2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)最新文献_第5页

A highly sensitive microfluidic device for bacterial detection in blood serum 一种用于血清细菌检测的高灵敏度微流控装置

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227601

M. Al-Adhami, E. Tan, G. Rao, Y. Rostov

引用次数: 1

Pulse waveform as an indicator of baseline offset in pulse transit time based blood pressure estimation 在基于脉冲传递时间的血压估计中，脉搏波形作为基线偏移的指标

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227576

Chen Lin, Yuan Zhou, Hu Wang, Yao Wang

{"title":"Pulse waveform as an indicator of baseline offset in pulse transit time based blood pressure estimation","authors":"Chen Lin, Yuan Zhou, Hu Wang, Yao Wang","doi":"10.1109/HIC.2017.8227576","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227576","url":null,"abstract":"Cuff-less blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for long-term BP monitoring. However, state-of-art PTT models are unable to trace the change of pressure baseline in subjects, which limits their application in long-term BP tracking. This study investigated the relationship between the change of pressure baseline and pulse waveform in long-term BP monitoring. In the study, a total of 36 subjects received daily monitoring of systolic BP (SBP) and PTT for over one month. Linear regression was used to develop the SBP-ln(PTT) model for each subject. SBP predictions with regression differences greater than + SD (7.63 mmHg) were assumed to be with positive/negative baseline offset. For each subject, 12 features extracted from pulse waveform were obtained and their values were converted to standard scores to quantify pulse waveform variation. Independent two-sample t-test showed five pulse wave features changed significantly when subjects' pressure baseline varied. Furthermore, the consistency of pulse waveform variation was validated over the change of pressure baseline in subjects. In summary, this study demonstrated that pulse waveform could indicate baseline offset in PTT-based BP estimation. By highlighting five pulse wave features, this study provides novel insights to overcome the challenge of frequent calibrations in long-term PTT-based BP monitoring.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121389913","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

Sport analytics platform for athletic readiness assessment 用于运动准备评估的运动分析平台

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227608

B. Moatamed, Sajad Darabi, Migyeong Gwak, Mohammad Kachuee, Casey J. Metoyer, Mike Linn, M. Sarrafzadeh

{"title":"Sport analytics platform for athletic readiness assessment","authors":"B. Moatamed, Sajad Darabi, Migyeong Gwak, Mohammad Kachuee, Casey J. Metoyer, Mike Linn, M. Sarrafzadeh","doi":"10.1109/HIC.2017.8227608","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227608","url":null,"abstract":"Many coaches and athletes are showing an increasing interest in training monitoring systems every year. There is a plethora of performance markers that can aid in a coaches assessment of physiological and psychological conditions of their athletes. These markers can indicate an athletes readiness for competition, adaptation to training, or risk for injury. However, studies have shown examination of these performance markers individually may not result in a clear perception of ones performance. Hence, an inclusive analysis of these metrics is required to achieve meaningful assessment. Recently with the growing use of wearable activity trackers, we have access to many of these markers. Currently, there are a few sport monitoring tools which are using a subset of these metrics and are mostly providing real-time data visualization to coaching staff. However, an appropriate athletic performance monitoring system should be intuitive, provide useful data analysis, feedback and reliable predictions to coaches and athletes. In this paper, we are proposing an athletic monitoring system which collects a comprehensive set of metrics and visualize them in real-time and informs coaches about athlete's readiness score.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131221633","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: 4

Implementing clinical practice guidelines for chronic obstructive pulmonary disease in an EHR system 在电子病历系统中实施慢性阻塞性肺疾病的临床实践指南

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227606

Marisa Walker, Weiwei Ge, J. Gichoya, S. Purkayastha

引用次数: 0

A dedicated bit-serial hardware neuron for massively-parallel neural networks in fast epilepsy diagnosis 用于大规模并行神经网络快速癫痫诊断的专用位串行硬件神经元

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227595

Si Mon Kueh, T. Kazmierski

引用次数: 3

A biosignal-specific processing tool for machine learning and pattern recognition 用于机器学习和模式识别的生物信号特定处理工具

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227588

Mohsen Nabian, A. Nouhi, Yu Yin, S. Ostadabbas

{"title":"A biosignal-specific processing tool for machine learning and pattern recognition","authors":"Mohsen Nabian, A. Nouhi, Yu Yin, S. Ostadabbas","doi":"10.1109/HIC.2017.8227588","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227588","url":null,"abstract":"Electrocardiogram (ECG), Electrodermal Activity (EDA), Electromyogram (EMG) and Impedance Cardiography (ICG) are among physiological signals widely used in various biomedical applications including health tracking, sleep quality assessment, early disease detection/diagnosis and human affective state recognition. This paper presents the development of a biosignal-specific processing and feature extraction tool for analyzing these physiological signals according to the state-of-the-art studies reported in the scientific literature. This tool is intended to assist researchers in machine learning and pattern recognition to extract feature matrix from these bio-signals automatically and reliably. In this paper, we provided the algorithms used for the signal-specific filtering and segmentation as well as extracting features that have been shown highly relevant to a better category discrimination in an intended application. This tool is an open-source software written in MATLAB and made compatible with MathWorks Classification Learner app for further classification purposes such as model training, cross-validation scheme farming, and classification result computation.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129343235","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

Multiplexed detection of infectious diseases with microfluidic loop-mediated isothermal amplification and a smartphone 用微流控环介导的等温扩增和智能手机多路检测传染病

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227629

F. Sun, Weili Chen, Hojeong Yu, Akid Omob, Ryan Brisbin, A. Ganguli, V. Vemuri, P. Strzeboński, Guangzhe Cui, K. J. Allen, Smit Desai, Weiran Lin, David M. Nash, D. Hirschberg, Ian Brooks, R. Bashir, B. Cunningham

{"title":"Multiplexed detection of infectious diseases with microfluidic loop-mediated isothermal amplification and a smartphone","authors":"F. Sun, Weili Chen, Hojeong Yu, Akid Omob, Ryan Brisbin, A. Ganguli, V. Vemuri, P. Strzeboński, Guangzhe Cui, K. J. Allen, Smit Desai, Weiran Lin, David M. Nash, D. Hirschberg, Ian Brooks, R. Bashir, B. Cunningham","doi":"10.1109/HIC.2017.8227629","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227629","url":null,"abstract":"New tools are needed to enable rapid detection, identification, and reporting of infectious viral and microbial pathogens in a wide variety of point-of-care applications that impact human and animal health. We report the design, construction, and characterization of a platform for multiplexed analysis of disease-specific DNA sequences that utilizes a smartphone camera as the sensor in conjunction with a handheld instrument that interfaces the phone with a silicon-based microfluidic chip. Utilizing specific nucleic acid sequences for four equine respiratory pathogens as representative examples, we demonstrated the ability of the system to use a single 15-μL droplet of test sample to perform selective positive/negative determination of target sequences, including integrated experimental controls, in approximately 30 minutes. The system achieves detection limits comparable to those obtained by laboratory-based methods and instruments.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127694822","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

Proprioceptive improvements of lower-limb amputees under training with a vibrotactile device — A pilot study 振动触觉装置训练下下肢截肢者本体感觉的改善-一项初步研究

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227626

Jairo Maldonado-Contreras, P. Marayong, I-Hung Khoo, Rae Rivera, Brian Ruhe, Will Wu

{"title":"Proprioceptive improvements of lower-limb amputees under training with a vibrotactile device — A pilot study","authors":"Jairo Maldonado-Contreras, P. Marayong, I-Hung Khoo, Rae Rivera, Brian Ruhe, Will Wu","doi":"10.1109/HIC.2017.8227626","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227626","url":null,"abstract":"Limited mobility severely impacts the quality of life of persons with lower-limb amputations. Therefore, it is imperative to develop proper rehabilitation techniques to prevent falls and injuries. A vibrotactile device was developed as a training tool to enhance the rehabilitation of persons with recent lower-limb amputations. Stimuli provided by the device trains the user to sense discrete perturbations and then perform a corrective movement to reduce the chance of a fall. This pilot study was conducted to test the functionality of the device in improving the prosthetic proprioception of lower-limb amputees and the effect of the training instruction on motor learning. Two subjects were included in this study, one control and one receiving experimental training, with both subjects performing standing and walking tasks. Standing trials were used to evaluate the improvements in response and movement times and walking trials were tested for improvements in correct movement. In the standing task, the control and the experimental subject showed a 0.1% and 17% improvement in response time, respectively. In the walking task, both subjects showed improvements in making correct movement. Future work will focus on the design improvements of the device and the experiment protocols to further evaluate the effectiveness of the training.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124233472","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

Association rule mining for risk prediction and stratification: A philips lifeline case study 关联规则挖掘风险预测和分层:飞利浦生命线案例研究

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227593

A. Samadani, D. Schulman, Portia E. Singh, Mladen Milošević

引用次数: 0

BCG algorithm for unobtrusive heart rate monitoring 用于非突发性心率监测的BCG算法

2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT) Pub Date : 2017-11-01 DOI: 10.1109/HIC.2017.8227614

E. Pino, Javier A. P. Chávez, P. Aqueveque

{"title":"BCG algorithm for unobtrusive heart rate monitoring","authors":"E. Pino, Javier A. P. Chávez, P. Aqueveque","doi":"10.1109/HIC.2017.8227614","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227614","url":null,"abstract":"Ballistocardiogram (BCG) has been revisited in the last years as an unobtrusive method to detect heart beats. New electromechanical film (EMFi) sensors are now able to detect minimal oscillations in its surface, allowing to detect the mechanical action of the heart as it beats. This has allowed to develop unobtrusive systems for heart rate monitoring to be used as Point-of-Care devices, and to deploy them in waiting rooms, assisted living facilities or at home. In this work, an EMFi sensor is used to measure BCG via the pressure changes on the seat produced by the beating heart. In a lab environment, 34 healthy volunteers are measured under two conditions: at rest and after exercise, simultaneously with ECG. Also, in a clinical environment, 24 volunteers are also measured while waiting. The algorithm looks for the variability of the length transform at different scales or windows to determine a search window to detect beats from the BCG. A second correlation filter helps eliminate false peaks detected due to noise in the signal. Results show that in resting conditions, the mean error between the BCG HR and the reference ECG is only 0.4 beats per minute, with a standard deviation of 1.88. The noise rejection accuracy is 93%. The proposed algorithm can be used to identify beats and issue alarms under abnormal rhythms, providing timely alerts for at-risk population.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131386189","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: 19