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Learning Shallow Detection Cascades for Wearable Sensor-Based Mobile Health Applications
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<span title="2016-07-13">2016</span>
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arXiv
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<span class="release-stage" >pre-print</span>
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In this paper, we propose a novel approach to learning shallow detection cascades developed explicitly for use in a real-time wearable-phone or wearable-phone-cloud systems. ...
The field of mobile health aims to leverage recent advances in wearable on-body sensing technology and smart phone computing capabilities to develop systems that can monitor health states and deliver just-in-time ...
The authors would like to thank Deepak Ganesan for helpful discussions of this research. ...
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Big Sensed Data Meets Deep Learning for Smarter Health Care in Smart Cities
<span title="2017-11-20">2017</span>
<i title="MDPI AG">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bajb2sq2z5a3beaybwby4ac4w4" style="color: black;">Journal of Sensor and Actuator Networks</a>
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Hard sensing-based data acquisition through wearables or invasive probes, coupled with soft sensing-based acquisition such as crowd-sensing results in hidden patterns in the aggregated sensor data. ...
Furthermore, we present a comparison and taxonomy of these methodologies based on types of sensors and sensed data. ...
[48] used convolutional neural networks (CNN) for the classification and detection of the key features in Parkinson's disease based on data generated from wearable sensors. ...
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On revisiting vital signs IoT sensors for COVID-19 and long COVID-19 monitoring: a condensed updated review and future directions
<span title="2021-12-31">2021</span>
<i title="Journal of Ideas in Health">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6nyf5in7ubbhbpq7trlwbdylpe" style="color: black;">Journal of Ideas in Health</a>
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Although there are several IoT devices for health monitoring, there is still work to standardize data formats and APIs for data extraction. ...
Conclusion: Here, technological trends such as Serverless computing, homomorphic cryptography, Federated Learning, Elixir programming language, Web Assembly, and vertical elasticity are discussed towards ...
They also provide mobile applications for Android and IOS, enabling users to visualize their data and set alerts and alarms based on them. ...
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NT-FDS—A Noise Tolerant Fall Detection System Using Deep Learning on Wearable Devices
<span title="2021-03-12">2021</span>
<i title="MDPI AG">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a>
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The work focuses on Deep Learning (DL) particularly Recurrent Neural Networks (RNNs) with an underlying Bidirectional Long Short-Term Memory (BiLSTM) stack to implement FDS based on wearable sensors. ...
data making it unfit for reliable fall detection. ...
Deep Learning Techniques for Wearable Sensors Based Fall Detection Recently applications of Deep Learning, with their ability to deliver remarkable results in comparison to extracting features manually ...
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An egocentric computer vision based co-robot wheelchair
<span title="">2016</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dmucnarmarh2fj6syg5jyqs7ny" style="color: black;">2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)</a>
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Motivated by the emerging needs to improve the quality of life for the elderly and disabled individuals who rely on wheelchairs for mobility, and who might have limited or no hand functionality at all, ...
we propose an egocentric computer vision based co-robot wheelchair to enhance their mobility without hand usage. ...
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. ...
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Table of Contents
<span title="">2021</span>
<i title="Institute of Electrical and Electronics Engineers (IEEE)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ezthgawmfbeczntonmx4gfjvtm" style="color: black;">IEEE Transactions on Instrumentation and Measurement</a>
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Amorim An Open-Source Wearable Sensor System for Detecting Extravasation of Intravenous Infusion ............ H.-C. Lee and J.-S. ...
Guan Shallow Convolutional Neural Networks for Human Activity Recognition Using Wearable Sensors .................................... ................................................................... ...
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Empowering Persons with Deafblindness
<span title="">2018</span>
<i title="ACM Press">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/x2nft42cpndnln67jzca2rd3dq" style="color: black;">Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference on - PETRA '18</a>
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Based on user needs and informed by disability studies, we combine elements from smart textiles, sensors, semantic technologies, image processing, face and object recognition, machine learning, affective ...
In this work, we present the underlying concepts and the overall design vision of the resulting assistive smart wearable. ...
for improvements in the quality of their life and health. ...
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American Sign Language Recognition Based on MobileNetV2
<span title="">2020</span>
<i title="ASTES Journal">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5z5fhzfgard2vod5er2hdyuq54" style="color: black;">Advances in Science, Technology and Engineering Systems</a>
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This paper wishes to extend the previously proposed Convolutional Neural Network (CNN) model for predicting American Sign Language with a MobileNetV2-based transfer learning model. ...
Because of its relatively fewer parameters and less intensive computational operations compared to other deep learning architectures, the model was also ideal to be implemented on mobile devices. ...
Acknowledgment I wish to acknowledge Tunku Abdul Rahman University College for sponsoring this research. ...
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Trends in human activity recognition with focus on machine learning and power requirements
<span title="">2021</span>
<i title="Elsevier BV">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vui6j5722zev3lcb7xtzdug5nq" style="color: black;">Machine Learning with Applications</a>
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Potential applications include the use of wearables for continuous health monitoring. ...
Deep learning algorithms for HAR using mobile and wearable sensor networks: State of the art and research challenges One of the most important components of HAR is feature extraction. ...
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Sensors and Actuators in Smart Cities
<span title="2018-02-16">2018</span>
<i title="MDPI AG">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bajb2sq2z5a3beaybwby4ac4w4" style="color: black;">Journal of Sensor and Actuator Networks</a>
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Author Contributions: Alex Adim Obinikpo and Burak Kantarci conceived and pursued the literature survey on deep learning techniques on big sensed data for smart health applications, reviewed the state ...
The authors are grateful to the Middle East University, Amman, Jordan for the financial support granted to cover the publication fee of this research article. Author Contributions: Abdelhamied A. ...
While shallow learning algorithms enforce shallow methods on sensor data for feature representation, deep learning seeks to extract hierarchical representations [21, 22] from large-scale data. ...
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A Review on the Role of Machine Learning in Enabling IoT Based Healthcare Applications
<span title="">2021</span>
<i title="Institute of Electrical and Electronics Engineers (IEEE)">
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Due to the large amount of data involved in healthcare, and the enormous value that accurate predictions hold, the integration of machine learning (ML) algorithms into H-IoT is imperative. ...
The key elements of all H-IoT applications are data gathering and processing. ...
These were connected to a mobile application which can aggregate and store this data onto a cloud based platform for analysis. ...
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State of the Art of Audio- and Video-Based Solutions for AAL
<span title="2022-03-28">2022</span>
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Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one's activities. In addition, a single [...] ...
In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. ...
systems for smart homes shows that domestic (including audio and video based) or wearable sensors are very common for HAR, combined with machine learning. ...
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A Wireless Reflectance Pulse Oximeter With Digital Baseline Control for Unfiltered Photoplethysmograms
<span title="">2012</span>
<i title="Institute of Electrical and Electronics Engineers (IEEE)">
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ACKNOWLEDGMENTS The authors thank David Huddleston, KSU Electronics Design Laboratory, for his assistance with the reflow soldering on the surface-mounted devices. ...
flexibility suitable for mobile and surface-based applications. ...
These conditions are primary drivers for the development of wearable and mobile health monitoring technologies that offer the potential to (a) increase the quality of life for individuals that already ...
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Data-Driven Analytics Leveraging Artificial Intelligence in the Era of COVID-19: An Insightful Review of Recent Developments
<span title="2021-12-23">2021</span>
<i title="MDPI AG">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nzoj5rayr5hutlurimhzyjlory" style="color: black;">Symmetry</a>
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This insightful review aims to highlight existing AI-based technological developments and future research dynamics in this area. ...
These technologies assisted the early detection/diagnosis, trends analysis, intervention planning, healthcare burden forecasting, comorbidity analysis, and mitigation and control, to name a few. ...
[200] Mobile sensors IoT-based solution for hospitals in order to improve health monitoring and providing timelier healthcare for patients Krishnan et al. ...
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Program
<span title="2020-09-28">2020</span>
<i title="IEEE">
2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)
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This paper proposes an augmented reality (AR)-based question-answering system (QAS) for wedding dress, which applies mobile application to wedding market. ...
In this research, we propose a forensic scheme to detect and even locate image manipulations based on deep-learning-based camera model identification. ...
The user can monitor the output voltage and current through mobile phone immediately.
16:00 An Intelligent Fall Detection Design for Mobile Health-Care Applications Jui-Hung Hsieh, Hui-Lan Zhang and ...
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