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Artificial Intelligence Based Body Sensor Network Framework—Narrative Review: Proposing an End-to-End Framework using Wearable Sensors, Real-Time Location Systems and Artificial Intelligence/Machine Learning Algorithms for Data Collection, Data Mining and Knowledge Discovery in Sports and Healthcare
2021
Sports Medicine - Open
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The current study aims to propose artificial intelligence-based body sensor network framework (AIBSNF), a framework for strategic use of body sensor networks (BSN), which combines with real-time location ...
This facilitates gathering of time-synchronized location and physiological vitals data, which allows artificial intelligence and machine learning (AI/ML)-based time series analysis. ...
Acknowledgements The authors of the paper would like to acknowledge Ms Maithili Phatak for her contribution for the artwork in the current paper. ...
doi:10.1186/s40798-021-00372-0
pmid:34716868
fatcat:htbk2pu7fvcbjcpslg3lcvgfhi
Detection of Abnormal Gait from Skeleton Data
2016
Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
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Human gait analysis has becomes of special interest to computer vision community in recent years. ...
We achieve 98% success to classify normal and abnormal gaits and show some relevant features that are able to distinguish them. ...
At the same time, the recent improvement of of low cost depth cameras with real-time capabilities such as Microsoft Kinect have been employed and in a wide range of applications, including human-computer ...
doi:10.5220/0005722901310137
dblp:conf/visapp/MengDDB16
fatcat:uusedyouencvbfh3s3kc3wllpy
A Novel Martingale Based Model Using a Smartphone to Detect Gait Bout in Human Activity Recognition
2022
Journal of Sensors
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MTMS(PSO) utilizes the martingale framework to capture gait bout in human activity recognition data. ...
Secondly, the activity recognition model involves computing a threshold for identifying gait bout. ...
Acknowledgments This work was supported by a University of Ulster Vice-Chancellor's Research Studentship. The authors would like to thank anonymous reviewers for their constructive suggestions. ...
doi:10.1155/2022/4753732
fatcat:6ndp3xymzjagbnzd22fe3r6lcy
A Survey on Visual Surveillance of Object Motion and Behaviors
2004
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
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It has a wide spectrum of promising applications, including access control in special areas, human identification at a distance, crowd flux statistics and congestion analysis, detection of anomalous behaviors ...
., occlusion handling, a combination of twoand three-dimensional tracking, a combination of motion analysis and biometrics, anomaly detection and behavior prediction, content-based retrieval of surveillance ...
Xie, and G. Xu from the NLPR for their valuable suggestions and assistance in preparing this paper. ...
doi:10.1109/tsmcc.2004.829274
fatcat:cozxn2ogtrew3pybyuxcrj2rhi
Tensor-based anomaly detection: An interdisciplinary survey
2016
Knowledge-Based Systems
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Traditional spectral-based methods such as PCA are popular for anomaly detection in a variety of problems and domains. ...
This survey aims to highlight the potential of tensor-based techniques as a novel approach for detection and identification of abnormalities and failures. ...
For instance, the difference of predicted and actual values can be used along with a threshold to detect anomalies. ...
doi:10.1016/j.knosys.2016.01.027
fatcat:lejxxae63jcutfx2ncahownt7e
Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges
2013
Sensors
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In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series ...
This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. ...
Acknowledgements The authors of this work are partially supported by SAAPHO (Secure Active Aging: Participation and Health for the Old). ...
doi:10.3390/s131217472
pmid:24351646
pmcid:PMC3892855
fatcat:fy4hhounsrgffno2fclhanqt7m
Detection of Motor Impairment in Parkinson's Disease Via Mobile Touchscreen Typing
2017
IEEE Transactions on Biomedical Engineering
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This paper presents an algorithm to detect PD by analyzing the typing activity on smartphones independently of the content of the typed text. We propose a set of touchscreen typing ...
At present, evaluation of PD signs requires trained experts to quantify motor impairment in the clinic, limiting the frequency and quality of the information available for understanding the status and ...
ACKNOWLEDGEMENTS The authors would like to thank the Federación Española Parkinson and the M+Vision and MIT linQ faculty for their guidance in developing this project. ...
doi:10.1109/tbme.2017.2664802
pmid:28237917
fatcat:jyfmuyijynbenkpudrjm4ebwce
Symbolic Modelling of Dynamic Human Motions
[chapter]
2010
Biosensors
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In order to be able to use the described method in a real application, an image processing and computer vision section for data acquisition should be added to the system. ...
It is conjectured that the study of these dynamic (spatiotemporal) multidimensional manifestations will facilitate a new approach to anomaly pattern detection for human motions. ...
doi:10.5772/7215
fatcat:mgfvhfsrhrgodazqxktbhuo2zq
A survey of multilinear subspace learning for tensor data
2011
Pattern Recognition
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Lastly, the paper summarizes a wide range of MSL applications and concludes with perspectives on future research directions. ...
This leads to a strong demand for learning algorithms to extract useful information from these massive data. ...
Acknowledgment The authors would like to thank the anonymous reviewers for their insightful comments, which have helped to improve the quality of this paper. ...
doi:10.1016/j.patcog.2011.01.004
fatcat:6puqzxrohfawraeiyid6633wdm
Distributed Machine Learning in Materials that Couple Sensing, Actuation, Computation and Communication
[article]
2016
arXiv
pre-print
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This paper reviews machine learning applications and approaches to detection, classification and control of intelligent materials and structures with embedded distributed computation elements. ...
As the ultimate goal of this research is to incorporate the approaches described in this survey into a robotic material paradigm, the potential for adapting the computational models used in these applications ...
Detection of gait anomaly and be used to predict and possibly prevent falls. ...
arXiv:1606.03508v1
fatcat:zb5jcvda5jg6zpsv5w47wwr6nq
Big data analytics for preventive medicine
2019
Neural computing & applications (Print)
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We summarize state-of-the-art data analytics algorithms used for classification of disease, clustering (unusually high incidence of a particular disease), anomalies detection (detection of disease) and ...
The aim of this study is to provide a comprehensive and structured overview of extensive research on the advancement of data analytics methods for disease prevention. ...
[210] integrate PCA and multivariate cumulative sum(MCUSUM) for anomaly detection with high sensitivity to small anomaly. ...
doi:10.1007/s00521-019-04095-y
pmid:32205918
pmcid:PMC7088441
fatcat:x52upnuwbjdchkyb7hog5pvawm
Tackling Faults in the Industry 4.0 Era—A Survey of Machine-Learning Solutions and Key Aspects
2019
Sensors
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At the same time, the introduction of the Industrial Internet of Things (IIoT), providing improved wireless connectivity for real-time manufacturing data collection and processing, has resulted in the ...
Towards this end, a detailed overview of ML-based human–machine interaction techniques is provided, allowing humans to be in-the-loop of the manufacturing processes in a symbiotic manner with minimal errors ...
Thus, an intelligent data analysis and real-time supervision (IDARTS) framework was presented for data collection and creation of context-aware data analysis and evaluation. ...
doi:10.3390/s20010109
pmid:31878065
pmcid:PMC6983262
fatcat:n4muoguq5jalrfwqkq4264vswe
A systematic review of security and privacy issues in the internet of medical things; the role of machine learning approaches
2021
PeerJ Computer Science
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A total of 153 papers were reviewed and a critical analysis was conducted on the selected papers. ...
Thus, a detailed analysis was carried out on the selected papers through focusing on their methods, advantages, limitations, the utilized tools, and data. ...
include a computing analysis facility, which is coupled with a local archiving database in order to store the initial records of the patient. ...
doi:10.7717/peerj-cs.414
pmid:33834100
pmcid:PMC8022640
fatcat:tlpu7eud4zgifbhgzkqucsxk6e
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
[article]
2021
arXiv
pre-print
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With the advances of data-driven machine learning research, a wide variety of prediction problems have been tackled. ...
We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure and electrical-based analysis. ...
A structural time series is represented as (X, A) where X ∈ R T XpXc is a multivariate time series where T is the number of time steps, p is the number of sequences, c is the number of channels, and A ...
arXiv:2105.13137v1
fatcat:gm7d2ziagba7bj3g34u4t3k43y
Application of AI and IoT in Clinical Medicine: Summary and Challenges
2021
Current Medical Science
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In this work, we examine the technical basis of IoT, cloud computing, big data analysis and machine learning involved in clinical medicine, combined with concepts of specific algorithms such as activity ...
recognition, behavior recognition, anomaly detection, assistant decision-making system, to describe the scenario-based applications of remote diagnosis and treatment collaboration, neonatal intensive ...
Domain-specific functions require functions tailored to specific applications, such as Time-Domain Gait Detection, which utilizes a timedomain algorithm for gait detection in addition to the Fast Fourier ...
doi:10.1007/s11596-021-2486-z
pmid:34939144
pmcid:PMC8693843
fatcat:3g3qpksktjhv5koqs3i7ylco7y
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