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2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)最新文献

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Evaluation of QoS in data mobile network for vital signs transmission 数据移动网络中生命体征传输的QoS评价
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/HIC.2016.7797718
D. Chandy, A. Soto, M. Huerta, J. Bermeo, R. Clotet, G. Sagbay, R. Ávila
{"title":"Evaluation of QoS in data mobile network for vital signs transmission","authors":"D. Chandy, A. Soto, M. Huerta, J. Bermeo, R. Clotet, G. Sagbay, R. Ávila","doi":"10.1109/HIC.2016.7797718","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797718","url":null,"abstract":"The quality of pre-hospital care and timely coordination of the stakeholders in the public health network, play a very important role maintaining the status of a patient. The integration of technology in emergency scenarios is proposed as a tool to improve response times, monitor patient status and even perform video-consultations between the site of the incident and medical personnel located in certain clinics. The parameters of QoS (maximum latency and percentage of packet loss) that the network must provide to the different telemedicine services, as well as the logical infrastructure, physical infrastructure and network devices that comprise it were also defined. The performance of the LTE network for the uplink data flow was evaluated through NS-3 software. The results show that the network performance decreases when the traffic generated by other users increase or by increasing the bit rate of the information from ambulances. Additionally, it showed that the network performance can improve substantially by increasing radio resources or bandwidth channel of the LTE network.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"02 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129126544","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: 7
A fabric-based wearable band for hand gesture recognition based on filament strain sensors: A preliminary investigation 一种基于纤维应变传感器的可穿戴手势识别手环:初步研究
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/hic.2016.7797710
Andrea Ferrane, X. Jiang, L. Maiolo, A. Pecora, L. Colace, C. Menon
{"title":"A fabric-based wearable band for hand gesture recognition based on filament strain sensors: A preliminary investigation","authors":"Andrea Ferrane, X. Jiang, L. Maiolo, A. Pecora, L. Colace, C. Menon","doi":"10.1109/hic.2016.7797710","DOIUrl":"https://doi.org/10.1109/hic.2016.7797710","url":null,"abstract":"A wearable system based on a breathable cloth wristband equipped with stretchable strain gauge sensors were assembled and tested to detect a set of 16 different hand gestures. The sensors embedded on the wristband prototype do not require a direct contact with the skin, thus maximizing comfort. To evaluate the performance of the developed band, different gestures were labelled by using grasping information detected in real-time by commercial Force-Sensing Resistor (FSR) sensors. Signals recorded by the wristband were processed through two machine-learning algorithms, i.e. Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), reaching accuracies of 87% and 95% respectively.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131441823","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: 27
An mHealth hybrid app for self-reporting pain measures for sickle cell disease 一款用于镰状细胞病自我报告疼痛测量的移动健康混合应用程序
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/HIC.2016.7797726
K. Garry, Pooja Rallabhandi, Elizabeth Walek, Margaret Y. Nettleton, Ishrat Ahmed, Jishuan Wang, Kevin Cleary, Z. Quezado
{"title":"An mHealth hybrid app for self-reporting pain measures for sickle cell disease","authors":"K. Garry, Pooja Rallabhandi, Elizabeth Walek, Margaret Y. Nettleton, Ishrat Ahmed, Jishuan Wang, Kevin Cleary, Z. Quezado","doi":"10.1109/HIC.2016.7797726","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797726","url":null,"abstract":"The utilization of acute health care and readmission rates among sickle cell disease patients are very high and are associated with significant health care costs and disparities. Mobile technology can help assess adherence to therapeutic interventions in sickle cell disease and other pain syndromes, and decrease barriers to continuity of care (i.e., limited hospital access, travel difficulties). However, it is unclear whether this technology can improve monitoring of patients' clinical outcomes (pain, anxiety, fatigue, mobility). In this paper we report on an ongoing project to utilize web and mobile technology to monitor clinical outcomes for patients with sickle cell disease. We share preliminary results of pilot studies using the technology for pediatric patients, and describe our current efforts to reduce hospital readmission rates.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"47 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122846648","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
Point-of-care HIV-1 diagnostic with integrated nucleic acid extraction and amplification from whole blood 利用全血综合核酸提取和扩增技术即时诊断HIV-1
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/HIC.2016.7797737
Mark D. Borysiak, Andrew T. Bender, D. Boyle, J. Posner
{"title":"Point-of-care HIV-1 diagnostic with integrated nucleic acid extraction and amplification from whole blood","authors":"Mark D. Borysiak, Andrew T. Bender, D. Boyle, J. Posner","doi":"10.1109/HIC.2016.7797737","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797737","url":null,"abstract":"The HIV/AIDS epidemic continues to be a major global health challenge, and accurate, affordable HIV-1 viral load testing is increasingly needed at the point-of-care (POC). Nucleic acid amplification tests (NAATs) provide high diagnostic accuracy of infectious diseases, yet most systems are restricted to central laboratories due to assay and instrumentation complexity. Here we describe a NAAT with integrated sample preparation and amplification using isotachophoresis and recombinase polymerase amplification. We argue that this approach has the potential to reduce the cost and complexity of point-of-care (POC) NAATs. We demonstrate the detection of HIV-1 nucleic acids in whole blood. Preliminary data demonstrate linearity at low copy number which may provide valuable quantitative data on the HIV viral load of a patient.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"367 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116449540","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: 3
Gait monitoring system for patients with Parkinson's disease using wearable sensors 使用可穿戴传感器的帕金森病患者步态监测系统
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/HIC.2016.7797687
Shyam V. Perumal, R. Sankar
{"title":"Gait monitoring system for patients with Parkinson's disease using wearable sensors","authors":"Shyam V. Perumal, R. Sankar","doi":"10.1109/HIC.2016.7797687","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797687","url":null,"abstract":"The goal of this research is to develop a gait monitoring system for patients with Parkinson's disease (PD) using wearable sensors. To achieve this objective, the first step of our work is to identify the most significant features that would best distinguish between subjects with PD and healthy control subjects. Here, various gait features were extracted using data obtained from an online database (Physionet) and further analyzed to find the most significant features that would provide the best discrimination between the two groups. The statistical analysis of variance (ANOVA) test was conducted to differentiate the subjects based on the values of the mean and pattern classification was carried out using the Linear Discriminant Analysis (LDA) algorithm. The results show that a distinct set of gait features (step distance, stance and swing phases) contributed significantly in achieving a better classification accuracy rate.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116805334","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
The Lab-on-PCB framework for affordable, electronic-based point-of-care diagnostics: From design to manufacturing 可负担得起的基于电子的即时诊断的pcb实验室框架:从设计到制造
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/HIC.2016.7797713
N. Vasilakis, K. Papadimitriou, D. Evans, H. Morgan, T. Prodromakis
{"title":"The Lab-on-PCB framework for affordable, electronic-based point-of-care diagnostics: From design to manufacturing","authors":"N. Vasilakis, K. Papadimitriou, D. Evans, H. Morgan, T. Prodromakis","doi":"10.1109/HIC.2016.7797713","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797713","url":null,"abstract":"A novel, Lab-on-Printed Circuit Board (LoPCB) manufacturing technology is demonstrated for the development of low-cost electrochemical biosensors combined with microfluidics for Point-of-Care (PoC) applications. An analysis of the developed PCB architecture is presented, detailing the three development areas of the proposed LoPCB platform, i.e. microfluidics, biosensors and electronics. Design rules and potential fabrication limitations are also discussed, based on the characterization of prototype fabricated systems. Two PCB-based devices have been designed and fabricated, a microfluidic active diluter with a variable and actively controlled dilution ratio and an electrochemical biosensor. The obtained results demonstrate the feasibility of a complete LoPCB platform, where all three compartments will co-exist and co-operate, providing an electronic-based PoC system for electrochemical biosensing.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124957739","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: 10
An intelligent system to assist the diagnosis of epilepsy disorder in children: A case of study 协助儿童癫痫症诊断的智能系统:个案研究
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/HIC.2016.7797717
Sunaina Singh-Mugica, B. Tovar-Corona, M. A. Silva-Ramírez, Laura Ivoone Garay Jiménez
{"title":"An intelligent system to assist the diagnosis of epilepsy disorder in children: A case of study","authors":"Sunaina Singh-Mugica, B. Tovar-Corona, M. A. Silva-Ramírez, Laura Ivoone Garay Jiménez","doi":"10.1109/HIC.2016.7797717","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797717","url":null,"abstract":"The proposed intelligent system MAED (Medical assistance for epilepsy diagnosis) was designed and implemented using fuzzy logic and Bayes method as inference tools to assist in epilepsy diagnosis in children. This disease can be misdiagnosed because either it is not evident in the electroencephalographic (EEG) recording or because the clinical symptoms are mistaken with other disorders. Therefore, it becomes necessary to consider both, clinical and paraclinical (EEG) information to achieve an accurate diagnosis. A set of 25 children (22 epileptic, 3 hyperactive), was used to test the system in order to establish the probability of epilepsy diagnosis. This system helps to reinforce the physician diagnosis through the systematic analysis of the patient information because is based on the standard clinical guidelines. MAED could also be used as a training tool for improving the knowledge of the medical specialist student.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127406590","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
A cancer detection device utilizing multi-tiered neural networks for improved classification 一种利用多层神经网络改进分类的癌症检测装置
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/HIC.2016.7797705
J. Shell, W. D. Gregory
{"title":"A cancer detection device utilizing multi-tiered neural networks for improved classification","authors":"J. Shell, W. D. Gregory","doi":"10.1109/HIC.2016.7797705","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797705","url":null,"abstract":"We introduce a multi-tiered neural network architecture that accurately classifies malignant breast tissue from benign breast tissue. The methodology implemented six different backpropagation neural network (BNN) architectures on 180 malignant and 180 benign breast tissue impedance data files sampled at 47 frequencies from 1 hertz (Hz) to 32 megahertz (MHz). The data were collected utilizing a NovaScan cancer detection prototype device in an approved IRB study at Aurora Medical Center, Milwaukee. The BNN analysis consists of a multi-tiered consensus approach autonomously selecting 4 of 6 neural networks to determine a malignant or benign classification. The BNN analysis was then compared to the histology results with consistent sensitivity of 100 percent and a specificity of 100 percent. This implementation successfully relied solely on statistical variation between the histologically confirmed benign and malignant impedance data and intricate neural network analysis. This approach could be a valuable tool to augment current medical practice assessment of the health of breast and other tissue.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130425342","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
Early diagnosis and predictive monitoring of skin diseases 皮肤病的早期诊断和预测监测
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/HIC.2016.7797690
N. Dhinagar, M. Celenk
{"title":"Early diagnosis and predictive monitoring of skin diseases","authors":"N. Dhinagar, M. Celenk","doi":"10.1109/HIC.2016.7797690","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797690","url":null,"abstract":"Skin diseases like melanoma are traditionally screened by a visual analysis of key features, such as the pigmentation and vascularity of the region of interest. Monitoring the changes of these features during follow-up imaging sessions is critical towards a correct medical diagnosis. This paper proposes a framework to monitor these changes on the skin over time. The proposed framework utilizes the Lucas-Kanade displacement flow implementation to detect the severity of spatial changes in the skin. These spatial changes are captured via the magnitude and direction of the vectors in the resultant displacement field. This change monitoring is tested for surface and sub-surface skin image data. The proposed framework is developed and validated with skin samples of cutaneous melanoma, setting the stage for future extension to images from other skin diseases. The skin sample images would be classified as high and low risk based on the severity of change. Further, a predictive algorithm is devised to estimate the change in the high risk skin lesions, providing significant information to determine the course of medical action.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115565907","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
A novel heart rate monitoring method using a smartphone 一种使用智能手机的新型心率监测方法
2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT) Pub Date : 2016-11-01 DOI: 10.1109/HIC.2016.7797683
Rifat-uz Zaman, C. Cho, Yeesock Kim, J. Chong
{"title":"A novel heart rate monitoring method using a smartphone","authors":"Rifat-uz Zaman, C. Cho, Yeesock Kim, J. Chong","doi":"10.1109/HIC.2016.7797683","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797683","url":null,"abstract":"Accurate heart rate detection is important in healthcare and exercise monitoring. Recently, heart rate monitoring using a smartphone has been highlighted due to its convenience and accuracy. In this paper, we hypothesize that our smartphone-based heart rate detection algorithm reliably detects heart rate based on fingertip image changes. Here, we have used successive video camera fingertip images with edge detection and smoothing techniques to process the fingertip images and to find out the heart rate of the subject. To investigate the capability of our proposed algorithm, we recruited 3 subjects and collected 2-min video data from each subject. We evaluated the performance of our proposed method by comparing it to the previous average intensity-based method [1]. Test results show that our proposed and previous methods give similar heart rate detection performance.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129145754","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
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