2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)最新文献_第5页

Spectral denoising for MR spectroscopy using noise level function 基于噪声级函数的磁共振光谱去噪

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167527

Mathieu Naudin, B. Tremblais, C. Guillevin, R. Guillevin, C. Fernandez-Maloigne

{"title":"Spectral denoising for MR spectroscopy using noise level function","authors":"Mathieu Naudin, B. Tremblais, C. Guillevin, R. Guillevin, C. Fernandez-Maloigne","doi":"10.1109/ICABME.2017.8167527","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167527","url":null,"abstract":"1H-MRSI (proton Magnetic Resonance Spectroscopic Imaging) is now widely used to assist physicists to analyze and quantify brain metabolites in a noninvasive way. In case of glioma, the brain tissue metabolite composition is not widely different but metabolites concentration are varying depending on the grade of the tumor. In the higher stage of the tumor, new metabolites could be detected such as lactate or lipids in the long and short echo time. These variations appear owing to brain tissue modification generated by the tumoral process and help to classify the tumor in grades. 1H-MRS provides crucial data to feed models in order to estimate the best treatment (surgical, etc). Initially, the spectrum is the result of a large number of acquisitions. With a sufficiently long acquisition time, the resulting signal resulting from about 150 mean filter appears to be very low in noise. Nevertheless in this case acquisition time is too long to envisage the study of different parts of the brain. That is why we need to propose an efficient and robust spectrum denoising method.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114437460","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}

引用次数: 0

Multidimensional segmentation of heterogeneous data 异构数据的多维分割

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167550

H. Saker, P. Stadler, Ahmad M. Shahin

引用次数: 2

Validity of activity measurement using a smart phone 使用智能手机测量活动的有效性

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167520

A. Hammoud, R. Jaber, H. Othman

{"title":"Validity of activity measurement using a smart phone","authors":"A. Hammoud, R. Jaber, H. Othman","doi":"10.1109/ICABME.2017.8167520","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167520","url":null,"abstract":"Since smart phones are equipped with built-in accelerometers they can be used for self-monitoring of physical activity which is an important health behavior and predictor of functioning, especially in older adults. The objective of this study is to investigate the validity of a smart phone-based activity monitoring application in adults aged below and above 65 years old. Ten adults aged below 65 years (mean of 33, standard deviation 13.7) and ten adults aged 65 years or older (mean 76, standard deviation 5.5) were asked to monitor their daily physical activity with a smart phone and an ActiGraph GT3X for 7 consecutive days. Spearman correlations between the counts per minute of the two devices were calculated for adults aged below and above 65 years separately. For both devices, each monitored minute was classified into four categories of activity intensity based on the counts per minute: sedentary, light, moderate, and high activity intensity. Association and agreement between the two devices was analyzed for separately for the two groups using Pearson's Correlations and paired t-tests. Data from 10 adults aged below 65 years and 10 adults aged above 65 years could be included in the analyses. Spearman correlations in adults aged below 65 years varied between 0.62 and 0.89 and correlations in adults aged above 65 years varied between 0.73 and 0.98. Pearson's correlations between the two devices for total number of minutes spent in different activity intensity categories per day per participant were high in both groups (range 0.79–0.98). Paired t-tests revealed that the smart phone underestimates the number of sedentary minutes per day in participants aged below and above 65 years with 6.45% and 6.78% respectively.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123187120","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}

引用次数: 2

Wireless body sensor network and ECG Android application for eHealth 面向电子健康的无线身体传感器网络和心电Android应用

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167526

Abdelbaset Khalaf, Rishaad Abdoola

引用次数: 9

Separation and localization of EHG sources using tensor models 基于张量模型的EHG源分离与定位

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167547

Saeed Zahran, Bayan Alrifai, Ahmad Diab, M. Khalil, C. Marque

引用次数: 1

Monitoring visual sustained attention with a low-cost EEG headset 用低成本脑电图耳机监测视觉持续注意力

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167572

A. Mheich, J. Guilloton, N. Houmani

引用次数: 3

Failure-cost mathematical model for medical equipment maintenance 医疗设备维修故障成本数学模型

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167525

A. Khalaf, Karim D Djouani, Y. Hamam, Y. Alayli

引用次数: 4

An investigation of feature combinations of time-domain power spectral descriptors feature extraction for myoelectric control of hand prostheses 基于时域功率谱描述子特征组合的假肢肌电控制特征提取研究

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167530

Ali H. Al-timemy

{"title":"An investigation of feature combinations of time-domain power spectral descriptors feature extraction for myoelectric control of hand prostheses","authors":"Ali H. Al-timemy","doi":"10.1109/ICABME.2017.8167530","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167530","url":null,"abstract":"Upper limb prostheses controlled with Pattern Recognition (PR) and myoelectric signals have great promise for amputees who lost an upper limb since it can control large number of movements intuitively. One of the existing challenges with such PR systems include the need to develop new feature extraction techniques to facilitate clinical implementation of PR systems to satisfy amputees' needs. In this paper, the features of newly proposed Time Domain Power-Spectral Descriptors (TD-PSD) feature extraction method will be investigated in order to find the best feature set to classify eight hand and finger movement. Two congenital female transradial amputees were recruited and the myoelectric signals which are also known as Electromyography (EMG) signals, were collected from different surface EMG sensors when the two participants performed eight finger and hand movements. Results showed that a subset of four TD-PSD features achieved similar performance to that of the full set of TD-PSD features, with average error rates of the classification being equal to approximately 7% which is within the acceptable error rates of a usable PR system where it should be below 10%.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128880507","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}

引用次数: 0

Ensemble of bagged tree classifier for the diagnosis of neuromuscular disorders 用于神经肌肉疾病诊断的袋装树分类器集成

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167564

Kadhim Kamal Al-Barazanchi, A. Q. Al-Neami, Ali H. Al-timemy

{"title":"Ensemble of bagged tree classifier for the diagnosis of neuromuscular disorders","authors":"Kadhim Kamal Al-Barazanchi, A. Q. Al-Neami, Ali H. Al-timemy","doi":"10.1109/ICABME.2017.8167564","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167564","url":null,"abstract":"Intramuscular Electromyography (EMG) signal provides a significant source of information that plays an inevitable role in the diagnosis of neuromuscular disorders. The ensemble method represents a supervised machine learning algorithm that constructs a combination of classifiers to achieve accurate classification decision. In this respect, the aim of this study is to propose classification method for diagnosis of neuromuscular disorders including Amyotrophic lateral sclerosis (ALS) and myopathy diseases, through using publicly available EMG data, recorded by intramuscular single-channel EMG electrode. The ensemble of bagged tree algorithm generates and averages multiple versions of decision tree predicatore that are formed by producing a bootstrap replicate of the EMG learning data set. A set of ten time-domain features extracted from the intramuscular EMG recordings are classified by the ensemble of bagged tree algorithm. A classification accuracy rate of 92.8% was obtained with the proposed bagged tree classifier, which reports high classification accuracy. The outcome of this study can assist the clinicians to decide the correct diagnosis of neuromuscular disorders.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129936056","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}

引用次数: 18

Multi-muscle force estimation using data fusion and HD-sEMG: An experimental study 基于数据融合和HD-sEMG的多肌肉力估计实验研究

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI: 10.1109/ICABME.2017.8167529

M. A. Harrach, S. Boudaoud, V. Carriou, F. Marin

{"title":"Multi-muscle force estimation using data fusion and HD-sEMG: An experimental study","authors":"M. A. Harrach, S. Boudaoud, V. Carriou, F. Marin","doi":"10.1109/ICABME.2017.8167529","DOIUrl":"https://doi.org/10.1109/ICABME.2017.8167529","url":null,"abstract":"This paper presents a new multi-muscle force estimation approach based on a HD-sEMG/force model in experimental context. Accordingly, we will try to estimate the muscle force of the three elbow flexors: Biceps Brachii (BB), Brachialis (BR) and Brachioradialis (BRD) in isometric isotonic conditions. This will be done by using a recently proposed sEMG/force equation model validated by simulation. For representing muscle activation, we will the sEMG Root Mean Squared value acquired after data fusion via Watershed image segmentation algorithm. This data fusion method allows us to obtain one RMS value per force level from the sEMG signals recorded from the HD-sEMG grids putted on each one of the three considered muscles. Five subjects participated in the experimental protocol, where we recorded the force simultaneously with the HD-sEMG signals for 9 contraction levels. After solving a linear equation system, the force of each muscle is estimated. Obtained results shown different muscle activation synergies with the dominance of the BB muscle. Finally, the feasibility of this approach is demonstrated in solving the load sharing problem in isometric isotonic context.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130797053","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}

引用次数: 6