| 1. |
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| 2. |
- Klionsky, Daniel J., et al.
(författare)
-
Guidelines for the use and interpretation of assays for monitoring autophagy
- 2012
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Ingår i: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
-
Forskningsöversikt (refereegranskat)abstract
- In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
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| 3. |
- Kehoe, Laura, et al.
(författare)
-
Make EU trade with Brazil sustainable
- 2019
-
Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 4. |
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| 5. |
- Jönsson, Håkan, et al.
(författare)
-
Matkulturer på Arbetsplatserna
- 2005
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Ingår i: Mat, hälsa och oregelbundna arbetstider. - Lund : Department of Sociology, Lund University. - 9172671874 ; Research report in Sociology 2005:1, s. 43-59, s. 43-59
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 6. |
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| 7. |
- Teede, Helena J, et al.
(författare)
-
Recommendations from the 2023 International Evidence-based Guideline for the Assessment and Management of Polycystic Ovary Syndrome.
- 2023
-
Ingår i: Fertility and sterility. - 1556-5653. ; 120:4, s. 767-793
-
Tidskriftsartikel (refereegranskat)abstract
- What is the recommended assessment and management of those with polycystic ovary syndrome (PCOS), based on the best available evidence, clinical expertise, and consumer preference?International evidence-based guidelines address prioritized questions and outcomes and include 254 recommendations and practice points, to promote consistent, evidence-based care and improve the experience and health outcomes in PCOS.The 2018 International PCOS Guideline was independently evaluated as high quality and integrated multidisciplinary and consumer perspectives from six continents; it is now used in 196 countries and is widely cited. It was based on best available, but generally very low to low quality, evidence. It applied robust methodological processes and addressed shared priorities. The guideline transitioned from consensus based to evidence-based diagnostic criteria and enhanced accuracy of diagnosis, whilst promoting consistency of care. However, diagnosis is still delayed, the needs of those with PCOS are not being adequately met, evidence quality was low and evidence-practice gaps persist.The 2023 International Evidence-based Guideline update reengaged the 2018 network across professional societies and consumer organizations with multidisciplinary experts and women with PCOS directly involved at all stages. Extensive evidence synthesis was completed. Appraisal of Guidelines for Research and Evaluation-II (AGREEII)-compliant processes were followed. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework was applied across evidence quality, feasibility, acceptability, cost, implementation and ultimately recommendation strength and diversity and inclusion were considered throughout.This summary should be read in conjunction with the full Guideline for detailed participants and methods. Governance included a six-continent international advisory and management committee, five guideline development groups, and paediatric, consumer, and translation committees. Extensive consumer engagement and guideline experts informed the update scope and priorities. Engaged international society-nominated panels included paediatrics, endocrinology, gynaecology, primary care, reproductive endocrinology, obstetrics, psychiatry, psychology, dietetics, exercise physiology, obesity care, public health and other experts, alongside consumers, project management, evidence synthesis, statisticians and translation experts. Thirty-nine professional and consumer organizations covering 71 countries engaged in the process. Twenty meetings and five face-to-face forums over 12 months addressed 58 prioritized clinical questions involving 52 systematic and 3 narrative reviews. Evidence-based recommendations were developed and approved via consensus across five guideline panels, modified based on international feedback and peer review, independently reviewed for methodological rigour, and approved by the Australian Government National Health and Medical Research Council (NHMRC).The evidence in the assessment and management of PCOS has generally improved in the past five years, but remains of low to moderate quality. The technical evidence report and analyses (∼6000 pages) underpins 77 evidence-based and 54 consensus recommendations, with 123 practice points. Key updates include: i) further refinement of individual diagnostic criteria, a simplified diagnostic algorithm and inclusion of anti-Müllerian hormone (AMH) levels as an alternative to ultrasound in adults only; ii) strengthening recognition of broader features of PCOS including metabolic risk factors, cardiovascular disease, sleep apnea, very high prevalence of psychological features, and high risk status for adverse outcomes during pregnancy; iii) emphasizing the poorly recognized, diverse burden of disease and the need for greater healthcare professional education, evidence-based patient information, improved models of care and shared decision making to improve patient experience, alongside greater research; iv) maintained emphasis on healthy lifestyle, emotional wellbeing and quality of life, with awareness and consideration of weight stigma; and v) emphasizing evidence-based medical therapy and cheaper and safer fertility management.Overall, recommendations are strengthened and evidence is improved, but remain generally low to moderate quality. Significantly greater research is now needed in this neglected, yet common condition. Regional health system variation was considered and acknowledged, with a further process for guideline and translation resource adaptation provided.The 2023 International Guideline for the Assessment and Management of PCOS provides clinicians and patients with clear advice on best practice, based on the best available evidence, expert multidisciplinary input and consumer preferences. Research recommendations have been generated and a comprehensive multifaceted dissemination and translation programme supports the Guideline with an integrated evaluation program.This effort was primarily funded by the Australian Government via the National Health Medical Research Council (NHMRC) (APP1171592), supported by a partnership with American Society for Reproductive Medicine, Endocrine Society, European Society for Human Reproduction and Embryology, and the Society for Endocrinology. The Commonwealth Government of Australia also supported Guideline translation through the Medical Research Future Fund (MRFCRI000266). HJT and AM are funded by NHMRC fellowships. JT is funded by a Royal Australasian College of Physicians (RACP) fellowship. Guideline development group members were volunteers. Travel expenses were covered by the sponsoring organizations. Disclosures of interest were strictly managed according to NHMRC policy and are available with the full guideline, technical evidence report, peer review and responses (www.monash.edu/medicine/mchri/pcos). Of named authors HJT, CTT, AD, LM, LR, JBoyle, AM have no conflicts of interest to declare. JL declares grant from Ferring and Merck; consulting fees from Ferring and Titus Health Care; speaker's fees from Ferring; unpaid consultancy for Ferring, Roche Diagnostics and Ansh Labs; and sits on advisory boards for Ferring, Roche Diagnostics, Ansh Labs, and Gedeon Richter. TP declares a grant from Roche; consulting fees from Gedeon Richter and Organon; speaker's fees from Gedeon Richter and Exeltis; travel support from Gedeon Richter and Exeltis; unpaid consultancy for Roche Diagnostics; and sits on advisory boards for Roche Diagnostics. MC declares travels support from Merck; and sits on an advisory board for Merck. JBoivin declares grants from Merck Serono Ltd.; consulting fees from Ferring B.V; speaker's fees from Ferring Arzneimittell GmbH; travel support from Organon; and sits on an advisory board for the Office of Health Economics. RJN has received speaker's fees from Merck and sits on an advisory board for Ferring. AJoham has received speaker's fees from Novo Nordisk and Boehringer Ingelheim. The guideline was peer reviewed by special interest groups across our 39 partner and collaborating organizations, was independently methodologically assessed against AGREEII criteria and was approved by all members of the guideline development groups and by the NHMRC.
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| 8. |
- Teede, Helena J, et al.
(författare)
-
Recommendations From the 2023 International Evidence-based Guideline for the Assessment and Management of Polycystic Ovary Syndrome.
- 2023
-
Ingår i: The Journal of clinical endocrinology and metabolism. - 1945-7197. ; 108:10, s. 2447-2469
-
Tidskriftsartikel (refereegranskat)abstract
- What is the recommended assessment and management of those with polycystic ovary syndrome (PCOS), based on the best available evidence, clinical expertise, and consumer preference?International evidence-based guidelines address prioritized questions and outcomes and include 254 recommendations and practice points, to promote consistent, evidence-based care and improve the experience and health outcomes in PCOS.The 2018 International PCOS Guideline was independently evaluated as high quality and integrated multidisciplinary and consumer perspectives from six continents; it is now used in 196 countries and is widely cited. It was based on best available, but generally very low to low quality, evidence. It applied robust methodological processes and addressed shared priorities. The guideline transitioned from consensus based to evidence-based diagnostic criteria and enhanced accuracy of diagnosis, whilst promoting consistency of care. However, diagnosis is still delayed, the needs of those with PCOS are not being adequately met, evidence quality was low and evidence-practice gaps persist.The 2023 International Evidence-based Guideline update reengaged the 2018 network across professional societies and consumer organizations with multidisciplinary experts and women with PCOS directly involved at all stages. Extensive evidence synthesis was completed. Appraisal of Guidelines for Research and Evaluation-II (AGREEII)-compliant processes were followed. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework was applied across evidence quality, feasibility, acceptability, cost, implementation and ultimately recommendation strength and diversity and inclusion were considered throughout.This summary should be read in conjunction with the full Guideline for detailed participants and methods. Governance included a six-continent international advisory and management committee, five guideline development groups, and paediatric, consumer, and translation committees. Extensive consumer engagement and guideline experts informed the update scope and priorities. Engaged international society-nominated panels included paediatrics, endocrinology, gynaecology, primary care, reproductive endocrinology, obstetrics, psychiatry, psychology, dietetics, exercise physiology, obesity care, public health and other experts, alongside consumers, project management, evidence synthesis, statisticians and translation experts. Thirty-nine professional and consumer organizations covering 71 countries engaged in the process. Twenty meetings and five face-to-face forums over 12 months addressed 58 prioritized clinical questions involving 52 systematic and 3 narrative reviews. Evidence-based recommendations were developed and approved via consensus across five guideline panels, modified based on international feedback and peer review, independently reviewed for methodological rigour, and approved by the Australian Government National Health and Medical Research Council (NHMRC).The evidence in the assessment and management of PCOS has generally improved in the past five years, but remains of low to moderate quality. The technical evidence report and analyses (∼6000 pages) underpins 77 evidence-based and 54 consensus recommendations, with 123 practice points. Key updates include: i) further refinement of individual diagnostic criteria, a simplified diagnostic algorithm and inclusion of anti-Müllerian hormone (AMH) levels as an alternative to ultrasound in adults only; ii) strengthening recognition of broader features of PCOS including metabolic risk factors, cardiovascular disease, sleep apnea, very high prevalence of psychological features, and high risk status for adverse outcomes during pregnancy; iii) emphasizing the poorly recognized, diverse burden of disease and the need for greater healthcare professional education, evidence-based patient information, improved models of care and shared decision making to improve patient experience, alongside greater research; iv) maintained emphasis on healthy lifestyle, emotional wellbeing and quality of life, with awareness and consideration of weight stigma; and v) emphasizing evidence-based medical therapy and cheaper and safer fertility management.Overall, recommendations are strengthened and evidence is improved, but remain generally low to moderate quality. Significantly greater research is now needed in this neglected, yet common condition. Regional health system variation was considered and acknowledged, with a further process for guideline and translation resource adaptation provided.The 2023 International Guideline for the Assessment and Management of PCOS provides clinicians and patients with clear advice on best practice, based on the best available evidence, expert multidisciplinary input and consumer preferences. Research recommendations have been generated and a comprehensive multifaceted dissemination and translation programme supports the Guideline with an integrated evaluation program.This effort was primarily funded by the Australian Government via the National Health Medical Research Council (NHMRC) (APP1171592), supported by a partnership with American Society for Reproductive Medicine, Endocrine Society, European Society for Human Reproduction and Embryology, and the European Society for Endocrinology. The Commonwealth Government of Australia also supported Guideline translation through the Medical Research Future Fund (MRFCRI000266). HJT and AM are funded by NHMRC fellowships. JT is funded by a Royal Australasian College of Physicians (RACP) fellowship. Guideline development group members were volunteers. Travel expenses were covered by the sponsoring organizations. Disclosures of interest were strictly managed according to NHMRC policy and are available with the full guideline, technical evidence report, peer review and responses (www.monash.edu/medicine/mchri/pcos). Of named authors HJT, CTT, AD, LM, LR, JBoyle, AM have no conflicts of interest to declare. JL declares grant from Ferring and Merck; consulting fees from Ferring and Titus Health Care; speaker's fees from Ferring; unpaid consultancy for Ferring, Roche Diagnostics and Ansh Labs; and sits on advisory boards for Ferring, Roche Diagnostics, Ansh Labs, and Gedeon Richter. TP declares a grant from Roche; consulting fees from Gedeon Richter and Organon; speaker's fees from Gedeon Richter and Exeltis; travel support from Gedeon Richter and Exeltis; unpaid consultancy for Roche Diagnostics; and sits on advisory boards for Roche Diagnostics. MC declares travels support from Merck; and sits on an advisory board for Merck. JBoivin declares grants from Merck Serono Ltd.; consulting fees from Ferring B.V; speaker's fees from Ferring Arzneimittell GmbH; travel support from Organon; and sits on an advisory board for the Office of Health Economics. RJN has received speaker's fees from Merck and sits on an advisory board for Ferring. AJoham has received speaker's fees from Novo Nordisk and Boehringer Ingelheim. The guideline was peer reviewed by special interest groups across our 39 partner and collaborating organizations, was independently methodologically assessed against AGREEII criteria and was approved by all members of the guideline development groups and by the NHMRC.
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| 9. |
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| 10. |
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| 11. |
- Åkerberg, Anna, 1974-
(författare)
-
An interactive health technology solution for encouraging physical activity : a first model based on a user perspective
- 2018
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Globally, the level of physical inactivity is increasing. The overall aim of this thesis was to develop and test a first model of an interactive health technology solution (called App&Move) that should encourage physically inactive adults to be more physically active. App&Move was iteratively developed based on the user perspective, a so-called user-centered design. First, available technology was assessed; the validity and reliability of one smartphone pedometer application and one commonly used traditional pedometer were investigated. It was found that none of the investigated pedometers could measure correctly in all investigated situations. However, measurements by a smartphone appli-cation was identified to have high potential when aimed at monitoring physical activity in everyday situations. As the next step, a questionnaire was developed and distributed in central Sweden. The 107 respondents who answered the questionnaire were divided and analyzed in groups of users and non-users of physical activity self-monitoring technology. The results showed that users and non-users of such technology mainly had similar opinions about desirable functions of the technology. To gain further knowledge concerning how to design App&Move, the target group physically inactive non-users participated in focus group interviews. Important results were that the technology should focus on encouragement rather than measurements and that it preferably should be integrated into already existing technology, if possible already owned and worn by the person. A brainstorming workshop confirmed that the smartphone was a suitable platform, and a decision to develop a smartphone application was taken. A first draft of App&Move was developed, focusing on encouragement and measuring everyday activity and exercise in minutes per day. App&Move was based on available physical activity recommendations and strategies for successful behavior change. App&Move was positively received in a user workshop and thereafter iteratively refined and developed based on further user input. App&Move was usability tested in 23 physically inactive adults who used App&Move for four weeks and answered two questionnaires. Three usability aspects, effectiveness, efficiency and satisfaction, were assessed as follows: acceptable, high and medium, and slight increases in activity minutes were observed during the test period. To conclude, this thesis has investigated the user perspective of physical activity self-monitoring technology with a target group of physically inactive adults. Based on these findings, a behavior change application for smartphone, App&Move, was presented. The usability test indicated promising results with respect to usability and indicated an ability to encourage the users to physical activity to some extent.
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| 12. |
- Abbaspour Asadollah, Sara, et al.
(författare)
-
Evaluation of surface EMG-based recognition algorithms for decoding hand movements
- 2019
-
Ingår i: Medical and Biological Engineering and Computing. - : Springer. - 0140-0118 .- 1741-0444. ; 58:1, s. 83-100
-
Tidskriftsartikel (refereegranskat)abstract
- Myoelectric pattern recognition (MPR) to decode limb movements is an important advancement regarding the control of powered prostheses. However, this technology is not yet in wide clinical use. Improvements in MPR could potentially increase the functionality of powered prostheses. To this purpose, offline accuracy and processing time were measured over 44 features using six classifiers with the aim of determining new configurations of features and classifiers to improve the accuracy and response time of prosthetics control. An efficient feature set (FS: waveform length, correlation coefficient, Hjorth Parameters) was found to improve the motion recognition accuracy. Using the proposed FS significantly increased the performance of linear discriminant analysis, K-nearest neighbor, maximum likelihood estimation (MLE), and support vector machine by 5.5%, 5.7%, 6.3%, and 6.2%, respectively, when compared with the Hudgins’ set. Using the FS with MLE provided the largest improvement in offline accuracy over the Hudgins feature set, with minimal effect on the processing time. Among the 44 features tested, logarithmic root mean square and normalized logarithmic energy yielded the highest recognition rates (above 95%). We anticipate that this work will contribute to the development of more accurate surface EMG-based motor decoding systems for the control prosthetic hands. [Figure not available: see fulltext.].
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| 13. |
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| 14. |
- Abbaspour, Saadeh, et al.
(författare)
-
A comparative analysis of hybrid deep learning models for human activity recognition
- 2020
-
Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 20:19
-
Tidskriftsartikel (refereegranskat)abstract
- Recent advances in artificial intelligence and machine learning (ML) led to effective methods and tools for analyzing the human behavior. Human Activity Recognition (HAR) is one of the fields that has seen an explosive research interest among the ML community due to its wide range of applications. HAR is one of the most helpful technology tools to support the elderly’s daily life and to help people suffering from cognitive disorders, Parkinson’s disease, dementia, etc. It is also very useful in areas such as transportation, robotics and sports. Deep learning (DL) is a branch of ML based on complex Artificial Neural Networks (ANNs) that has demonstrated a high level of accuracy and performance in HAR. Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are two types of DL models widely used in the recent years to address the HAR problem. The purpose of this paper is to investigate the effectiveness of their integration in recognizing daily activities, e.g., walking. We analyze four hybrid models that integrate CNNs with four powerful RNNs, i.e., LSTMs, BiLSTMs, GRUs and BiGRUs. The outcomes of our experiments on the PAMAP2 dataset indicate that our proposed hybrid models achieve an outstanding level of performance with respect to several indicative measures, e.g., F-score, accuracy, sensitivity, and specificity. © 2020 by the authors.
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| 15. |
- Abbaspour, Sara, et al.
(författare)
-
A Novel Approach for Removing ECG Interferences from Surface EMG signals Using a Combined ANFIS and Wavelet
- 2016
-
Ingår i: Journal of Electromyography & Kinesiology. - : Elsevier BV. - 1050-6411 .- 1873-5711. ; 26, s. 52-59
-
Tidskriftsartikel (refereegranskat)abstract
- In recent years, the removal of electrocardiogram (ECG) interferences from electromyogram (EMG) signals has been given large consideration. Where the quality of EMG signal is of interest, it is important to remove ECG interferences from EMG signals. In this paper, an efficient method based on a combination of adaptive neuro-fuzzy inference system (ANFIS) and wavelet transform is proposed to effectively eliminate ECG interferences from surface EMG signals. The proposed approach is compared with other common methods such as high-pass filter, artificial neural network, adaptive noise canceller, wavelet transform, subtraction method and ANFIS. It is found that the performance of the proposed ANFIS-wavelet method is superior to the other methods with the signal to noise ratio and relative error of 14.97 dB and 0.02 respectively and a significantly higher correlation coefficient (p < 0.05).
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| 16. |
- Abbaspour, Sara, 1984-, et al.
(författare)
-
ECG Artifact Removal from Surface EMG Signal Using an Automated Method Based on Wavelet-ICA
- 2015
-
Ingår i: Studies in Health Technology and Informatics, Volume 211. - 9781614995159 ; , s. 91-97
-
Konferensbidrag (refereegranskat)abstract
- This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact components from the original EMG signal. Components that correspond to the ECG artifact are then identified by an automated detection algorithm and are subsequently removed using a conventional high pass filter. Finally, the results of the proposed method are compared with wavelet transform, ICA, adaptive filter and empirical mode decomposition-ICA methods. The automated artifact removal method proposed in this study successfully removes the ECG artifacts from EMG signals with a signal to noise ratio value of 9.38 while keeping the distortion of original EMG to a minimum.
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| 17. |
- Abbaspour, Sara, 1984-
(författare)
-
Electromyogram Signal Enhancement and Upper-Limb Myoelectric Pattern Recognition
- 2019
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Losing a limb causes difficulties in our daily life. To regain the ability to live an independent life, artificial limbs have been developed. Hand prostheses belong to a group of artificial limbs that can be controlled by the user through the activity of the remnant muscles above the amputation. Electromyogram (EMG) is one of the sources that can be used for control methods for hand prostheses. Surface EMGs are powerful, non-invasive tools that provide information about neuromuscular activity of the subjected muscle, which has been essential to its use as a source of control for prosthetic limbs. However, the complexity of this signal introduces a big challenge to its applications. EMG pattern recognition to decode different limb movements is an important advancement regarding the control of powered prostheses. It has the potential to enable the control of powered prostheses using the generated EMG by muscular contractions as an input. However, its use has yet to be transitioned into wide clinical use. Different algorithms have been developed in state of the art to decode different movements; however, the challenge still lies in different stages of a successful hand gesture recognition and improvements in these areas could potentially increase the functionality of powered prostheses. This thesis firstly focuses on improving the EMG signal’s quality by proposing novel and advanced filtering techniques. Four efficient approaches (adaptive neuro-fuzzy inference system-wavelet, artificial neural network-wavelet, adaptive subtraction and automated independent component analysis-wavelet) are proposed to improve the filtering process of surface EMG signals and effectively eliminate ECG interferences. Then, the offline performance of different EMG-based recognition algorithms for classifying different hand movements are evaluated with the aim of obtaining new myoelectric control configurations that improves the recognition stage. Afterwards, to gain proper insight on the implementation of myoelectric pattern recognition, a wide range of myoelectric pattern recognition algorithms are investigated in real time. The experimental result on 15 healthy volunteers suggests that linear discriminant analysis (LDA) and maximum likelihood estimation (MLE) outperform other classifiers. The real-time investigation illustrates that in addition to the LDA and MLE, multilayer perceptron also outperforms the other algorithms when compared using classification accuracy and completion rate.
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| 18. |
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| 19. |
- Abbaspour, Sara, et al.
(författare)
-
Evaluation of wavelet based methods in removing motion artifact from ECG signal
- 2015
-
Ingår i: IFMBE Proceedings. - Cham : Springer International Publishing. - 9783319129662 ; , s. 1-4
-
Konferensbidrag (refereegranskat)abstract
- Accurate recording and precise analysis of the electrocardiogram (ECG) signals are crucial in the pathophysiological study and clinical treatment. These recordings are often corrupted by different artifacts. The aim of this study is to propose two different methods, wavelet transform based on nonlinear thresholding and a combination method using wavelet and independent component analysis (ICA), to remove motion artifact from ECG signals. To evaluate the performance of the proposed methods, the developed techniques are applied to the real and simulated ECG data. The results of this evaluation are presented using quantitative and qualitative criteria. The results show that the proposed methods are able to reduce motion artifacts in ECG signals. Signal to noise ratio (SNR) of the wavelet technique is equal to 13.85. The wavelet-ICA method performed better with SNR of 14.23.
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| 20. |
- Abbaspour, Sara, 1984-
(författare)
-
Proposing Combined Approaches to Remove ECG Artifacts from Surface EMG Signals
- 2015
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Electromyography (EMG) is a tool routinely used for a variety of applications in a very large breadth of disciplines. However, this signal is inevitably contaminated by various artifacts originated from different sources. Electrical activity of heart muscles, electrocardiogram (ECG), is one of sources which affects the EMG signals due to the proximity of the collection sites to the heart and makes its analysis non-reliable. Different methods have been proposed to remove ECG artifacts from surface EMG signals; however, in spite of numerous attempts to eliminate or reduce this artifact, the problem of accurate and effective de-noising of EMG still remains a challenge. In this study common methods such as high pass filter (HPF), gating method, spike clipping, hybrid technique, template subtraction, independent component analysis (ICA), wavelet transform, wavelet-ICA, artificial neural network (ANN), and adaptive noise canceller (ANC) and adaptive neuro-fuzzy inference system (ANFIS) are used to remove ECG artifacts from surface EMG signals and their accuracy and effectiveness is investigated. HPF, gating method and spike clipping are fast; however they remove useful information from EMG signals. Hybrid technique and ANC are time consuming. Template subtraction requires predetermined QRS pattern. Using wavelet transform some artifacts remain in the original signal and part of the desired signal is removed. ICA requires multi-channel signals. Wavelet-ICA approach does not require multi-channel signals; however, it is user-dependent. ANN and ANFIS have good performance, but it is possible to improve their results by combining them with other techniques. For some applications of EMG signals such as rehabilitation, motion control and motion prediction, the quality of EMG signals is very important. Furthermore, the artifact removal methods need to be online and automatic. Hence, efficient methods such as ANN-wavelet, adaptive subtraction and automated wavelet-ICA are proposed to effectively eliminate ECG artifacts from surface EMG signals. To compare the results of the investigated methods and the proposed methods in this study, clean EMG signals from biceps and deltoid muscles and ECG artifacts from pectoralis major muscle are recorded from five healthy subjects to create 10 channels of contaminated EMG signals by adding the recorded ECG artifacts to the clean EMG signals. The artifact removal methods are also applied to the 10 channels of real contaminated EMG signals from pectoralis major muscle of the left side. Evaluation criteria such as signal to noise ratio, relative error, correlation coefficient, elapsed time and power spectrum density are used to evaluate the performance of the proposed methods. It is found that the performance of the proposed ANN-wavelet method is superior to the other methods with a signal to noise ratio, relative error and correlation coefficient of 15.53, 0.01 and 0.98 respectively.
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| 21. |
- Abbaspour, S., et al.
(författare)
-
Real-Time and Offline Evaluation of Myoelectric Pattern Recognition for the Decoding of Hand Movements
- 2021
-
Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:16
-
Tidskriftsartikel (refereegranskat)abstract
- Pattern recognition algorithms have been widely used to map surface electromyographic signals to target movements as a source for prosthetic control. However, most investigations have been conducted offline by performing the analysis on pre-recorded datasets. While real-time data analysis (i.e., classification when new data becomes available, with limits on latency under 200-300 milliseconds) plays an important role in the control of prosthetics, less knowledge has been gained with respect to real-time performance. Recent literature has underscored the differences between offline classification accuracy, the most common performance metric, and the usability of upper limb prostheses. Therefore, a comparative offline and real-time performance analysis between common algorithms had yet to be performed. In this study, we investigated the offline and real-time performance of nine different classification algorithms, decoding ten individual hand and wrist movements. Surface myoelectric signals were recorded from fifteen able-bodied subjects while performing the ten movements. The offline decoding demonstrated that linear discriminant analysis (LDA) and maximum likelihood estimation (MLE) significantly (p < 0.05) outperformed other classifiers, with an average classification accuracy of above 97%. On the other hand, the real-time investigation revealed that, in addition to the LDA and MLE, multilayer perceptron also outperformed the other algorithms and achieved a classification accuracy and completion rate of above 68% and 69%, respectively.
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| 22. |
- Abdelakram, Hafid, et al.
(författare)
-
Impact of Activities in Daily Living on Electrical Bioimpedance Measurements for Bladder Monitoring
- 2023
-
Konferensbidrag (refereegranskat)abstract
- Accurate bladder monitoring is critical in the management of conditions such as urinary incontinence, voiding dysfunction, and spinal cord injuries. Electrical bioimpedance (EBI) has emerged as a cost-effective and non-invasive approach to monitoring bladder activity in daily life, with particular relevance to patient groups who require measurement of bladder urine volume (BUV) to prevent urinary leakage. However, the impact of activities in daily living (ADLs) on EBI measurements remains incompletely characterized. In this study, we investigated the impact of normal ADLs such as sitting, standing, and walking on EBI measurements using the MAX30009evkit system with four electrodes placed on the lower abdominal area. We developed an algorithm to identify artifacts caused by the different activities from the EBI signals. Our findings demonstrate that various physical activities clearly affected the EBI measurements, indicating the necessity of considering them during bladder monitoring with EBI technology performed during physical activity (or normal ADLs). We also observed that several specific activities could be distinguished based on their impedance values and waveform shapes. Thus, our results provide a better understanding of the impact of physical activity on EBI measurements and highlight the importance of considering such physical activities during EBI measurements in order to enhance the reliability and effectiveness of EBI technology for bladder monitoring.
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| 23. |
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| 24. |
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| 25. |
- Abdullah, Saad, et al.
(författare)
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A Novel Fiducial Point Extraction Algorithm to Detect C and D Points from the Acceleration Photoplethysmogram (CnD)
- 2023
-
Ingår i: Electronics. - : MDPI AG. - 2079-9292. ; 12:5
-
Tidskriftsartikel (refereegranskat)abstract
- The extraction of relevant features from the photoplethysmography signal for estimating certain physiological parameters is a challenging task. Various feature extraction methods have been proposed in the literature. In this study, we present a novel fiducial point extraction algorithm to detect c and d points from the acceleration photoplethysmogram (APG), namely “CnD”. The algorithm allows for the application of various pre-processing techniques, such as filtering, smoothing, and removing baseline drift; the possibility of calculating first, second, and third photoplethysmography derivatives; and the implementation of algorithms for detecting and highlighting APG fiducial points. An evaluation of the CnD indicated a high level of accuracy in the algorithm’s ability to identify fiducial points. Out of 438 APG fiducial c and d points, the algorithm accurately identified 434 points, resulting in an accuracy rate of 99%. This level of accuracy was consistent across all the test cases, with low error rates. These findings indicate that the algorithm has a high potential for use in practical applications as a reliable method for detecting fiducial points. Thereby, it provides a valuable new resource for researchers and healthcare professionals working in the analysis of photoplethysmography signals.
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| 26. |
- Abdullah, Saad, et al.
(författare)
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Machine Learning-Based Classification of Hypertension using CnD Features from Acceleration Photoplethysmography and Clinical Parameters
- 2023
-
Ingår i: Proceedings - IEEE Symposium on Computer-Based Medical Systems. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350312249 ; , s. 923-924
-
Konferensbidrag (refereegranskat)abstract
- Cardiovascular diseases (CVDs) are a leading cause of death worldwide, and hypertension is a major risk factor for acquiring CVDs. Early detection and treatment of hypertension can significantly reduce the risk of developing CVDs and related complications. In this study, a linear SVM machine learning model was used to classify subjects as normal or at different stages of hypertension. The features combined statistical parameters derived from the acceleration plethysmography waveforms and clinical parameters extracted from a publicly available dataset. The model achieved an overall accuracy of 87.50% on the validation dataset and 95.35% on the test dataset. The model's true positive rate and positive predictivity was high in all classes, indicating a high accuracy, and precision. This study represents the first attempt to classify cardiovascular conditions using a combination of acceleration photoplethysmogram (APG) features and clinical parameters The study demonstrates the potential of APG analysis as a valuable tool for early detection of hypertension.
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| 27. |
- Abdullah, Saad, et al.
(författare)
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PPGFeat: a novel MATLAB toolbox for extracting PPG fiducial points
- 2023
-
Ingår i: Frontiers in Bioengineering and Biotechnology. - 2296-4185. ; 11
-
Tidskriftsartikel (refereegranskat)abstract
- Photoplethysmography is a non-invasive technique used for measuring several vital signs and for the identification of individuals with an increased disease risk. Its principle of work is based on detecting changes in blood volume in the microvasculature of the skin through the absorption of light. The extraction of relevant features from the photoplethysmography signal for estimating certain physiological parameters is a challenging task, where various feature extraction methods have been proposed in the literature. In this work, we present PPGFeat, a novel MATLAB toolbox supporting the analysis of raw photoplethysmography waveform data. PPGFeat allows for the application of various preprocessing techniques, such as filtering, smoothing, and removal of baseline drift; the calculation of photoplethysmography derivatives; and the implementation of algorithms for detecting and highlighting photoplethysmography fiducial points. PPGFeat includes a graphical user interface allowing users to perform various operations on photoplethysmography signals and to identify, and if required also adjust, the fiducial points. Evaluating the PPGFeat’s performance in identifying the fiducial points present in the publicly available PPG-BP dataset, resulted in an overall accuracy of 99% and 3038/3066 fiducial points were correctly identified. PPGFeat significantly reduces the risk of errors in identifying inaccurate fiducial points. Thereby, it is providing a valuable new resource for researchers for the analysis of photoplethysmography signals.
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| 28. |
- Afifi, S., et al.
(författare)
-
A Novel Medical Device for Early Detection of Melanoma
- 2019
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Ingår i: Studies in Health Technology and Informatics. - : NLM (Medline). - 0926-9630 .- 1879-8365. ; 261, s. 122-127
-
Tidskriftsartikel (refereegranskat)abstract
- Melanoma is the deadliest form of skin cancer. Early detection of melanoma is vital, as it helps in decreasing the death rate as well as treatment costs. Dermatologists are using image-based diagnostic tools to assist them in decision-making and detecting melanoma at an early stage. We aim to develop a novel handheld medical scanning device dedicated to early detection of melanoma at the primary healthcare with low cost and high performance. However, developing this particular device is very challenging due to the complicated computations required by the embedded diagnosis system. In this paper, we propose a hardware-friendly design for implementing an embedded system by exploiting the recent hardware advances in reconfigurable computing. The developed embedded system achieved optimized implementation results for the hardware resource utilization, power consumption, detection speed and processing time with high classification accuracy rate using real data for melanoma detection. Consequently, the proposed embedded diagnosis system meets the critical embedded systems constraints, which is capable for integration towards a cost- and energy-efficient medical device for early detection of melanoma.
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| 29. |
- Ahl, Matilda, et al.
(författare)
-
Inflammatory reaction in the retina after focal non-convulsive status epilepticus in mice investigated with high resolution magnetic resonance and diffusion tensor imaging
- 2021
-
Ingår i: Epilepsy Research. - : Elsevier. - 0920-1211 .- 1872-6844. ; 176
-
Tidskriftsartikel (refereegranskat)abstract
- Pathophysiological consequences of focal non-convulsive status epilepticus (fNCSE) have been difficult to demonstrate in humans. In rats fNCSE pathology has been identified in the eyes. Here we evaluated the use of high-resolution 7 T structural T1-weighted magnetic resonance imaging (MRI) and 9.4 T diffusion tensor imaging (DTI) for detecting hippocampal fNCSE-induced retinal pathology ex vivo in mice. Seven weeks post-fNCSE, increased number of Iba1+ microglia were evident in the retina ipsilateral to the hemisphere with fNCSE, and morphologically more activated microglia were found in both ipsi- and contralateral retina compared to non-stimulated control mice. T1-weighted intensity measurements of the contralateral retina showed a minor increase within the outer nuclear and plexiform layers of the lateral retina. T1-weighted measurements were not performed in the ipsilateral retina due to technical difficulties. DTI fractional anisotropy(FA) values were discretely altered in the lateral part of the ipsilateral retina and unaltered in the contralateral retina. No changes were observed in the distal part of the optic nerve. The sensitivity of both imaging techniques for identifying larger retinal alteration was confirmed ex vivo in retinitis pigmentosa mice where a substantial neurodegeneration of the outer retinal layers is evident. With MR imaging a 50 % decrease in DTI FA values and significantly thinner retina in T1-weighted images were detected. We conclude that retinal pathology after fNCSE in mice is subtle and present bilaterally. High-resolution T1-weighted MRI and DTI independently did not detect the entire pathological retinal changes after fNCSE, but the combination of the two techniques indicated minor patchy structural changes.
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| 30. |
- Ahmed, Mobyen Uddin, et al.
(författare)
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A Generic System-level Framework for Self-Serve Health Monitoring System through Internet of Things(IoT)
- 2015
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Ingår i: Studies in Health Technology and Informatics, Volume 211. - 9781614995159 ; , s. 305-307
-
Konferensbidrag (refereegranskat)abstract
- Sensor data are traveling from sensors to a remote server, data is analysed remotely in a distributed manner, and health status of a user is presented in real-time. This paper presents a generic system-level framework for a self-served health monitoring system through the Internet of Things (IoT) to facilities an efficient sensor data management.
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| 31. |
- Ahmed, Mobyen Uddin, et al.
(författare)
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An Overview on the Internet of Things for Health Monitoring Systems
- 2016
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Ingår i: 2nd EAI International Conference on IoT Technologies for HealthCare HealthyIoT2015. - Cham : Springer International Publishing. ; , s. 429-436
-
Konferensbidrag (refereegranskat)abstract
- The aging population and the increasing healthcare cost in hospitals are spurring the advent of remote health monitoring systems. Advances in physiological sensing devices and the emergence of reliable low-power wireless network technologies have enabled the design of remote health monitoring systems. The next generation Internet, commonly referred to as Internet of Things (IoT), depicts a world populated by devices that are able to sense, process and react via the Internet. Thus, we envision health monitoring systems that support Internet connection and use this connectivity to enable better and more reliable services. This paper presents an overview on existing health monitoring systems, considering the IoT vision. We focus on recent trends and the development of health monitoring systems in terms of: (1) health parameters, (2) frameworks, (3) wireless communication, and (4) security issues. We also identify the main limitations, requirements and advantages within these systems.
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| 32. |
- Ahmed, Mobyen Uddin, et al.
(författare)
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Healthcare Service at Home : An Intelligent Health Monitoring System for Elderly
- 2015
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Ingår i: Medicinteknikdagarna 2015 MFT 2015.
-
Konferensbidrag (refereegranskat)abstract
- This paper presents an intelligent healthcare service to support active ageing by assisting seniors to participate in regular monitoring of elderly’s health condition. The proposed system is applicable to use in home environment and offers a self-service approach to monitor elderly’s health condition. According to the evaluation, the proposed system shows its necessity, competence and usefulness.
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| 33. |
- Ahmed, Mobyen Uddin, et al.
(författare)
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Intelligent Stress Management System
- 2009
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Ingår i: Medicinteknikdagarna 2009.
-
Konferensbidrag (refereegranskat)abstract
- Today, in our daily life we are subjected to a wide range of pressures. When the pressures exceed the extent that we are able to deal with then stress is trigged. High level of stress may cause serious health problems i.e. it reduces awareness of bodily symptoms. So, people may first notice it weeks or months later meanwhile the stress could cause more serious effect in the body and health. A difficult issue in stress management is to use biomedical sensor signals in the diagnosis and treatment of stress. This paper presents a case-based system that assists a clinician in diagnosis and treatment of stress. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques such as textual information retrieval, rule-based reasoning (RBR), and fuzzy logic have been combined together with case-based reasoning to enable more reliable and efficient diagnosis and treatment of stress. The performance has been validated implementing a research prototype and close collaboration with experts.
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| 34. |
- Ahmed, Mobyen Uddin, 1976-, et al.
(författare)
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Multi-parameter Sensing Platform in ESS-H and E-care@home
- 2017
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Ingår i: Joint conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) EMBEC & NBC’17.
-
Konferensbidrag (refereegranskat)abstract
- Considering the population of ageing, health monitoring of elderly at home have the possibility for a person to keep track on his/her health status, e.g. decreased mobility in a personal environment. This also shows the potential of real-time decision support, early detection of symptoms, following of health trends and context awareness [1]. The ongoing projects Embedded Sensor for Health (ESS-H)1 and E-care@home2 are focusing on health monitoring of elderly at home. This paper presents the implementation of multi-parameter sensing on an Android platform. The objectives are, both to follow health trends and to enabling real time monitoring.
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| 35. |
- Ahmed, Mobyen Uddin, 1976-, et al.
(författare)
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Run-Time Assurance for the E-care@home System
- 2018
-
Ingår i: Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 225). - Cham : Springer International Publishing. - 9783319762128 - 9783319762135 ; , s. 107-110
-
Konferensbidrag (refereegranskat)abstract
- This paper presents the design and implementation of the software for a run-time assurance infrastructure in the E-care@home system. An experimental evaluation is conducted to verify that the run-time assurance infrastructure is functioning correctly, and to enable detecting performance degradation in experimental IoT network deployments within the context of E-care@home. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
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| 36. |
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| 37. |
- Andersson, Anders, et al.
(författare)
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Effects of Tobacco Smoke on IL-16 in CD8+ Cells from Human Airways and Blood: a Key Role for Oxygen Free Radicals?
- 2011
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Ingår i: AJP - Lung cellular and molecular physiology. - : American Physiological Society. - 1522-1504. ; 300:1
-
Tidskriftsartikel (refereegranskat)abstract
- Chronic exposure to tobacco smoke leads to an increase in the frequency of infections and in CD8(+) and CD4(+)cells as well as the CD4(+) chemo-attractant cytokine IL-16 in the airways. Here, we investigated whether tobacco smoke depletes intracellular IL-16 protein and inhibits de novo production of IL-16 in CD8(+) cells from human airways and blood, while at the same time increasing extracellular IL-16 and whether oxygen free radicals (OFR) are involved. Intracellular IL-16 protein in CD8(+) cells and mRNA in all cells was decreased in bronchoalveolar lavage (BAL) samples from chronic smokers. This was also the case in human blood CD8(+) cells exposed to water-soluble tobacco smoke components in vitro; in which oxidized proteins were markedly increased. Extracellular IL-16 protein was increased in cell-free BAL fluid from chronic smokers and in human blood CD8(+) cells exposed to water-soluble tobacco smoke components in vitro. This was not observed in occasional smokers after short-term exposure to tobacco smoke. A marker of activation (CD69) was slightly increased whereas other markers of key cellular functions (membrane integrity, apoptosis and proliferation) in human blood CD8(+) cells in vitro were negatively affected by water-soluble tobacco smoke components. An OFR scavenger prevented these effects whereas a protein synthesis inhibitor, a beta-adrenoceptor, a glucocorticoid receptor agonist, a phosphodiesterase, a calcineurin phosphatase and a caspase-3 inhibitor did not. In conclusion, tobacco smoke depletes preformed intracellular IL-16 protein, inhibits its de novo synthesis and distorts key cellular functions in human CD8(+) cells. OFR may play a key role in this context.
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| 38. |
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| 39. |
- Antão, Laura H., et al.
(författare)
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Climate change reshuffles northern species within their niches
- 2022
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Ingår i: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 12:6, s. 587-592
-
Tidskriftsartikel (refereegranskat)abstract
- Climate change is a pervasive threat to biodiversity. While range shifts are a known consequence of climate warming contributing to regional community change, less is known about how species’ positions shift within their climatic niches. Furthermore, whether the relative importance of different climatic variables prompting such shifts varies with changing climate remains unclear. Here we analysed four decades of data for 1,478 species of birds, mammals, butterflies, moths, plants and phytoplankton along a 1,200 km high latitudinal gradient. The relative importance of climatic drivers varied non-uniformly with progressing climate change. While species turnover among decades was limited, the relative position of species within their climatic niche shifted substantially. A greater proportion of species responded to climatic change at higher latitudes, where changes were stronger. These diverging climate imprints restructure a full biome, making it difficult to generalize biodiversity responses and raising concerns about ecosystem integrity in the face of accelerating climate change.
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| 40. |
- Ask, Maria, et al.
(författare)
-
The Innovative Exploration Drilling and Data Acquisition Research School
- 2021
-
Ingår i: NSG2021 27th European Meeting of Environmental and Engineering Geophysics. - : European Association of Geoscientists and Engineers.
-
Konferensbidrag (refereegranskat)abstract
- The Innovative Exploration Drilling and Data Acquisition Research School (I-EDDA-RS) is aimed at educating emerging scientists and engineers in on-site drilling and geoscientific investigation technology for mining. I-EDDA-RS consists if a consortium of scientists and specialists from six universities and research institutes in Germany and Sweden. A central component of the research school is that the courses have hands-on components at drill sites, boreholes and repositories. In addition, a course on entrepreneurial skills required in the exploration industry is also included in I-EDDA-RS. The arrival of the Covid-19 pandemic resulted in altered plans. Instead of offering ten courses with strong field work, practical, and entrepreneurial components during 2020, four courses via distant learning were offered. While this was disappointing in many aspects, two of the courses attracted a larger group of students from a wider part of the world than original envisioned. Outreach via on-line and open webinars is also a route to explore, as a complement to meetings and conferences in real life. The I-EDDA-RS courses in 2021 welcomes students at MSc & PhD level, as well as experienced professionals for lifelong learning (c.f. https://www.iedda.eu/rs). The form and type of teaching is to be determined.
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| 41. |
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| 42. |
- Ask, Per, et al.
(författare)
-
NovaMedTech - A regional program for supporting new medical technologies in personalized health care
- 2012
-
Ingår i: Studies in Health Technology and Informatics. - 9781614990680 ; 177, s. 71-5
-
Konferensbidrag (refereegranskat)abstract
- NovaMedTech is an initiative funded from EU structural funds for supporting new medical technologies for personalized health care. It aims at bringing these technologies into clinical use and to the health care market. The program has participants from health care, industry and academia in East middle Sweden. The first three year period of the program was successful in terms of product concepts tried clinically, and number of products brought to a commercialization phase. Further, the program has led to a large number of scientific publications. Among projects supported, we can mention: Intelligent sensor networks; A digital pen to collect medical information about health status from patients; A web-based intelligent stethoscope; Methodologies to measure local blood flow and nutrition using optical techniques; Blood flow assessment from ankle pressure measurements; Technologies for pressure ulcer prevention; An IR thermometer for improved accuracy; A technique that identifies individuals prone to commit suicide among depressed patients; Detection of infectious disease using an electronic nose; Identification of the lactate threshold from breath; Obesity measurements using special software and MR camera; and An optical probe guided tumor resection. During the present three years period emphasis will be on entrepreneurial activities supporting the commercialization and bringing products to the market.
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| 43. |
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| 44. |
- Aspholm-Hurtig, Marina, et al.
(författare)
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Functional adaptation of BabA, the H. pylori ABO blood group antigen binding adhesin.
- 2004
-
Ingår i: Science (New York, N.Y.). - : American Association for the Advancement of Science (AAAS). - 1095-9203 .- 0036-8075. ; 305:5683, s. 519-22
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Tidskriftsartikel (refereegranskat)abstract
- Adherence by Helicobacter pylori increases the risk of gastric disease. Here, we report that more than 95% of strains that bind fucosylated blood group antigen bind A, B, and O antigens (generalists), whereas 60% of adherent South American Amerindian strains bind blood group O antigens best (specialists). This specialization coincides with the unique predominance of blood group O in these Amerindians. Strains differed about 1500-fold in binding affinities, and diversifying selection was evident in babA sequences. We propose that cycles of selection for increased and decreased bacterial adherence contribute to babA diversity and that these cycles have led to gradual replacement of generalist binding by specialist binding in blood group O-dominant human populations.
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| 45. |
- Baig, M. M., et al.
(författare)
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A systematic review of rapid response applications based on early warning score for early detection of inpatient deterioration
- 2021
-
Ingår i: Informatics for Health and Social Care. - : Taylor and Francis Ltd.. - 1753-8157 .- 1753-8165. ; 46:2, s. 148-157
-
Tidskriftsartikel (refereegranskat)abstract
- Aim: The aim of this study was to investigate the effectiveness of current rapid response applications available in acute care settings for escalation of patient deterioration. Current challenges and barriers, as well as key recommendations, were also discussed. Methods: We adopted PRISMA review methodology and screened a total of 559 articles. After considering the eligibility and selection criteria, we selected 13 articles published between 2015 and 2019. The selection criteria were based on the inclusion of studies that report on the advancement made to the current practice for providing rapid response to the patient deterioration in acute care settings. Results: We found that current rapid response applications are complicated and time-consuming for detecting inpatient deterioration. Existing applications are either siloed or challenging to use, where clinicians are required to move between two or three different applications to complete an end-to-end patient escalation workflow–from vital signs collection to escalation of deteriorating patients. We found significant differences in escalation and responses when using an electronic tool compared to the manual approach. Moreover, encouraging results were reported in extensive documentation of vital signs and timely alerts for patient deterioration. Conclusion: The electronic vital signs monitoring applications are proved to be efficient and clinically suitable if they are user-friendly and interoperable. As an outcome, several key recommendations and features were identified that would be crucial to the successful implementation of any rapid response system in all clinical settings.
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| 46. |
- Baig, M. M., et al.
(författare)
-
A Systematic Review of Wearable Patient Monitoring Systems – Current Challenges and Opportunities for Clinical Adoption
- 2017
-
Ingår i: Journal of medical systems. - : Springer New York LLC. - 0148-5598 .- 1573-689X. ; 41:7
-
Tidskriftsartikel (refereegranskat)abstract
- The aim of this review is to investigate barriers and challenges of wearable patient monitoring (WPM) solutions adopted by clinicians in acute, as well as in community, care settings. Currently, healthcare providers are coping with ever-growing healthcare challenges including an ageing population, chronic diseases, the cost of hospitalization, and the risk of medical errors. WPM systems are a potential solution for addressing some of these challenges by enabling advanced sensors, wearable technology, and secure and effective communication platforms between the clinicians and patients. A total of 791 articles were screened and 20 were selected for this review. The most common publication venue was conference proceedings (13, 54%). This review only considered recent studies published between 2015 and 2017. The identified studies involved chronic conditions (6, 30%), rehabilitation (7, 35%), cardiovascular diseases (4, 20%), falls (2, 10%) and mental health (1, 5%). Most studies focussed on the system aspects of WPM solutions including advanced sensors, wireless data collection, communication platform and clinical usability based on a specific area or disease. The current studies are progressing with localized sensor-software integration to solve a specific use-case/health area using non-scalable and ‘silo’ solutions. There is further work required regarding interoperability and clinical acceptance challenges. The advancement of wearable technology and possibilities of using machine learning and artificial intelligence in healthcare is a concept that has been investigated by many studies. We believe future patient monitoring and medical treatments will build upon efficient and affordable solutions of wearable technology.
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| 47. |
- Baig, M. M., et al.
(författare)
-
Advanced decision support system for older adults
- 2015
-
Ingår i: Studies in Health Technology and Informatics, vol. 211. - 9781614995159 ; , s. 235-240
-
Konferensbidrag (refereegranskat)abstract
- Decision support systems are rapidly becoming part of today's healthcare delivery. The paradigm has shifted from traditional and manual recording to computer-based electronic records and, further, to handheld devices as versatile and innovative healthcare monitoring systems. The current study focuses on interpreting multiple physical signs and early warning for hospitalized older adults so that severe consequences can be minimized. Data from a total of 30 patients have been collated in New Zealand Hospitals under local and national ethics approvals. The system records blood pressure, heart rate (pulse), oxygen saturation (SpO2), ear temperature and blood glucose levels from hospitalized patients and transfers this information to a web-based software application for remote monitoring and further interpretation. Ultimately, this system is aimed to achieve a high level of agreement with clinicians' interpretation when assessing specific physical signs such as bradycardia, tachycardia, hypertension, hypotension, hypoxemia, fever and hypothermia and to generate early warnings.
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| 48. |
- Baig, Mirza Mansoor, et al.
(författare)
-
Clinical decision support systems in hospital care using ubiquitous devices : Current issues and challenges
- 2019
-
Ingår i: Health Informatics Journal. - : SAGE PUBLICATIONS INC. - 1460-4582 .- 1741-2811. ; 25:3, s. 1091-1104
-
Tidskriftsartikel (refereegranskat)abstract
- Supporting clinicians in decision making using advanced technologies has been an active research area in biomedical engineering during the past years. Among a wide range of ubiquitous systems, smartphone applications have been increasingly developed in healthcare settings to help clinicians as well as patients. Today, many smartphone applications, from basic data analysis to advanced patient monitoring, are available to clinicians and patients. Such applications are now increasingly integrating into healthcare for clinical decision support, and therefore, concerns around accuracy, stability, and dependency of these applications are rising. In addition, lack of attention to the clinicians' acceptability, as well as the low impact on the medical professionals' decision making, are posing more serious issues on the acceptability of smartphone applications. This article reviews smartphone-based decision support applications, focusing on hospital care settings and their overall impact of these applications on the wider clinical workflow. Additionally, key challenges and barriers of the current ubiquitous device-based healthcare applications are identified. Finally, this article addresses current challenges, future directions, and the adoption of mobile healthcare applications.
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| 49. |
- Baig, M. M., et al.
(författare)
-
Early Detection of Prediabetes and T2DM Using Wearable Sensors and Internet-of-Things-Based Monitoring Applications
- 2021
-
Ingår i: Applied Clinical Informatics. - : Georg Thieme Verlag. - 1869-0327. ; 12:1, s. 1-9
-
Tidskriftsartikel (refereegranskat)abstract
- Background Prediabetes and type 2 diabetes mellitus (T2DM) are one of the major long-term health conditions affecting global healthcare delivery. One of the few effective approaches is to actively manage diabetes via a healthy and active lifestyle. Objectives This research is focused on early detection of prediabetes and T2DM using wearable technology and Internet-of-Things-based monitoring applications. Methods We developed an artificial intelligence model based on adaptive neuro-fuzzy inference to detect prediabetes and T2DM via individualized monitoring. The key contributing factors to the proposed model include heart rate, heart rate variability, breathing rate, breathing volume, and activity data (steps, cadence, and calories). The data was collected using an advanced wearable body vest and combined with manual recordings of blood glucose, height, weight, age, and sex. The model analyzed the data alongside a clinical knowledgebase. Fuzzy rules were used to establish baseline values via existing interventions, clinical guidelines, and protocols. Results The proposed model was tested and validated using Kappa analysis and achieved an overall agreement of 91%. Conclusion We also present a 2-year follow-up observation from the prediction results of the original model. Moreover, the diabetic profile of a participant using M-health applications and a wearable vest (smart shirt) improved when compared to the traditional/routine practice.
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| 50. |
- Baig, M. M., et al.
(författare)
-
Machine learning-based clinical decision support system for early diagnosis from real-time physiological data
- 2016
-
Ingår i: Proceedings/TENCON. - : Institute of Electrical and Electronics Engineers Inc.. - 9781509025961 ; , s. 2943-2946
-
Konferensbidrag (refereegranskat)abstract
- This research aims to design a self-organizing decision support system for early diagnosis of key physiological events. The proposed system consists of pre-processing, clustering and diagnostic system, based on self-organizing fuzzy logic modeling. The clustering technique was employed with empirical pattern analysis, particularly when the information available is incomplete or the data model is affected by vagueness, which is mostly the case with medical/clinical data. Clustering module can be viewed as unsupervised learning from a given dataset. This module partitions the patient vital signs to identify the key relationships, patterns and clusters among the medical data. Secondly, it uses self-organizing fuzzy logic modeling for early symptom and event detection. Based on the clustering outcome, when detecting abnormal signs, a high level of agreement was observed between system interpretation and human expert diagnosis of the physiological events and signs. © 2016 IEEE.
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