Journal of Medical Signals & Sensors最新文献_第10页

A Fast Approximate Method for Predicting the Behavior of Auditory Nerve Fibers and the Evoked Compound Action Potential (ECAP) Signal. 听觉神经纤维行为及诱发复合动作电位(ECAP)信号的快速近似预测方法。

Journal of Medical Signals & Sensors Pub Date : 2021-07-21 eCollection Date: 2021-07-01 DOI: 10.4103/jmss.JMSS_28_20

Azam Ghanaei, S Mohammad P Firoozabadi, Hamed Sadjedi

{"title":"A Fast Approximate Method for Predicting the Behavior of Auditory Nerve Fibers and the Evoked Compound Action Potential (ECAP) Signal.","authors":"Azam Ghanaei, S Mohammad P Firoozabadi, Hamed Sadjedi","doi":"10.4103/jmss.JMSS_28_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_28_20","url":null,"abstract":"Background: The goal of the current research is to develop a model based on computer simulations which describes both the behavior of the auditory nerve fibers and the cochlear implant system as a rehabilitation device.Methods: The approximate method was proposed as a low error and fast tool for predicting the behavior of auditory nerve fibers as well as the evoked compound action potential (ECAP) signal. In accurate methods every fiber is simulated; whereas, in approximate method information related to the response of every fiber and its characteristics such as the activation threshold of cochlear fibers are saved and interpolated to predict the behavior of a set of nerve fibers.Results: The approximate model can predict and analyze different stimulation techniques. Although precision is reduced to <1.66% of the accurate method, the required execution time for simulation is reduced by more than 98%.Conclusion: The amplitudes of the ECAP signal and the growth function were investigated by changing the parameters of the approximate model including geometrical parameters, electrical, and temporal parameters. In practice, an audiologist can tune the stimulation parameters to reach an effective restoration of the acoustic signal.","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 3","pages":"169-176"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/58/57/JMSS-11-169.PMC8382029.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39371684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Design and Development Armband Vital Sign Monitor for Health-Care Monitoring. 健康监护臂带生命体征监测仪的设计与开发。

Journal of Medical Signals & Sensors Pub Date : 2021-07-21 eCollection Date: 2021-07-01 DOI: 10.4103/jmss.JMSS_29_20

Sugondo Hadiyoso, Rohmat Tulloh, Yuyun Siti Rohmah, Akhmad Alfaruq

{"title":"Design and Development Armband Vital Sign Monitor for Health-Care Monitoring.","authors":"Sugondo Hadiyoso, Rohmat Tulloh, Yuyun Siti Rohmah, Akhmad Alfaruq","doi":"10.4103/jmss.JMSS_29_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_29_20","url":null,"abstract":"Background: One of the vital organs that require regular check is heart. The representation of heart health can be identified through electrocardiogram (ECG) signals, blood pressure (BP), heart rate, and oxygen saturation (SpO2). Monitoring the heart condition needs to be regularly done to prevent heart attack that can occur suddenly and very quickly particularly for someone who has had a heart attack before. Nevertheless, it raises the problem of cost, time efficient, and flexibility. It takes a high cost and much time to perform this examination. A vital signal monitoring device is needed with low cost, wearable, accurate, and simple in use.Methods: This research designs and develops a device and application for monitoring human vital signals including ECG, SpO2, BP, and heart rate. A multi-sensor system with a control unit was applied to the device which was then called the Armband Vital Sign Monitor. This device can be used to measure vital parameters simultaneously using multiplexing techniques programmed in the microcontroller. Armband vital sign monitor is also equipped with Bluetooth module as a communication media for further data processing and display.Results: Armband vital sign monitor produces >99% accuracy in body temperature measurements, ±2 deviation values in SpO2 measurements, and systolic and diastolic deviations at ±3-8 mmHg. For EGC signals, tests are performed by comparing signals visually in graphical form, and EGC can be obtained properly as shown by the graph.Conclusion: In this study, an Armband vital sign device has been developed that can measure the body's vital parameters. The parameters which were measured included temperature, heart rate, BP, SpO2, and ECG. This device has small dimensions and can be put on the wrist. The device is also equipped with Bluetooth so monitoring can be conducted wirelessly.","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 3","pages":"208-216"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/15/66/JMSS-11-208.PMC8382033.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39371687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electrocardiogram Signals Denoising Using Improved Variational Mode Decomposition. 改进变分模态分解的心电图信号去噪方法。

Journal of Medical Signals & Sensors Pub Date : 2021-05-24 eCollection Date: 2021-04-01 DOI: 10.4103/jmss.JMSS_17_20

Vikas Malhotra, Mandeep Kaur Sandhu

{"title":"Electrocardiogram Signals Denoising Using Improved Variational Mode Decomposition.","authors":"Vikas Malhotra, Mandeep Kaur Sandhu","doi":"10.4103/jmss.JMSS_17_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_17_20","url":null,"abstract":"Background: Electrocardiogram (ECG) plays a vital role in the analysis of heart activity. It can be used to analyze the different heart diseases and mental stress assessment also. Various noises, such as baseline wandering, muscle artifacts and power line interface disturbs the information within the ECG signal. To acquire correct information from ECG signal, these noises should be removed.Methods: In the proposed work, the improved variational mode decomposition (IVMD) method for the removal of noise in ECG signals is used. In the proposed method, the weighted signal amplitude integrated over the timeframe of the ECG signal varies the window size during decomposition. Raw ECG data are extracted from 10 subjects and ECG data are also taken from the MIT BIH database for the proposed method.Results: The performance comparison of traditional variational mode decomposition (VMD) and the proposed technique is also calculated using mean square error, percentage root mean square difference, signal to noise ratio and correlation coefficient. The extracted highest signal to noise ratio (SNR) value of acquired ECG signals using traditional VMD is 42db whereas highest value of signal to noise ratio (SNR) using improved VMD (IVMD) is 83db.Conclusion: The proposed IVMD technique represented better performance than traditional VMD for denoising of ECG signals.","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 2","pages":"100-107"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/51/49/JMSS-11-100.PMC8253313.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39189863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

In vitro Studies of Polycaprolactone Nanofibrous Scaffolds Containing Novel Gehlenite Nanoparticles. 新型辉长石纳米颗粒聚己内酯纳米纤维支架的体外研究。

Journal of Medical Signals & Sensors Pub Date : 2021-05-24 eCollection Date: 2021-04-01 DOI: 10.4103/jmss.JMSS_42_20

Moloud Amini Baghbadorani, Ashkan Bigham, Mohammad Rafienia, Hossein Salehi

{"title":"In vitro Studies of Polycaprolactone Nanofibrous Scaffolds Containing Novel Gehlenite Nanoparticles.","authors":"Moloud Amini Baghbadorani, Ashkan Bigham, Mohammad Rafienia, Hossein Salehi","doi":"10.4103/jmss.JMSS_42_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_42_20","url":null,"abstract":"Background: Recently, many studies have been done on the physicochemical properties and biocompatibility of polycaprolactone (PCL) scaffolds containing ceramic reinforcers in the field of bone tissue engineering. In this study, the physical, mechanical and biological properties of electrospined-fabricated PCL scaffolds containing gehlenite (GLN) nanoparticles (NPs) as a novel bioceramic were investigated.Methods: To obtain the appropriate mechanical properties, the solution contains 3%, 5%, 7%, and 10% wt. of GLN NPs were prepared. Fiber morphology was investigated by scanning electron microscopy. In order to evaluate the NPs distribution, Energy Dispersive X-Ray Spectroscopy, X-ray diffraction, and Fourier Transform Infrared Spectroscopy spectroscopy were used. The scaffold hydrophilicity was measured by the water contact angle test. The tensile test was used to check the mechanical strength of the scaffold. The proliferation of MG-63 cells was evaluated by the MTT test. Alkaline phosphatase (ALP) activity of MG-63 cells was also examined.Results: Average fibers' diameters and porosity of PCL/GLN7% were obtained 150-500 nm and 80%, respectively. An increase in the scaffold hydrophilicity was observed by the addition of GLN NPs. The strength of PCL/GLN7% was higher than the blank PCL scaffold. Cell proliferation of scaffolds containing GLN was higher than the blank PCL scaffold. A significant increase in the secretion of ALP for GLN-loaded scaffolds was seen.Discussion: The results showed that PCL/GLN7% composite scaffold could be a good candidate for bone tissue engineering.Conclusion: The overall results indicate that the scaffold (PCL /GLN7%) has suitable mechanical properties, a great cell compatibility for bone tissue regeneration.","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 2","pages":"131-137"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d0/cd/JMSS-11-131.PMC8253317.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39188760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Cervical Cancer Prediction by Merging Features of Different Colposcopic Images and Using Ensemble Classifier. 融合不同阴道镜图像特征及集成分类器预测宫颈癌。

Journal of Medical Signals & Sensors Pub Date : 2021-05-24 eCollection Date: 2021-04-01 DOI: 10.4103/jmss.JMSS_16_20

Elham Nikookar, Ebrahim Naderi, Ali Rahnavard

{"title":"Cervical Cancer Prediction by Merging Features of Different Colposcopic Images and Using Ensemble Classifier.","authors":"Elham Nikookar, Ebrahim Naderi, Ali Rahnavard","doi":"10.4103/jmss.JMSS_16_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_16_20","url":null,"abstract":"Background: Cervical cancer is a significant cause of cancer mortality in women, particularly in low-income countries. In regular cervical screening methods, such as colposcopy, an image is taken from the cervix of a patient. The particular image can be used by computer-aided diagnosis (CAD) systems that are trained using artificial intelligence algorithms to predict the possibility of cervical cancer. Artificial intelligence models had been highlighted in a number of cervical cancer studies. However, there are a limited number of studies that investigate the simultaneous use of three colposcopic screening modalities including Greenlight, Hinselmann, and Schiller.Methods: We propose a cervical cancer predictor model which incorporates the result of different classification algorithms and ensemble classifiers. Our approach merges features of different colposcopic images of a patient. The feature vector of each image includes semantic medical features, subjective judgments, and a consensus. The class label of each sample is calculated using an aggregation function on expert judgments and consensuses.Results: We investigated different aggregation strategies to find the best formula for aggregation function and then we evaluated our method using the quality assessment of digital colposcopies dataset, and our approach performance with 96% of sensitivity and 94% of specificity values yields a significant improvement in the field.Conclusion: Our model can be used as a supportive clinical decision-making strategy by giving more reliable information to the clinical decision makers. Our proposed model also is more applicable in cervical cancer CAD systems compared to the available methods.","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 2","pages":"67-78"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/12/5d/JMSS-11-67.PMC8253312.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39189860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Development of a Permanent Device for Fertility Period Detection by Basal Body Temperature and Analysis of the Cervical Mucus Potential of Hydrogen. 通过基础体温检测生育期和分析宫颈粘液氢电位的永久性装置的开发。

Journal of Medical Signals & Sensors Pub Date : 2021-05-24 eCollection Date: 2021-04-01 DOI: 10.4103/jmss.JMSS_18_20

Sofiene Mansouri

{"title":"Development of a Permanent Device for Fertility Period Detection by Basal Body Temperature and Analysis of the Cervical Mucus Potential of Hydrogen.","authors":"Sofiene Mansouri","doi":"10.4103/jmss.JMSS_18_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_18_20","url":null,"abstract":"Background: Sometimes, women find it difficult to conceive a baby and others use contraceptives that often have side effects. Researchers have already established the importance of measuring basal body temperature (BBT) and the potential of hydrogen (pH).Method: We have designed and realized a device that allows the simultaneous measurement of the BBT and the pH. We used an Arduino Uno board, a pH sensor, and a temperature sensor. The device communicates with a smartphone, can be integrated into all e-health platforms, and can be used at home. We validated our ovulation detector by a measurement campaign on a group of twenty women. If the pH is >7 and at the same time, the BBT is minimum and <36.5°C, the women is in ovulation phase. If the pH is ≤7 and in the same time, the BBT is between 36.5°C and 37°C, the women are in preovulation or follicular phase. If the pH is ≤7 and in the same time, the BBT is >36.5°C, the women are in postovulation or luteal phase.Results: We tested the contraceptive aspect of our ovulometer on a set of seven women. We also tested the help of conceiving babies by having intercourse during the ovulation period fixed by our ovulation detector. The results are satisfactory.Conclusions: In the final version of our device, we displayed just in \"fertility period\" if the pH is ≥7 and the BBT is <36.5°C else we displayed in \"nonfertility period.\"","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 2","pages":"92-99"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/19/61/JMSS-11-92.PMC8253316.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39189862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biomarker Discovery by Imperialist Competitive Algorithm in Mass Spectrometry Data for Ovarian Cancer Prediction. 帝国主义竞争算法在卵巢癌预测质谱数据中的生物标志物发现。

Journal of Medical Signals & Sensors Pub Date : 2021-05-24 eCollection Date: 2021-04-01 DOI: 10.4103/jmss.JMSS_20_20

Shiva Pirhadi, Keivan Maghooli, Niloofar Yousefi Moteghaed, Masoud Garshasbi, Seyed Jalaleddin Mousavirad

{"title":"Biomarker Discovery by Imperialist Competitive Algorithm in Mass Spectrometry Data for Ovarian Cancer Prediction.","authors":"Shiva Pirhadi, Keivan Maghooli, Niloofar Yousefi Moteghaed, Masoud Garshasbi, Seyed Jalaleddin Mousavirad","doi":"10.4103/jmss.JMSS_20_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_20_20","url":null,"abstract":"Background: Mass spectrometry is a method for identifying proteins and could be used for distinguishing between proteins in healthy and nonhealthy samples. This study was conducted using mass spectrometry data of ovarian cancer with high resolution. Usually, diagnostic and monitoring tests are done according to sensitivity and specificity rates; thus, the aim of this study is to compare mass spectrometry of healthy and cancerous samples in order to find a set of biomarkers or indicators with a reasonable sensitivity and specificity rates.Methods: Therefore, combination methods were used for choosing the optimum feature set as t-test, entropy, Bhattacharya, and an imperialist competitive algorithm with K-nearest neighbors classifier. The resulting feature from each method was feed to the C5 decision tree with 10-fold cross-validation to classify data.Results: The most important variables using this method were identified and a set of rules were extracted. Similar to most frequent features, repetitive patterns were not obtained; the generalized rule induction method was used to identify the repetitive patterns.Conclusion: Finally, the resulting features were introduced as biomarkers and compared with other studies. It was found that the resulting features were very similar to other studies. In the case of the classifier, higher sensitivity and specificity rates with a lower number of features were achieved when compared with other studies.","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 2","pages":"108-119"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/a2/bc/JMSS-11-108.PMC8253319.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39190284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating Morphological Features of Electrocardiogram Signals for Diagnosing of Myocardial Infarction Using Classification-Based Feature Selection. 基于分类的特征选择评价心电图信号的形态学特征对心肌梗死的诊断价值。

Journal of Medical Signals & Sensors Pub Date : 2021-05-24 eCollection Date: 2021-04-01 DOI: 10.4103/jmss.JMSS_12_20

Seyed Ataddin Mahmoudinejad, Naser Safdarian

{"title":"Evaluating Morphological Features of Electrocardiogram Signals for Diagnosing of Myocardial Infarction Using Classification-Based Feature Selection.","authors":"Seyed Ataddin Mahmoudinejad, Naser Safdarian","doi":"10.4103/jmss.JMSS_12_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_12_20","url":null,"abstract":"Background: Cardiovascular disease (CVD) is the first cause of world death, and myocardial infarction (MI) is one of the five primary disorders of CVDs which the patient electrocardiogram (ECG) analysis plays a dominant role in MI diagnosis. This research aims to evaluate some extracted features of ECG data to diagnose MI.Methods: In this paper, we used the Physikalisch-Technische Bundesanstalt database and extracted some morphological features, such as total integral of ECG, integral of the T-wave section, integral of the QRS complex, and J-point elevation from a cycle of normal and abnormal ECG waveforms. Since the morphology of healthy and abnormal ECG signals is different, we applied integral to different ECG cycles and intervals. We executed 100 of iterations on a 10-fold and 5-fold cross-validation method and calculated the average of statistical parameters to show the performance and stability of four classifiers, namely logistic regression (LR), simple decision tree, weighted K-nearest neighbor, and linear support vector machine. Furthermore, different combinations of proposed features were employed as a feature selection procedure based on classifier's performance using the aforementioned trained classifiers.Results: The results of our proposed method to diagnose MI utilizing all the proposed features with an LR classifier include 90.37%, 94.87%, and 86.44% for accuracy, sensitivity, specificity, respectively. Also, we calculated the standard deviation value for the accuracy of 0.006.Conclusion: Our proposed classification-based method successfully classified and diagnosed MI using different combinations of presented features. Consequently, all proposed features are valuable in MI diagnosis and are praiseworthy for future works.","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 2","pages":"79-91"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/82/4d/JMSS-11-79.PMC8253315.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39189861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Early Detection of Alzheimer's Disease Based on Clinical Trials, Three-Dimensional Imaging Data, and Personal Information Using Autoencoders. 基于临床试验、三维成像数据和使用自编码器的个人信息的阿尔茨海默病早期检测。

Journal of Medical Signals & Sensors Pub Date : 2021-05-24 eCollection Date: 2021-04-01 DOI: 10.4103/jmss.JMSS_11_20

Hamid Akramifard, Mohammad Ali Balafar, Seyed Naser Razavi, Abd Rahman Ramli

{"title":"Early Detection of Alzheimer's Disease Based on Clinical Trials, Three-Dimensional Imaging Data, and Personal Information Using Autoencoders.","authors":"Hamid Akramifard, Mohammad Ali Balafar, Seyed Naser Razavi, Abd Rahman Ramli","doi":"10.4103/jmss.JMSS_11_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_11_20","url":null,"abstract":"Background: A timely diagnosis of Alzheimer's disease (AD) is crucial to obtain more practical treatments. In this article, a novel approach using Auto-Encoder Neural Networks (AENN) for early detection of AD was proposed.Method: The proposed method mainly deals with the classification of multimodal data and the imputation of missing data. The data under study involve the MiniMental State Examination, magnetic resonance imaging, positron emission tomography, cerebrospinal fluid data, and personal information. Natural logarithm was used for normalizing the data. The Auto-Encoder Neural Networks was used for imputing missing data. Principal component analysis algorithm was used for reducing dimensionality of data. Support Vector Machine (SVM) was used as classifier. The proposed method was evaluated using Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Then, 10fold crossvalidation was used to audit the detection accuracy of the method.Results: The effectiveness of the proposed approach was studied under several scenarios considering 705 cases of ADNI database. In three binary classification problems, that is AD vs. normal controls (NCs), mild cognitive impairment (MCI) vs. NC, and MCI vs. AD, we obtained the accuracies of 95.57%, 83.01%, and 78.67%, respectively.Conclusion: Experimental results revealed that the proposed method significantly outperformed most of the stateoftheart methods.","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 2","pages":"120-130"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ed/94/JMSS-11-120.PMC8253314.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39190285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Real-Time Fast Fourier Transform-Based Notch Filter for Single-Frequency Noise Cancellation: Application to Electrocardiogram Signal Denoising. 基于实时快速傅立叶变换的单频降噪陷波滤波器:在心电图信号降噪中的应用。

Journal of Medical Signals & Sensors Pub Date : 2021-01-30 eCollection Date: 2021-01-01 DOI: 10.4103/jmss.JMSS_3_20

Anis Ben Slimane, Azza Ouled Zaid

{"title":"Real-Time Fast Fourier Transform-Based Notch Filter for Single-Frequency Noise Cancellation: Application to Electrocardiogram Signal Denoising.","authors":"Anis Ben Slimane, Azza Ouled Zaid","doi":"10.4103/jmss.JMSS_3_20","DOIUrl":"https://doi.org/10.4103/jmss.JMSS_3_20","url":null,"abstract":"Despite the considerable improvement of the common-mode rejection ratio of digital filtering techniques, the electrocardiogram (ECG) traces recorded by commercialized devices are still contaminated by residual power line interference (PLI). In this study, we address this issue by proposing a novel real-time filter adapted to single-frequency noise cancellation and automatic power line frequency detection. The filtering process is principally based on a point-by-point fast Fourier transform and a judicious choice of the analysis window length. Intensive experiments conducted on real and synthetic signals have shown that our filtering method offers very clean ECGs, due to the suppression of spikes corresponding to the PLI and the preservation of spikes outside the filter band. In addition, this method is characterized by its low computational complexity which makes it suitable for real-time cleaning of ECG signals and thus can serve for more accurate diagnosis in computer-based automated cardiac system.","PeriodicalId":37680,"journal":{"name":"Journal of Medical Signals & Sensors","volume":"11 1","pages":"52-61"},"PeriodicalIF":0.0,"publicationDate":"2021-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/b4/92/JMSS-11-52.PMC8043120.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38929317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4