Int. J. Medical Eng. Informatics最新文献

{"title":"Radial basis function neural network with genetic algorithm for discrimination of recombination hotspots in saccharomyces cerevisiae","authors":"Ashok Kumar Dwivedi","doi":"10.1504/ijmei.2020.10028641","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028641","url":null,"abstract":"Recombination influences the evolution of saccharomyces cerevisiae. Genomic regions where recombinations occurs are known as recombination hotspots. There are two kind of hotspots for recombination. The spots where recombination occurs more frequently are called recombination hot spots and regions where recombination occurs less frequently are known as cold spots. In this work, we have formulated methods based on neural network models for the classification of these hot and cold recombination spots on the basis of compositional features of nucleotide sequences. These models were validated using tenfold cross validation technique. The classification accuracy of 83%, 82%, and 78% were achieved using radial basis function neural network with genetic algorithm, radial basis function neural network and multilayer perceptron models respectively. Moreover, the performance of these model were evaluated on different ct classification measurements. Furthermore, results indicate that redial basis function neural network with genetic algorithm gives best result.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125632851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-frequency analysis-based method for application of infant cry classification","authors":"J. Saraswathy, M. Hariharan, W. Khairunizam, J. Sarojini, S. Yaacob","doi":"10.1504/ijmei.2020.10028642","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028642","url":null,"abstract":"Automatic infant cry classification is one of the significant studies under medical engineering, adopting the medical and engineering techniques for the classification of diverse physical and physiological states of the infants. This paper proposes a new investigation of time-frequency (t-f)-based signal processing technique using wavelet packet spectrum (wpspectrum) for classification of newborn cry signals. The study was initialised with the extraction of a cluster of t-f features from the generated t-f matrix of recorded cry signals using wpspectrum by extending time-domain and frequency-domain features to the joint t-f domain. In accordance, conventional features such as mel-frequency cepstral coefficients (MFCCs) and linear prediction coefficients (LPCs) were also extracted in order to compare the performance of the suggested t-f approach. Probabilistic neural network (PNN) and general regression neural network (GRNN) were used in classification. The proposed methodology was implemented to classify different sets of infant cry signals and the best empirical result of above 99% was reported.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115675882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving ECG signal denoising using wavelet transform for the prediction of malignant arrhythmias","authors":"A. Giorgio, C. Guaragnella, Domenico Andrea Giliberti","doi":"10.1504/ijmei.2020.10028643","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028643","url":null,"abstract":"This paper deals with the accuracy of algorithms for the detection of ventricular late potentials (VLP) in an electrocardiographic signal (ECG), being associated with malignant arrhytmias and possible cardiac death. VLP detection is strongly influenced by signal noise. The objective of this paper is to define a denoising algorithm improving the VLPs detection. The method uses wavelet denoising, subband coding, unfortunately introducing heavy linear distortions. Therefore, an equalisation filter has been properly designed, in order to cancel the distortions. The algorithm has been implemented and successfully verified using MATLAB. Then, it has been implemented on Altera's FPGA and then verified on the evaluation board DE1-SoC. On-board processed results and theoretical results are consistent, validating the algorithm. The results show that the algorithm capability to be implemented as programmable hardware. It also could be used for upgrading ECG devices reliability in the field of heart diseases prevention.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115021670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review on automatic identification of fovea in retinal fundus images","authors":"S. RajeshI., Bharathi Malakreddy Arikerie, B. Reshmi","doi":"10.1504/ijmei.2020.10028646","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028646","url":null,"abstract":"Identification of retinal diseases is a very significant area of ophthalmology. Regular procedures are extremely specific, which rely on manual observation and highly prone to error. Hence, it is extremely fundamental to set up an automatic system for screening of vision threatening diseases like diabetic retinopathy (DR) and diabetic maculopathy (DM). Patients who are suffering from DR are at high risk to have DM which may lead to blindness, if not detected and treated appropriately at the appropriate time. Automatic analysis of retinal images requires knowledge and the properties of anatomical structures and retinal lesions. Thus, locating fovea plays a vital role in the analysis of retinal images. In recent times image processing has become a very effective tool for the detection and analysis of abnormalities in retinal images. This survey paper depicts the fundamental terminology related to automatic detection of macula and fovea. Literature review of various methods used for finding fovea in retinal fundus images is discussed. Detection issues involved in fovea are also discussed in this paper.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124408356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of salivary components as non-invasive biomarkers for monitoring chronic kidney disease","authors":"Bhaskar Navaneeth, M. Suchetha","doi":"10.1504/IJMEI.2020.10020254","DOIUrl":"https://doi.org/10.1504/IJMEI.2020.10020254","url":null,"abstract":"Saliva, a valuable source of biochemical information, is a potential diagnostic substance that helps to identify many diseases. Studies have revealed that saliva tests help identify many diseases. Saliva test has excellent advantages over blood test as the former can be collected non-invasively using simple equipment. This paper explores how salivary components can be used as diagnostic tool to identify chronic kidney disease (CKD). Experimental analysis was conducted to assess the levels of salivary components in whole saliva of CKD patients in contrast with healthy people. Urea and creatinine are the most accepted biomarkers of CKD. The correlation between creatinine and urea levels in human saliva and blood were analysed. Unstimulated saliva flow rate and pH levels were also monitored in this study. The results obtained from this study give concrete evidence that there is a positive correlation between creatinine and urea levels in blood and saliva. From the derived regression line equations, serum urea and creatinine values can be predicted from salivary values. Receiver operating characteristics (ROC) performance analysis was performed and area under the curve (AUC) of 0.95 and 0.89 was obtained for salivary creatinine and urea.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115818081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A decision support tool development: an analysis of the statistical significance of the dichotic listening of speech test results","authors":"E. Popova, E. Wasserman, N. Kartashev","doi":"10.1504/ijmei.2020.10028652","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028652","url":null,"abstract":"In this study, we analyse the statistical significance of the dichotic listening test results using two methods. The first method is based on the Agresti-Coull interval, and the other one is based on the sequential Wald analysis. We also propose a way to estimate the guaranteed boundaries for the eventual laterality index at every step of the dichotic listening test using the random walk method. This work is based on the analysis of 87 dichotic listening protocols of 59 children and adolescents of 4-16 years of age (patients of children's psychoneurological clinic) and three healthy adult volunteers. The dichotic listening was carried out in the clinical and laboratory conditions.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125020258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brainwave entrainment through external sensory stimulus: a therapy for insomnia","authors":"E. Karuppathal, R. Kalpana, A. Srinivasan","doi":"10.1504/IJMEI.2021.10037429","DOIUrl":"https://doi.org/10.1504/IJMEI.2021.10037429","url":null,"abstract":"Objective: To use Brainwave Entrainment through External sensory stimulus to treat Insomnia. Background: Insomnia is a condition that makes disorderness in the sleep. It plays a significant role in normal, pathological and psychiatric subjects. Most of the times, inducing sleep either through hypnotics or through sedative medicines are commonly adopted for treating sleeplessness. Brainwave Entrainment is an alternative procedure that modulates neural activities by synchronizing brainwave frequency with that of stimuli (Shusheng et al., 2016). Design/Methods: In this work audio, visual and haptic stimuli are used to improve overall sleep quality for insomnia subjects. Two audio signals at different frequencies were given to left and right ears. The results in binaural beat signal in delta band. Visual input is also given to two eyes through eye-mask to block the entry of external light. Automated system is developed to give pressure at HT-7 with time and pressure control. This therapy is self-administered by the TEST Group (who are diagnosed for insomnia) for a brief period on regular pace. Brain signals are acquired before and after therapy to understand the influence of AVE. Subjects who are not into insomnia (CONTROLs) are also studied for sleep pattern to make baseline comparison. Results: By analyzing power spectrum of these signals, results demonstrate that average delta signal power increases by 10% becoming at par with the CONTROLs. The test responses are also statistically analyzed using Cohen’s d value. The obtained results demonstrate impact of this therapy as significant changes in quality of sleep. Also, insomnia subjects who are not into oral medicine shows better response, in the sense their rhythmic changes became almost similar to that of CONTROLs with marked increase in REM state duration, reaching 20% of full sleep time, a normally recommended value. Conclusions: Brainwave entertainment through external sensory stimulus is very beneficial to treat insomnia soon after the diagnosis. Disclosure: Dr. Srinivasan has nothing to disclose. Dr. E has nothing to disclose. Dr. Venkatesan has nothing to disclose. Dr. R has nothing to disclose.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123237489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transmission and archiving of reduced MRI medical images","authors":"Hedi Amri, M. Abdmouleh, A. Khalfallah, J. Lapayre, M. Bouhlel","doi":"10.1504/ijmei.2020.105657","DOIUrl":"https://doi.org/10.1504/ijmei.2020.105657","url":null,"abstract":"Medical images are often large. To minimise their file sizes, different compression standards like JPEG, JPEG 2000 and TIFF have been developed, but they can affect the image quality in case of lossy compression. In this paper, we propose a compression method based on image resizing that can reduce the file size to a quarter before its transmission or archiving. When it is received or before its display, the reduced image is enlarged to ensure better visual comfort. This approach is called REPro. In this context, we have used three image reduction techniques namely square-square mesh decimation, square-square filtered mesh decimation, the square-staggered-square filtered mesh decimation. In addition, we have utilised four enlargement techniques namely zero padding, nearest neighbour interpolation, cubic spline interpolation and binterpolation to resize MRI images. The experimental results prove that the combination of the square-square mesh decimation with the B-spline interpolation ensures the minimum distortion of the original image.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129197884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An artificial intelligence approach for the recognition of early stages of eczema","authors":"D. Kalbande, Rohit Naik, J. Jatakia, U. Khopkar","doi":"10.1504/IJMEI.2020.10019990","DOIUrl":"https://doi.org/10.1504/IJMEI.2020.10019990","url":null,"abstract":"The rural population of India suffers from various medical ailments and due to the lack of medical facilities and practitioners, enough support is not available. Medical help might come late and the problem might have been aggravated. With the increasing awareness about artificial intelligence (AI), it is possible to solve these problems using technology. The research aims at detecting an early stage of the skin disease 'eczema', when the affected part of the human body is captured through a smart phone and approximate symptoms are provided by the medical practitioner. It uses artificial intelligence algorithms like convolutional neural networks and support vector machines algorithm for classifying the images, and back propagation algorithm for training a model based on the symptoms. Around 50 clinical photographs of eczema acquired from KEM Hospital, Mumbai to train the classifier and then different images of eczema were tested with an accuracy of greater than 85%.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133305043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pragmatic realities on brain imaging techniques and image fusion for Alzheimer's disease","authors":"P. S. J. Kumar, Yang Yung, Mingmin Pan","doi":"10.1504/ijmei.2020.105655","DOIUrl":"https://doi.org/10.1504/ijmei.2020.105655","url":null,"abstract":"Alzheimer's disease is the absolute generous of age-related neurodegenerative syndrome. It specifies substantial brain atrophy, amnesia and major neuro-logic disintegration. Brain imaging techniques has been progressively employed for medical explanation and variant diagnosis, and to afford understanding into the paraphernalia on functional and structural measurements of the brain, sketches of dimensional distribution besides their normal antiquity and progression over time. This paper makes an exertion in performing a practical virtuosity on brain imaging techniques and image fusion for the diagnosis of Alzheimer's disease. Several brain imaging techniques like computerised tomography, single-photon emission computed tomography, magnetic resonance spectroscopy, positron emission tomography, magnetoencephalo-graphy, magnetic resonance imaging diffusion tensor imaging was evaluated for Alzheimer's disease based on their degree of confidence, quality, volumetry, availability, cost and limitations.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127901508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}