2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)最新文献

Experimental validation of an optofluidic platform for microbial single cell isolation and whole genome amplification for human microbiome applications 用于微生物单细胞分离和全基因组扩增的光流平台的实验验证

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-07-19 DOI: 10.1109/MeMeA.2017.7985850

Yuguang Liu, P. Jeraldo, S. McDonough, J. Jen, Robin Patel, Marina Walther-Antonio, Christopher J. Lambert, B. Gale

引用次数: 0

Tailoring fast-scan cyclic voltammetry for tonic dopamine concentration measurement 定制快速扫描循环伏安法用于强直多巴胺浓度测量

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-07-19 DOI: 10.1109/MeMeA.2017.7985858

Yoonbae Oh, Yumin Kang, Cheonho Park, Hojin Shin, I. Kim, D. Jang, K. Bennet, Kendall H. Lee

{"title":"Tailoring fast-scan cyclic voltammetry for tonic dopamine concentration measurement","authors":"Yoonbae Oh, Yumin Kang, Cheonho Park, Hojin Shin, I. Kim, D. Jang, K. Bennet, Kendall H. Lee","doi":"10.1109/MeMeA.2017.7985858","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985858","url":null,"abstract":"Fast-scan cyclic voltammetry (FSCV) with background subtraction method has been widely used for detecting neurotransmitters in the brain. The most common application of FSCV is measuring phasic change of dopamine (DA) in the brain evoked by an external stimulus. The background subtraction method has greatly improved FSCV application to the neuroscience field, however, tonic dopamine concentration which is as vital as phasic change cannot be measured because the background is subtracted. In this study, we developed a tailoring FSCV technique which can manipulate background current by modifying the waveform voltage point. By using this technique, the last background current generated by last waveform in multiple pulses is tailored to the front background current. As a result, background current is cancelled out by subtracting the front voltammogram and tailored (last) voltammogram. On the other hand, DA oxidation/reduction pattern remained between front and last voltammogram, so that, tailoring FSCV can detect tonic DA concentration without background subtraction method. The tailoring technique is evaluated by comparing with commercialized enzyme-linked immunosorbent assay (ELISA) kits. By measuring endogenously released DA from DA cell, tailoring method showed significant correlation with ELISA result.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129491094","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

Evaluation of auditory cortex tonotopical organization in rats Through Principal Component Analysis 主成分分析法评价大鼠听觉皮层张力局部组织

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-07 DOI: 10.1109/MeMeA.2017.7985879

M. G. Bianco, S. Pullano, D. Menniti, A. Fiorillo, E. Villers-Sidani

引用次数: 4

Driver identification using vehicle acceleration and deceleration events from naturalistic driving of older drivers 利用老年驾驶员自然驾驶中的车辆加速和减速事件进行驾驶员识别

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-07 DOI: 10.1109/MeMeA.2017.7985845

Nathanael C. Fung, Bruce Wallace, A. Chan, R. Goubran, M. Porter, S. Marshall, F. Knoefel

{"title":"Driver identification using vehicle acceleration and deceleration events from naturalistic driving of older drivers","authors":"Nathanael C. Fung, Bruce Wallace, A. Chan, R. Goubran, M. Porter, S. Marshall, F. Knoefel","doi":"10.1109/MeMeA.2017.7985845","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985845","url":null,"abstract":"Driving is a common task that involves skill and individual preferences that can differ between drivers. The unique driving behaviours can be beneficial for differentiating drivers of shared vehicles and identifying differences between older drivers with normal and declining driving abilities. This paper presents a method for identifying individual drivers based on motor vehicle acceleration and deceleration events from their natural driving behaviour. We provide a novel approach to driver identification based on classification using multiple in-vehicle sensor signals collected in naturalistic conditions with anonymized driving locations. The dataset consists of thousands of trips from a selection of 14 stable-health older drivers (70 years and older) from their first year of the Candrive research study. We trained separate multiclass linear discriminant analysis classifiers to recognize unique patterns in their acceleration and deceleration events to predict the identity of the driver out of a group of drivers. For five different drivers, the acceleration and deceleration events were used to distinguish between drivers at 34% and 30% average accuracy, respectively. By taking a majority vote among the events, the accuracy improved to 61%, exceeding by about three times the null model of random guessing. This performance improvement continues when expanding the group from 2 to 14 drivers. The analysis shows potential for identifying drivers by the patterns in their driving maneuvers such as turning and stopping.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134250067","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: 35

RASUS: Rapid Assistance System through Uber-inspired Software for localization on-line of nurses and doctors RASUS:通过uber软件实现护士和医生在线本地化的快速援助系统

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-07 DOI: 10.1109/MeMeA.2017.7985876

H. Nieto-Chaupis

{"title":"RASUS: Rapid Assistance System through Uber-inspired Software for localization on-line of nurses and doctors","authors":"H. Nieto-Chaupis","doi":"10.1109/MeMeA.2017.7985876","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985876","url":null,"abstract":"We present RASUS: Rapid Assistance System through Uber-inspired Software aimed to provide information in real time about the geolocation of healthcare practitioners and patients. RASUS is designed to be used in the cases where rapid assistance and intervention is required. Once the patient has located the closest doctors (or nurses), the subsequent step is the decision of the patient to make a call to one of them. The usage of this software might be advantageous in those patients whose localizations are far from hospitals (or health centers) but pretty close to doctors or nurses which might be available to provide services in cases of emergency. The efficiency of RASUS is evaluated in the cases where type-2 diabetic patients are under imminent risk of being assaulted by unexpected diabetic coma. We have simulated random geolocation for both patients and healthcare practitioners in a Peri-urban area of Lima city in order to predict the advantages and disadvantages of software. From a Monte Carlo simulation, a 78% of diabetes patients (of a simulated sample) using RASUS might surpass the diabetic coma with a deviation of order of ±10%.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125422105","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: 1

An IoT-enabled multi-sensor multi-user system for human motion measurements 支持物联网的多传感器多用户人体运动测量系统

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-07 DOI: 10.1109/MeMeA.2017.7985877

L. D. Vito, F. Lamonaca, Gianluca Mazzilli, M. Riccio, D. L. Carní, P. F. Sciammarella

引用次数: 7

The calibration of targeting errors for an ultrasound-guided high-intensity focused ultrasound system 超声引导高强度聚焦超声系统定位误差的标定

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-07 DOI: 10.1109/MeMeA.2017.7985841

Ke Li, Jingfeng Bai, Yazhu Chen, Xiang Ji

{"title":"The calibration of targeting errors for an ultrasound-guided high-intensity focused ultrasound system","authors":"Ke Li, Jingfeng Bai, Yazhu Chen, Xiang Ji","doi":"10.1109/MeMeA.2017.7985841","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985841","url":null,"abstract":"Accurate targeting is one indispensable feature of image-guided high-intensity focused ultrasound (HIFU) systems for treatment safety and efficacy. In our previously developed ultrasound-guided phased-array HIFU system, a rotatable imaging probe was mounted into the central hole of applicator for targeting and monitoring. Two-dimensional image sequence of different imaging planes can be obtained by rotation of the probe. The misalignment between the spots predetermined in the image and the spots sonicated in the tissue can result in the ablation of normal tissue outside the targeting volume, and thus targeting error is unavoidable. An acrylic plate internally placing two flat-head bolts was constructed to measure and calibrate the targeting error. The imaging planes were switched from −90° to 90° with a 30° step, and the targeting errors were measured 12 times for each of these planes before and after calibration. The targeting errors in other imaging planes could be estimated by linear interpolation using the measured errors in the nearest two imaging planes. The coordinates of the spots to be sonicated were corrected in consideration of the targeting errors in the selected imaging plane. After calibration, the mean targeting errors were reduced to 0.30∼0.68 mm from 0.86∼1.74 mm. Besides, in the ex vivo experiment the needle-thermocouple tip was used as the target which could be identified in the image. The temperature rise measured by the thermocouple during sonication was in accordance with the theoretical result. In conclusion, the calibration of targeting errors is effective for our system, and the targeting accuracy is also capable to ensure safe sonication.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133335661","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

Monitoring pH, temperature and humidity in long-term stem cell culture in CO2 incubator 监测CO2培养箱中干细胞长期培养的pH值、温度和湿度

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-07 DOI: 10.1109/MeMeA.2017.7985922

D. Rajan, J. Verho, J. Kreutzer, H. Valimaki, H. Ihalainen, J. Lekkala, M. Patrikoski, S. Miettinen

{"title":"Monitoring pH, temperature and humidity in long-term stem cell culture in CO2 incubator","authors":"D. Rajan, J. Verho, J. Kreutzer, H. Valimaki, H. Ihalainen, J. Lekkala, M. Patrikoski, S. Miettinen","doi":"10.1109/MeMeA.2017.7985922","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985922","url":null,"abstract":"Cell culture in stem cell research is on the rise, not only for basic research but also for its potential medical and therapeutic applications. Monitoring culture process using sensors throughout the culture helps to optimize culture conditions for optimal growth and maximize yield from the cells. Further, the sensor data gives insight into developing better cell culture systems. Typical stem cell culture platforms, e.g. well plates or flasks, cannot be easily equipped with sensors and impose many challenges in periodic process measurements in a CO2 incubator. We present an incubator compatible modular measurement system with three sensors, to monitor pH, temperature and humidity continuously throughout the culture. Sensors are assembled around a flow through cuvette for highly sterile non-contact measurements. No sample preparation or sample extraction from the incubator is needed and the measurements are carried out in a closed flow loop without wasting any medium. The modular assembly is novel, reusable and feasible for humid incubator environments. The system has been tested, validated and used in mesenchymal stem cell expansion and differentiation, for periods ranging from two to three weeks. Once the measurement has commenced at the beginning of culture, continuous measurements without sensor recalibration or special manual attention are carried out till the end of the culture. Measurement data clearly show the interplay between measured parameters, indicating a few stress sources present all through the culture. Additionally, it gives an overall picture of behavior of critical control parameters in an incubator and points out the need for bioprocess systems with automatic process monitoring and smart control for maximum yield, optimal growth and maintenance of the cells.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122904295","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: 11

Failure mode and effect analysis of patch-clamp laboratory instrumentation for electrophysiology measurements 电生理测量膜片钳实验室仪器的失效模式及影响分析

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-07 DOI: 10.1109/MeMeA.2017.7985853

S. Saponara, F. Fusi, S. Saponara, M. Macucci, V. Groza

引用次数: 1

Gait phase detection from thigh kinematics using machine learning techniques 基于机器学习技术的大腿运动学步态相位检测

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-07 DOI: 10.1109/MeMeA.2017.7985886

J. Farah, N. Baddour, E. Lemaire

{"title":"Gait phase detection from thigh kinematics using machine learning techniques","authors":"J. Farah, N. Baddour, E. Lemaire","doi":"10.1109/MeMeA.2017.7985886","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985886","url":null,"abstract":"Intelligent orthotic devices require accurate detection of gait events for real-time control. For orthoses that control the knee, an ideal system would only locate sensors at the thigh and knee, thereby facilitating sensor and electronics integration with the assistive device. To determine potential gait phase identification approaches, classification was implemented using J-48 Decision Tree, Random Forest, Multi-layer Perceptrons, and Support Vector Machine classifiers, along with 5-fold (5-FCV) and 10-fold cross validation (10-FCV). Knee angle, thigh angular velocity, and thigh acceleration were obtained from 31 able-bodied participants during walking (10 strides each). Strides were segmented into Loading Response, Push-Off, Swing, and Terminal Swing and features were extracted using a 0.1 second sliding window. Gait phase classification was performed with and without the knee angle parameter. J-48 Decision Tree with the knee angle parameter was ranked the best classifier due to its second highest classification accuracy of 97.5% and lowest mean absolute error of 0.014. Results without the knee angle parameter differed by only 0.5% and 0.003. Therefore, an inertial sensor with accelerometer and gyroscope output, located at the thigh, is a viable approach for classifying gait phases for intelligent orthosis control.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122004586","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: 28