2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)最新文献_第5页

A comparison between heuristic and machine learning techniques in fall detection using Kinect v2 基于Kinect v2的启发式和机器学习技术在跌倒检测中的比较

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533763

Amin Amini, K. Banitsas, J. Cosmas

{"title":"A comparison between heuristic and machine learning techniques in fall detection using Kinect v2","authors":"Amin Amini, K. Banitsas, J. Cosmas","doi":"10.1109/MeMeA.2016.7533763","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533763","url":null,"abstract":"In this paper, two algorithms were tested on 11 healthy adults: one based on heuristic and another one on video tagging machine learning methods for automatic fall detection; both utilizing Microsoft Kinect v2. For our heuristic approach, we used skeletal data to detect falls based on a set of instructions and signal filtering methods. For the machine learning approach, we implemented a dataset utilizing the Adaptive Boosting Trigger (AdaBoostTrigger) algorithm via video tagging to enable fall detection. For each approach, each subject on average has performed six true positive and six false positive fall incidents in two different conditions: one with objects partially blocking the sensor's view and one with partial obstructed field of view. The accuracy of each approach has been compared against one another in different conditions. The result showed an average of 95.42 % accuracy in the heuristic approach and 88.33 % in machine learning technique. We conclude that heuristic approach performs more accurately for fall detection when there is a limited number of training dataset available. Nevertheless, as the gesture detection's complexity increases, the need for a machine learning technique is inevitable.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126934511","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: 16

Instrumented timed up and go: Fall risk assessment based on inertial wearable sensors 仪器计时up and go:基于惯性可穿戴传感器的跌倒风险评估

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533778

Joana Silva, I. Sousa

引用次数: 20

Role of voxel selection and ROI in fMRI data analysis 体素选择和ROI在fMRI数据分析中的作用

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533739

R. Zafar, A. Malik, N. Kamel, S. Dass

引用次数: 6

An image based quantitative fluorescence immunoassay reader for HbA1c testing: Calibration & repeatability study 用于糖化血红蛋白检测的基于图像的定量荧光免疫分析阅读器:校准和可重复性研究

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533702

K. Chowdhury, J. Joseph, Nethra Reddy, Jayaraman Kiruthi Vasan, M. Sivaprakasam

引用次数: 1

Towards inline spatially resolved temperature sensing in thermal ablation with chirped fiber Bragg grating 啁啾光纤光栅热烧蚀在线空间分辨温度传感研究

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533777

D. Tosi, S. Korganbayev, Nurlan Zhakin, Riccardo Gassino, G. Perrone, A. Vallan

引用次数: 12

A low power wireless breathing monitoring system using piezoelectric transducer 一种基于压电传感器的低功耗无线呼吸监测系统

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533756

I. Mahbub, Hanfeng Wang, S. Islam, S. Pullano, A. Fiorillo

引用次数: 19

Training impulses: A method to quantify exercise intensity in postmenopausal obese women 训练冲动:量化绝经后肥胖妇女运动强度的方法

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533784

F. Velluzzi, F. Tocco, A. Deledda, D. Lai, A. Loviselli, R. Milia, D. Concu, G. Ghiani, A. Concu

{"title":"Training impulses: A method to quantify exercise intensity in postmenopausal obese women","authors":"F. Velluzzi, F. Tocco, A. Deledda, D. Lai, A. Loviselli, R. Milia, D. Concu, G. Ghiani, A. Concu","doi":"10.1109/MeMeA.2016.7533784","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533784","url":null,"abstract":"Nine obese postmenopausal women aged 59±6.3 years having a body mass index of 35.2±2.0 kg/m2 performed a 12-week training protocol three times a week. Each training session, lasting about 80 min, consisted of general warmup and stretching exercises, free-body exercises, exercises with small implements (clubs, dumbbells, medicine ball), aerobic activity consisting of walking/running on the treadmill or open ground and cooling-down exercises. The training impulse method was utilized to indirectly quantify the amount of exercise intensity on the basis of heart rate values assessed during training sessions. The value adopted for training impulses prescribed for patients was about 130 arbitrary units and corresponded to 50 ~ 60% of their maximum oxygen consumption. Immediately before and at the end of the training patient took an incremental cycle-ergometer test (20W every 3 min), up to exhaustion, in such a way as to assess maximum values of: oxygen consumption, workload and the ratio between these two variables (i.e. the oxidative cost), heart rate, systolic and diastolic arterial blood pressures. At the trial end, in correspondence of the maximum workload reached during the cycle-ergometer exercise, both body mass and body mass index had significantly decreased, as had diastolic arterial blood pressure and oxidative cost of exercise, while fat free mass had increased, when refered to the trial entry. It can be concluded that the precise amount of training, as established by utilizing training impulses, may facilitate the choice of the strategy to ameliorate physical and mental health in postmenopausal obese women.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115072774","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: 5

Heartbeat pattern classification algorithm based on Gaussian mixture model 基于高斯混合模型的心跳模式分类算法

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533715

Mehmet Iscan, F. Yigit, C. Yilmaz

{"title":"Heartbeat pattern classification algorithm based on Gaussian mixture model","authors":"Mehmet Iscan, F. Yigit, C. Yilmaz","doi":"10.1109/MeMeA.2016.7533715","DOIUrl":"https://doi.org/10.1109/MeMeA.2016.7533715","url":null,"abstract":"Nowadays, probabilistic neural networks have been frequently used to pattern discrimination in biological signals despite of non-stationary and individual characteristics of human subjects. In this study, a new approach was proposed to pattern classification for electrocardiography (ECG) signals based on Gaussian mixture model and logarithmic linearization. The objective of this study was to identify and classify QRS complexes on ECG patterns. For this purpose, a high performance method to classify and discriminate various ECG patterns was developed. Besides, a comparison algorithm which evaluates time series signals was established, and the limitation of its parameters was determined in order to attain high performance in ECG classification. The proposed algorithm has been tested on the data from 20 normal subjects and 22 additional normal data sets from MIT-DB database. After the improvement by the proposed algorithm, we observed 99.21% and 99.24% of recognition rates in ECG data from 20 normal subjects and MIT-DB database, respectively. The results showed that the proposed algorithm achieved a high performance to classify and discriminate various ECG signals.","PeriodicalId":221120,"journal":{"name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134235697","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: 5

Monitoring of retinal vessels for diabetic patients in home care assistance 糖尿病患者在家庭护理援助中的视网膜血管监测

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533713

L. Carnimeo, Annamaria Roberta Altomare, Rosamaria Nitti

引用次数: 5

Experiential investigation of nonlinear acoustic field structure in two and three dimensions 二维和三维非线性声场结构的经验研究

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2016-05-15 DOI: 10.1109/MeMeA.2016.7533727

D. Kaleci, A. Sahin, Baki Karaböcü

引用次数: 0