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Real-Time Depth of Anaesthesia Assessment Based on Hybrid Statistical Features of EEG
2022
Sensors
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This paper proposed a new depth of anaesthesia (DoA) index for the real-time assessment of DoA using electroencephalography (EEG). ...
Then, the Gaussian process regression model was employed for real-time assessment of anaesthesia states. ...
Conclusions
Conclusions This paper studies the real-time monitoring of anaesthesia states using hybrid statistical features and machine learning methods. ...
doi:10.3390/s22166099
pmid:36015860
pmcid:PMC9414837
fatcat:iqqetxxokvalxbgzs2ptsbu2ha
A Robust approach for Depth of Anaesthesia Assessment Based on Hybrid Transform and Statistical Features
2019
IET Science, Measurement & Technology
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To develop an accurate and efficient depth of anaesthesia (DoA) assessment technique that could help anaesthesiologists to trace the patient's anaesthetic state during surgery, a new automated DoA approach ...
Ten statistical features were extracted and analysed, and from these, five features were selected for designing a new index for the DoA assessment. ...
Conclusion A robust approach for the DoA assessment based on the WFA and statistical features is proposed. In this method, ten statistical features were extracted from each EEG segment using the WFA. ...
doi:10.1049/iet-smt.2018.5393
fatcat:mdv7lrukinftpnpdlfd6iaxppm
Tracking Electroencephalographic Changes Using Distributions of Linear Models: Application to Propofol-Based Depth of Anesthesia Monitoring
2017
IEEE Transactions on Biomedical Engineering
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Here, we seek not only to assess the utility of a distribution-based approach, but also to assess how linear modeling performs compared to a high performing depth of anaesthesia monitoring method evaluated ...
As described above, HFD performs well as a frontal-EEG-based depth of anesthesia monitoring feature. ...
Authors photographs and biographies not available at the time of publication. ...
doi:10.1109/tbme.2016.2562261
pmid:27323352
fatcat:em47rrkivnd37hleuc5p43xfli
Intelligent Systems in Biomedicine
[chapter]
2002
International Series in Intelligent Technologies
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An application involving fuzzy reasoning and control paradigms in anaesthesia is described in some detail. ...
The complexity of biological systems, unlike physical science applications, makes the development of computerised systems for medicine not a straightforward algorithmic solution because of the inherent ...
This paper describes the structure of a real-time measuring system based on fuzzy logic as shown in figure 1. ...
doi:10.1007/978-94-010-0324-7_31
fatcat:psry55okm5ejti7oevfqwpbzo4
2018 Index IEEE Journal of Biomedical and Health Informatics Vol. 22
2018
IEEE journal of biomedical and health informatics
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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. ...
Strasser, T., +, JBHI Hz ASSR for Measuring Depth of Anaesthesia During Induction Phase. ...
., +, JBHI July 2018 968-978 Anesthesia 40-Hz ASSR for Measuring Depth of Anaesthesia During Induction Phase. ...
doi:10.1109/jbhi.2018.2880294
fatcat:3cy3e7no55emlgbxfe3mwef3vu
Application of higher order statistics/spectra in biomedical signals—A review
2010
Medical Engineering and Physics
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However, there are practical situations where one needs to look beyond autocorrelation of a signal to extract information regarding deviation from Gaussianity and the presence of phase relations. ...
The information contained in the power spectrum is essentially that of the autocorrelation sequence; which is sufficient for complete statistical descriptions of Gaussian signals of known means. ...
The feature set included parameters derived from moments of the power spectrum and moments based on the bispectrum of EEG signals.Experimental results have shown that based on the proposed features, the ...
doi:10.1016/j.medengphy.2010.04.009
pmid:20466580
fatcat:tj6lm3xcqba2dhxhpf6afitaua
Deep learning-based electroencephalography analysis: a systematic review
2019
Journal of Neural Engineering
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Recently, deep learning (DL) has shown great promise in helping make sense of EEG signals due to its capacity to learn good feature representations from raw data. ...
Electroencephalography (EEG) is a complex signal and can require several years of training, as well as advanced signal processing and feature extraction methodologies to be correctly interpreted. ...
Funding This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC-RDC) for JF and YR (reference number: RDPJ 514052-17), NSERC research funds for JF, HB, IA and ...
doi:10.1088/1741-2552/ab260c
pmid:31151119
fatcat:tgb2o34h2zbx7jft2d6bqbkvlu
A survey of fuzzy logic monitoring and control utilisation in medicine
2001
Artificial Intelligence in Medicine
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Many of these intelligent systems are based on fuzzy control strategies which describe complex systems mathematical models in terms of linguistic rules. ...
This paper surveys the utilisation of fuzzy logic control and monitoring in medical sciences with an analysis of its possible future penetration. # ...
Acknowledgements The authors acknowledge the impetus given to this survey by the preparation of a draft Roadmap for ERUDIT, the European Network for Excellence in Uncertainty Modelling and Fuzzy Technology ...
doi:10.1016/s0933-3657(00)00072-5
pmid:11154872
fatcat:u7fhlvvcwzf6rnrmz3u54thr4q
Deep Learning in EEG: Advance of the Last Ten-Year Critical Period
2021
IEEE Transactions on Cognitive and Developmental Systems
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We hope that this paper could serve as a summary of past work for deep learning in EEG and the beginning of further developments and achievements of EEG studies based on deep learning. ...
They are followed by the discussion, in which the pros and cons of deep learning are presented and future directions and challenges for deep learning in EEG are proposed. ...
On the one hand, EEG signal is non-stationary and much variable over time, which makes the extraction of robust features difficult. ...
doi:10.1109/tcds.2021.3079712
fatcat:5rck4hvysfhe5o2tfjywytr5o4
Deep learning-based electroencephalography analysis: a systematic review
[article]
2019
arXiv
pre-print
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Moreover, almost one-half of the studies trained their models on raw or preprocessed EEG time series. ...
Recently, deep learning (DL) has shown great promise in helping make sense of EEG signals due to its capacity to learn good feature representations from raw data. ...
Funding This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) for YR (reference number: RDPJ 514052-17), HB, IA and THF, the Fonds québécois de la recherche ...
arXiv:1901.05498v2
fatcat:5ugb4i3oerdrvarwozxvepbzxe
Scope of physiological and behavioural pain assessment techniques in children – a review
2018
Healthcare technology letters
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In this review, some good indicators of pain in children are explained in detail; they are facial expressions from an RGB image, thermal image and also feature from well proven physiological signals such ...
Thus, this conceptual work explains the demand for automatic coding techniques to evaluate pain and also it documents some evidence of techniques that act as an alternative approach for objectively determining ...
Challenges & future work: When we discuss the challenges, the key point to be considered is patient's cooperation, real-time data capture and the dependence of biopotentials on other factors. ...
doi:10.1049/htl.2017.0108
pmid:30155264
pmcid:PMC6103781
fatcat:z7cdizvs2ncs5jgdjjsy6uzzby
Current Developments in Automatic Drug Delivery in Anesthesia
2013
Biomedical Engineering
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Our group also developed controllers for the neuromuscular blockade, the depth of hypnosis and the analgesia. ...
The main objectives during general anaesthesia are adequate level of hypnosis, analgesia, relaxation, and stable vital functions. ...
Billinger for advice and assistance in the development of aspects of the BCI systems used in this work. ...
doi:10.1515/bmt-2013-4426
pmid:24043206
fatcat:qf5imnl6xvdrpc2vjkylgmanlq
Euroanaesthesia 2004: Joint Meeting of the European Society of Anaesthesiologists and European Academy of Anaesthesiology Lisbon, Portugal, 5–8 June 2004
2005
European Journal of Anaesthesiology
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A-188 Influence of xenon on heart rate variability in high risk cardiovascular patients Acknowledgements: This study was supported by a grant from the Else Acknowledgements: Supported in part by Baxter ...
A-226 Effects of candesartan and enalaprilat on the organ-specific microvascular permeability during hemorrhagic shock in rats Acknowledgement: This study was supported by the Swiss National Science Foundation ...
from the EEG and marketed as a monitor of depth of sedation and hypnosis during anaesthesia. ...
doi:10.1017/s0265021504000419
fatcat:wm7pcjpxtrairjazkct3zc6hlm
A Review of Deep Learning Methods for Photoplethysmography Data
[article]
2024
arXiv
pre-print
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Based on the tasks addressed in these papers, we categorized them into two major groups: medical-related, and non-medical-related. ...
However, challenges remain, such as limited quantity and quality of publicly available databases, a lack of effective validation in real-world scenarios, and concerns about the interpretability, scalability ...
Acknowledgement This work was supported by the National Natural Science Foundation of China (No. 62102008) and Beijing Natural Science Foundations (QY23040). ...
arXiv:2401.12783v1
fatcat:qpwykpoixnhzfjgzsne3brzpxa
Transösophageales Interventrikuläres Delay bei Vorhofflimmern und Kardialer Resynchronisation
2013
Biomedical Engineering
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Schellhorn, "Online ocular artefact removal for dc-eeg-signals: estimation of dc-level," DGBMT, 2004. [2] P. He, G. ...
Our gratitude also extends to the Centre for Promotion of Science, as the organizers of Festival of robotics 2012, without which these experiments wouldn't be possible in this extent. ...
The quality of adaption of a model is assessed based on a comparison between statistical properties of the TS and the model: • Visual comparison between the theoretical ACF of the ARMA model and the empirical ...
doi:10.1515/bmt-2013-4154
pmid:24042832
fatcat:qsbz2z3utva6rery74jfw66pe4
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