810 pmid:35254990 fatcat:oxwsifpznrac7h3ix35tvbdp2q

Respiration and Activity Detection based on Passive Radio Sensing in Home Environments

Qingchao Chen, Yang Liu, Bo Tan, Karl Woodbridge, Kevin Chetty
2020 IEEE Access  
This paper introduces a deep learning enabled passive radio sensing method that can monitor human respiration and daily activities through leveraging unplanned and ever-present wireless bursts in the ISM  ...  We use 2.4GHz 802.11 (WiFi) signals to demonstrate experimentally the capability of this technique for human respiration detection (including through-the-wall), and classifying everyday but complex human  ...  PROCESSING AND MACHINE LEARNING FRAMEWORK In this paper we adopt an end-to-end framework that integrates i). a highly sensitive phase extraction technique for respiration detection and ii). a deep transfer  ... 
doi:10.1109/access.2020.2966126 fatcat:x77vn2cp5zegtorhgz5iyhoeni

Wi-COVID: A COVID-19 Symptom Detection and Patient Monitoring Framework using WiFi

Fangyu Li, Maria Valero, Hossain Shahriar, Rumi Ahmed Khan, Sheikh Iqbal Ahamed
2020 Smart Health  
In this paper, we explore the possibility of monitoring respiration rates (RR) of COVID-19 patients using a widely-available technology at home - WiFi.  ...  Then, we propose the framework scheme for an end-to-end non-invasive monitoring platform of the COVID-19 patients using WiFi. Finally, we present some preliminary results of the proposed framework.  ...  We provide a comprehensive review of the current WiFi-based available technology for monitoring vital signs and people's activities that can provide a novel approach to monitor patients. 2.  ... 
doi:10.1016/j.smhl.2020.100147 pmid:33251320 pmcid:PMC7680085 fatcat:asgyrbkve5endpxm52z5ye5l4m

IoT Platform for COVID-19 Prevention and Control: A Survey

Yudi Dong, Yu-Dong Yao
2021 IEEE Access  
One of the lessons learned from the COVID-19 pandemic is that a long-term system with non-pharmaceutical interventions for preventing and controlling new infectious diseases is desirable to be implemented  ...  last for many years.  ...  The sensing data is then fed into a machine learning model to predict COVID-19. This proposed IoT-based framework is a low-cost solution for COVID-19 monitoring.  ... 
doi:10.1109/access.2021.3068276 pmid:34812390 pmcid:PMC8545211 fatcat:cmbjn3ua3be27cbyfd3tpvjypi

The State-of-the-Art Sensing Techniques in Human Activity Recognition: A Survey

Sizhen Bian, Mengxi Liu, Bo Zhou, Paul Lukowicz
2022 Sensors  
Finally, we summarized the presented sensing techniques with a comparison concerning selected performance metrics and proposed a few outlooks on the future sensing techniques used for HAR tasks.  ...  This work tries to present a thorough, in-depth survey on the state-of-the-art sensing modalities in HAR tasks to supply a solid understanding of the variant sensing principles for younger researchers  ...  [46] proposed a respiration rate monitoring using an in-ear headphone inertial sensor.  ... 
doi:10.3390/s22124596 pmid:35746376 pmcid:PMC9229953 fatcat:2cjpolwafnem7o4mehxigaqojq

A Survey of Commodity WiFi Sensing in 10 Years: Current Status, Challenges, and Opportunities [article]

Sheng Tan, Jie Yang
2022 arXiv   pre-print
The prevalence of WiFi devices and ubiquitous coverage of WiFi networks provide us the opportunity to extend WiFi capabilities beyond communication, particularly in sensing the physical environment.  ...  Next, this work presents the challenges faced by existing WiFi sensing systems. Lastly, we comprehensively discuss the future trending of commodity WiFi sensing.  ...  ACKNOWLEDGEMENT We thank the anonymous reviewers for their insightful feedback. This work was partially supported by the NSF Grants CNS 1910519, CNS 2131143, CNS 2120396, CNS1801630 and CCF2028876.  ... 
arXiv:2111.07038v3 fatcat:cowtxhmvh5b7lmfeswjdeik7ie

WiFi-based Human Activity Recognition using Raspberry Pi

Glenn Forbes, Stewart Massie, Susan Craw
2020 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI)  
This method is similar to how many deep learning activity recognition studies were performed using the IWL5300, however the Pi benefits from a deep learning approach as it has access to significantly more  ...  We use a deep variant of this model which requires more training and can potentially learn higher level concepts.  ... 
doi:10.1109/ictai50040.2020.00115 fatcat:gmrtslt3fvczvlqsmfglyqpd6u

IoT Platform for COVID-19 Prevention and Control: A Survey [article]

Yudi Dong, Yu-Dong Yao
2020 arXiv   pre-print
One of the lessons learned from the COVID-19 pandemic is that a long-term system with non-pharmaceutical interventions for preventing and controlling new infectious diseases is desirable to be implemented  ...  Specifically, we demonstrate a potential fog-cloud combined IoT platform that can be used in the systematic and intelligent COVID-19 prevention and control, which involves five interventions including  ...  The sensing data is then fed into a machine learning model to predict COVID-19. This proposed IoT-based framework is a low-cost solution for COVID-19 monitoring.  ... 
arXiv:2010.08056v2 fatcat:pk7kdk3wu5etlfpfkpn7br5aam

Ambient Assisted Living: A Research on Human Activity Recognition and Vital Health Sign Monitoring using Deep Learning Approaches

Later, we survey the existing literature for HAR and VHSM based on sensor modality and deep learning approach used.  ...  Next we present brief insights into sensor modalities and different deep learning architectures.  ...  Khan et al.,2017[49] Ambient (WiFi sensing) CNN Introduced a DCNN based end-to-end deep learning framework for respiration monitoring using passive WiFi sensing.  ... 
doi:10.35940/ijitee.f1111.0486s419 fatcat:5mtkrtx54ndtbn2oms6ij7s5xy

A Survey on CSI-based Human Behavior Recognition in Through-the-Wall Scenario

Zhengjie Wang, Kangkang Jiang, Yushan Hou, Zehua Huang, Wenwen Dou, Chengming Zhang, Yinjing Guo
2019 IEEE Access  
Meanwhile, the CSI signal provides us with additional benefits because it can propagate through a wall.  ...  Recent years have witnessed increasing research interest in human behavior recognition as it provides attractive applications in various sensing scenarios.  ...  CSI-BASED THROUGH-WALL BEHAVIOR RECOGNITION FRAMEWORK AND GENERAL METHODS In this section, we present a general framework for throughthe-wall behavior recognition using CSI based on COTS WiFi devices.  ... 
doi:10.1109/access.2019.2922244 fatcat:lofr7xfuufgbranwrofa4qdy7u

2020 Index IEEE Transactions on Mobile Computing Vol. 19

2021 IEEE Transactions on Mobile Computing  
., +, TMC April 2020 894-906 RSS Models for Respiration Rate Monitoring.  ...  Azizi, A., +, TMC Oct. 2020 2445-2460 Frequency estimation RSS Models for Respiration Rate Monitoring.  ... 
doi:10.1109/tmc.2020.3036773 fatcat:6puiux5lp5bfvjo47ey7ycwyfu

Deep Learning for Radio-based Human Sensing: Recent Advances and Future Directions [article]

Isura Nirmal, Abdelwahed Khamis, Mahbub Hassan, Wen Hu, Xiaoqing Zhu
2021 arXiv   pre-print
Recently, researchers have successfully applied deep learning to take radio-based sensing to a new level.  ...  In this survey, we provide a comprehensive review and taxonomy of recent research efforts on deep learning based RF sensing.  ...  WiFi CSI was used as the input for the deep learning.  ... 
arXiv:2010.12717v2 fatcat:pb6xt445tneijjohfwxizxr7he

Coexistence Management in Wireless Networks- A survey

Ayesha Hasan, Bilal Muhammad Khan
2022 IEEE Access  
The rapid proliferation of wireless networks poses a great challenge of effective coexistence management amongst a plethora of wireless communication protocol users that are co-located and contending for  ...  For effective spectrum utilization and optimum performance of existing wireless networks and for the realization of new wireless networks, coexistence management of the wireless spectrum is the key to  ...  In [77] deep convolutional networks are used for spectrum monitoring in radar bands.  ... 
doi:10.1109/access.2022.3165223 fatcat:oqikf5fnojfdhldfrhbtriam34

Passive and Context-Aware In-Home Vital Signs Monitoring Using Co-Located UWB-Depth Sensor Fusion

Zongxing Xie, Bing Zhou, Xi Cheng, Elinor Schoenfeld, Fan Ye
2022 ACM Transactions on Computing for Healthcare  
In this paper, we propose a robust, non-touch vital signs monitoring system using a pair of co-located Ultra-Wide Band (UWB) and depth sensors.  ...  Our experimental results demonstrate the robustness and superior performance of the individual modules as well as the end-to-end system for passive and context-aware vital signs monitoring.  ...  We implement deep learning models with PyTorch and run them using the GPU on the laptop.  ... 
doi:10.1145/3549941 fatcat:3vo4fmb3afap3j6avf3daf2vr4
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