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2020 Index IEEE Journal of Biomedical and Health Informatics Vol. 24

2020 IEEE journal of biomedical and health informatics  
., and Inan, O.T., A Globalized Model for Mapping Wearable Seismocardiogram Signals to Whole-Body Ballistocardiogram Signals Based on Deep Learning; JBHI May 2020 1296-1309 Herskovic, V., see Saint-Pierre  ...  Vehkaoja, A., Ballistocardiography Can Estimate Beat-to-Beat Heart Rate Accurately at Night in Patients After Vascular Intervention; JBHI Aug. 2020 2230-2237 Hoogi, A., Mishra, A., Gimenez, F., Dong  ...  Decentralized Authentication of Distributed Patients in Hospital Networks Using Blockchain.  ... 
doi:10.1109/jbhi.2020.3048808 fatcat:iifrkwtzazdmboabdqii7x5ukm

Extremely Randomized Trees with Privacy Preservation for Distributed Structured Health Data

Amin Aminifar, Matin Shokri, Fazle Rabbi, Violet Ka I Pun, Yngve Lamo
2022 IEEE Access  
In this paper, we propose a distributed extremely randomized tree algorithm for learning with privacy preservation.  ...  The data used by machine learning algorithms in healthcare applications is often distributed over multiple sources, e.g., hospitals.  ...  The condition and control groups were monitored for 291 and 402 days in total, respectively. • The Psykose dataset [87] contains motor activity data from 54 individuals (23 females and 31 males, respec-tively  ... 
doi:10.1109/access.2022.3141709 fatcat:3jwyizm3irei7o35ib7zyckhpa

Deep Learning and Health Informatics for Smart Monitoring and Diagnosis [article]

Amin Gasmi
2022 arXiv   pre-print
that support data augmentation, un-semi-supervised learning, multi-modality and transfer learning architecture.  ...  It involves data usage, validation, and transfer of an integrated medical analysis using neural networks of multi-layer deep learning techniques to analyze complex data.  ...  To preserve mental health, psychiatric hospitals are screened, diagnosing, and monitoring depression with a system-on-chip solution that accelerates filters, and reveals heart rates on ECG.  ... 
arXiv:2208.03143v1 fatcat:74qhazw3ive65hglqtbqv4pz4a

Review:Emerging Trends in Healthcare Adoption of Wireless Body Area Networks

Anuradha Rangarajan
2016 Biomedical Instrumentation & Technology  
The healthcare benefits of WBANs include continuous monitoring of patient vitals, measuring postacute rehabilitation time, and improving quality of medical care provided in medical emergencies.  ...  This device in turn assimilates and transmits data over a wireless local area network, wide area network, or the Internet to a remote healthcare monitoring facility, thus generating an end-to-end wireless  ...  Felisberto et al. 7 developed an open and distributed architecture based on a multiagent system to detect human movements, postures, and harmful activities including falls.  ... 
doi:10.2345/0899-8205-50.4.264 pmid:27413830 fatcat:xyoudtinbvh4jkn5n4otvfzh3y

A Survey on Ambient Intelligence in Healthcare

Giovanni Acampora, Diane J. Cook, Parisa Rashidi, Athanasios V. Vasilakos
2013 Proceedings of the IEEE  
We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction  ...  ), reasoning techniques (for reasoning about users' goals and intensions) and planning techniques (for planning activities and interactions).  ...  ) • • Activity Recognition Monitoring for Emergency Detection Using sensor networks for detecting hazards, falls, etc.  ... 
doi:10.1109/jproc.2013.2262913 pmid:24431472 pmcid:PMC3890262 fatcat:vexuom74fjfyzdiraeckuenyhy

Recent use of deep learning techniques in clinical applications based on gait: a survey

Yume Matsushita, Dinh Tuan Tran, Hirotake Yamazoe, Joo-Ho Lee
2021 Journal of Computational Design and Engineering  
However, a large number of samples are required for training models when using deep learning, where the amount of available gait-related data may be limited for several reasons.  ...  This paper discusses certain techniques that can be applied to enable the use of deep learning for gait analysis in case of limited availability of data.  ...  Therefore, FoG detection while monitoring patients has a high priority.  ... 
doi:10.1093/jcde/qwab054 fatcat:uoqojsssorfnjp7vvpm2fldvsa

Progress in Brain Computer Interfaces: Challenges and Trends [article]

Simanto Saha, Khondaker A. Mamun, Khawza Ahmed, Raqibul Mostafa, Ganesh R. Naik, Ahsan Khandoker, Sam Darvishi, Mathias Baumert
2019 arXiv   pre-print
Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and nonlinear brain dynamics and related feature extraction  ...  Psycho-neurophysiological phenomena and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life.  ...  It is critical to introduce a suitable act for lawful utilization of BCI and preservation of privacy and confidentiality of stored data.  ... 
arXiv:1901.03442v1 fatcat:pvaoniplfrbz5gcys4vn3qp4ei

Emerging Technologies for Next Generation Remote Health Care and Assisted Living

Ijaz Ahmad, Zeeshan Asghar, Tanesh Kumar, Gaolei Li, Ahsan Manzoor, Konstantin Mikhaylov, Syed Attique Shah, Marko Hoyhtya, Jarmo Reponen, Jyrki Huusko, Erkki Harjula
2022 IEEE Access  
First the need of using the latest technological developments in the domain of remote health care is briefly discussed.  ...  Then the most important technologies and technological paradigms that are crucial in enabling remote health care and assisted living are emphasised.  ...  For example, the use of AI and machine learning requires gathering raw data, which in this case is patients' data.  ... 
doi:10.1109/access.2022.3177278 fatcat:m3tewfdwhnfabhc3pwidlvdlva

Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances [article]

Shibo Zhang, Yaxuan Li, Shen Zhang, Farzad Shahabi, Stephen Xia, Yu Deng, Nabil Alshurafa
2022 arXiv   pre-print
We also present cutting-edge frontiers and future directions for deep learning-based HAR.  ...  Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human--computer interaction, that measure and improve our daily lives.  ...  Acknowledgments Special thanks to Haik Kalamtarian and Krystina Neuman for their valuable feedback.  ... 
arXiv:2111.00418v5 fatcat:wylhzwkndjar7fc3esvhca2axi

A Survey on Social-Physical Sensing [article]

Md Tahmid Rashid, Na Wei, Dong Wang
2021 arXiv   pre-print
Propelled by versatile data capture, communication, and computing technologies, physical sensing has revolutionized the avenue for spontaneously capturing and interpreting real-world phenomenon.  ...  In this paper, we provide a comprehensive survey of SPS, with an emphasis on its definition and key enablers, state-of-the-art applications, potential research challenges, and road-map for future work.  ...  smartphones' Bluetooth radio and augment it with crowdsensed data [105] Extrapolate smartphone GPS data with crowdsensed data while preserving privacy to deduce approximate geographical locations  ... 
arXiv:2104.01360v1 fatcat:b6sag5objzhezcfhscb3ctf2ca

A Secure Occupational Therapy Framework for Monitoring Cancer Patients' Quality of Life

Md. Abdur Rahman, Md. Mamunur Rashid, Julien Le Kernec, Bruno Philippe, Stuart J. Barnes, Francesco Fioranelli, Shufan Yang, Olivier Romain, Qammer H. Abbasi, George Loukas, Muhammad Imran
2019 Sensors  
Using our proposed framework, both transactional records and multimedia big data can be shared with an oncologist or palliative care unit for real-time decision support.  ...  We have also developed blockchain-based data analytics, which will allow a clinician to visualize the immutable history of the patient's data available from an in-home secure monitoring system for a better  ...  After studying 701 cancer patients, the authors reported that subjects with physical activity generally reported higher scores for most EORTC QLQ-C30 and Functional Assessment of Cancer Therapy: General  ... 
doi:10.3390/s19235258 pmid:31795384 pmcid:PMC6928807 fatcat:awaereyjxbh5vlj26qndz3free

SVD Square-root Iterated Extended Kalman Filter for Modeling of Epileptic Seizure Count Time Series with External Inputs

Sidratul Moontaha, Andreas Galka, Michael Siniatchkin, Sascha Scharlach, Sarah von Spiczak, Ulrich Stephani, Theodor May, Thomas Meurer
2019 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)  
In this paper a nonlinear filtering algorithm for count time series is developed that takes the non-negativity of the data into account and preserves positive definiteness of the covariance matrices of  ...  The resulting algorithm is applied to the evaluation and design of therapies for patients suffering from Myoclonic Astatic Epilepsy, employing time series of daily seizure rate.  ...  [101] demonstrated the use of movement, activity and phone use derived descriptors to infer depression severity levels by way of supervised learning, resulting in an accuracy 86.5%.  ... 
doi:10.1109/embc.2019.8857159 pmid:31945973 fatcat:dmckhawdpbfwjoiekeerk4ra54

2021 Index IEEE Journal of Biomedical and Health Informatics Vol. 25

2021 IEEE journal of biomedical and health informatics  
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, JBHI Oct. 2021 3804-3811 Mosaic Privacy-Preserving Mechanisms for Healthcare Analytics.  ... 
doi:10.1109/jbhi.2022.3140980 fatcat:ufig7b54gfftnj3mocspoqbzq4

A Survey of Human Gait-Based Artificial Intelligence Applications

Elsa J. Harris, I-Hung Khoo, Emel Demircan
2022 Frontiers in Robotics and AI  
algorithms, 2) Health and Wellness, with applications in gait monitoring for abnormal gait detection, recognition of human activities, fall detection and sports performance, 3) Human Pose Tracking using  ...  incorporate continuous monitoring and control systems and 6) Animation that reconstructs human motion utilizing gait data, simulation and machine learning techniques.  ...  In these applications, the AI can continuously monitor and learn data, look for patterns, classify human activities and detect the anomaly.  ... 
doi:10.3389/frobt.2021.749274 pmid:35047564 pmcid:PMC8762057 fatcat:mqvy5qpcsjgfhdj4mw3altiroe

Digital technologies as biomarkers, clinical outcomes assessment, and recruitment tools in Alzheimer's disease clinical trials

Michael Gold, Joan Amatniek, Maria C. Carrillo, Jesse M. Cedarbaum, James A. Hendrix, Bradley B. Miller, Julie M. Robillard, J. Jeremy Rice, Holly Soares, Maria B. Tome, Ioannis Tarnanas, Gabriel Vargas (+2 others)
2018 Alzheimer s & Dementia Translational Research & Clinical Interventions  
The implications for the collection and use of large amounts of data, lessons learned from other related disease areas, ethical concerns raised by these new technologies, and regulatory issues were also  ...  Finally, the challenges and opportunities of these new technologies for future use were discussed.  ...  The VRFCAT is currently being used in phase 2 trials for schizophrenia and major depressive disorder.  ... 
doi:10.1016/j.trci.2018.04.003 pmid:29955666 pmcid:PMC6021547 fatcat:we46sl535jd33igukj5s5l5a7q
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