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2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)最新文献

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Get Up!: Assessing Postural Activity & Transitions using Bi-Directional Gated Recurrent Units (Bi-GRUs) on Smartphone Motion Data 起来!在智能手机运动数据上使用双向门控循环单元(Bi-GRUs)评估姿势活动和转换
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962729
kar 2402565399 ku, Luke Buquicchio, Walter Gerych, E. Agu, Elke A. Rundensteiner
Many health conditions can affect a person’s mobility. Consequently, a person’s ability to perform transitions between activity states (e.g. sit-to-stand) are accurate measures of their mobility and general health. Mobility impairments can manifest either as discomfort while performing certain activity transitions or a complete inability to perform such transitions. The Timed up and Go (TUG) is an important clinical test that assesses patients’ sit-to-stand abilities. Research into passive methods to assess the quality of patients activity transitions and thus conduct the Timed Up and Go autonomously as they live their lives, have recently become popular. Machine and deep learning analysis of smartphone accelerometer and gyroscope data have demonstrated promising activity and transition recognition results. In this paper, we present Get Up!, a novel deep learning-based method to detect whether a person is performing a certain postural activity or transitioning between activities. Get Up! analyzes data from the accelerometer and gyroscope of the patient’s smartphone using Bi-Directional Gated Recurrent Units (Bi-GRU) neural networks with an attention mechanism. Our method outperforms TAHAR, the current state of the art machine learning method, achieving an error rate of 1.47% for activity classification and an accuracy of 97%. We also achieved an error rate of 0.17% with an accuracy of 93.3% when classifying postural transitions. As Get Up! segments activities and transitions, individual TUG sub-components can be timed to identify sub-components that patients find challenging.
许多健康状况都会影响一个人的行动能力。因此,一个人在活动状态(例如从坐到站)之间进行转换的能力是衡量其活动能力和总体健康状况的准确指标。行动障碍可以表现为在进行某些活动转换时的不适,也可以表现为完全无法进行这些转换。TUG (Timed up and Go)是一项重要的临床测试,用于评估患者的坐立能力。对被动方法的研究,以评估患者活动过渡的质量,从而在他们的生活中自主地进行定时起床和走,最近变得流行起来。智能手机加速计和陀螺仪数据的机器和深度学习分析显示了有希望的活动和过渡识别结果。在本文中,我们提出了Get Up!这是一种基于深度学习的新方法,用于检测一个人是否正在进行某种姿势活动或在活动之间转换。起来!利用双向门控循环单元(Bi-GRU)神经网络和注意力机制,分析来自患者智能手机加速计和陀螺仪的数据。我们的方法优于当前最先进的机器学习方法TAHAR,活动分类的错误率为1.47%,准确率为97%。在对姿势转换进行分类时,我们的错误率为0.17%,准确率为93.3%。《起来!》分段活动和过渡,单个TUG子组件可以定时识别患者认为具有挑战性的子组件。
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引用次数: 1
Wearable and Stationary Point-of-Care IoT Air Pollution Sensors for Pediatric Asthma Research and Management* 用于儿童哮喘研究和管理的可穿戴式和固定式护理点物联网空气污染传感器*
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962865
Quan Dong, Baichen Li, R. S. Downen, Nam Tran, Elizabeth Chorvinsky, D. Pillai, Mona E. Zaghloul, Zhenyu Li
The lack of mechanistic understanding of pediatric asthma development is partly due the lack of objective measures of environmental exposure metrics correlated with physiological responses. Here we report cloud-based wearable and stationary IoT air pollution sensors which can measure an asthma patient’s exposure to ozone, NO2 and aldehydes in real-life settings. The wrist-watch shaped sensor can measure formaldehyde levels in air from 30ppb to 10ppm using fuel cell technology, and continuously operate over 7 days without recharging. The smart-speaker sized stationary sensor measures ozone and NO2 from 20ppb to 1000ppb in the air. The wearable sensor can wirelessly upload data to the stationary sensor or an Android smartphone via Bluetooth Low Energy (BLE). The stationary sensor or the smartphone functions as a gateway to a cloud-based informatics system which handles sensor data storage, management and analytics. Potential applications of these point-of-care IoT sensors include epidemiological studies of asthma development and exacerbations, personalized asthma management and environmental monitoring.
缺乏对儿童哮喘发展机制的理解部分是由于缺乏与生理反应相关的环境暴露指标的客观测量。在这里,我们报告了基于云的可穿戴和固定式物联网空气污染传感器,它可以测量哮喘患者在现实生活中暴露于臭氧、二氧化氮和醛类物质的情况。这款腕表形状的传感器采用燃料电池技术,可以测量空气中的甲醛含量,范围从30ppb到10ppm,无需充电即可连续工作7天。智能扬声器大小的固定式传感器可以测量空气中的臭氧和二氧化氮,从20ppb到1000ppb。可穿戴传感器可以通过低功耗蓝牙(BLE)将数据无线上传到固定传感器或安卓智能手机。固定传感器或智能手机的功能是作为基于云的信息系统的网关,该系统处理传感器数据的存储、管理和分析。这些医疗点物联网传感器的潜在应用包括哮喘发展和恶化的流行病学研究、个性化哮喘管理和环境监测。
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引用次数: 5
Gaze-based video games for assessment of attention outside of the lab 基于注视的视频游戏,用于评估实验室外的注意力
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962737
J. Snider, L. Chukoskie
Advances in remote therapeutics also demand simultaneous development of remote assessment tools. Here, we report on a comparison of gamified assessments that we developed for assessing three components of the broad construct of attention, that will be used as part of an attention training suite designed to be used outside of the laboratory.
远程治疗的进步也要求同时开发远程评估工具。在这里,我们报告了我们开发的游戏化评估的比较,用于评估广泛的注意力结构的三个组成部分,这将被用作注意力训练套件的一部分,旨在在实验室之外使用。
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引用次数: 1
3D Printing for Whole Blood Filters Designed for Simple Integration with a Variety of Sensor Platforms 3D打印全血过滤器设计与各种传感器平台的简单集成
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962623
Benjamin Ingis, Eon Soo Lee
The ability to quickly and easily measure biomarker concentrations in a blood sample is an important element in bringing lab-on-a-chip devices to widespread point of care use. One challenge facing the development of these systems is sample preparation, specifically in the case of whole human blood. Because the red blood cells present in a whole blood sample can interfere with sensor operation, cell-free plasma is often desired as the analyte. However, at the point of care, the input into such a device is most often whole blood from a finger prick. Thus, a system is required which can easily extract the plasma from a whole blood sample and deliver it to the sensor. Because of the wide range of sensing mechanisms available, a versatile sample preparation and delivery system is desired. In this work, we introduce a PDMS microchannel system, produced partially through the use of 3D printing, which can be easily integrated with any flat form factor sensor platform, such as electrodes deposited on a silicon wafer. The system is passive, requiring no external actuation. The channel system is tested with both blood mimicking fluid (100% particle removal) and porcine whole blood (95% particle removal), and the ease of integration with a sensor platform is demonstrated. Such a device is a step toward the realization of widespread lab-on-a-chip deployment.
快速轻松地测量血液样本中生物标志物浓度的能力是将芯片实验室设备广泛应用于护理点的重要因素。这些系统发展面临的一个挑战是样品制备,特别是在全人血液的情况下。因为全血样本中的红细胞会干扰传感器的操作,所以通常需要无细胞血浆作为分析物。然而,在护理点,这种装置的输入通常是手指刺破的全血。因此,需要一种能够轻松地从全血样本中提取血浆并将其输送到传感器的系统。由于广泛的传感机制可用,一个通用的样品制备和输送系统是需要的。在这项工作中,我们介绍了一个PDMS微通道系统,部分通过使用3D打印生产,可以很容易地与任何平面形状的传感器平台集成,例如沉积在硅片上的电极。该系统是被动的,不需要外部驱动。该通道系统用血液模拟液(100%去除颗粒)和猪全血(95%去除颗粒)进行了测试,并证明了与传感器平台集成的便利性。这种装置是实现广泛的芯片实验室部署的一步。
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引用次数: 2
A Portable Colorimetric Reader for Early and Rapid Diagnosis of Sepsis 一种用于败血症早期快速诊断的便携式比色仪
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962853
M. Shah, J. Joseph, R. Kedia, Shalini Gupta, V. Sritharan
Septicemia or in short sepsis affects nearly 30 million people worldwide. Current clinical identification of sepsis includes culture-based methods that have a long turnaround time or monitoring of patient response that adds delay to therapy. There is currently no point-of-care care (PoC) device that allows both rapid and early sepsis diagnosis by the bedside. We have developed a portable colorimetric kit called Septiflo that gives concentration-dependent qualitative estimate of the sepsis-associated bacterial infection load in blood under 10 min. However, the results of this naked eye assessment remain somewhat subjective. In this paper, we present a handheld optical reader that can quantify the signal output of the Septiflo device making it a substantially more robust and accurate way to diagnose sepsis. The repeatability coefficient of variation (CoV) of this device when tested on five reference cartridges was found to be < 9 % and the reproducibility CoV across two reader instruments was < 8.2 %. The prototype instrument was also tested with human plasma samples in the clinically valid endotoxin concentration range of 1 to 1000 pg/mL. The calibrated values from the instrument and the known endotoxin concentrations correlated significantly with an R2 value of 0.97. The reader instrument’s hardware architecture and software algorithm are described below in detail.
败血症或简而言之败血症影响着全世界近3000万人。目前脓毒症的临床鉴定包括基于培养的方法,这些方法需要很长的周转时间或监测患者的反应,这增加了治疗的延迟。目前还没有即时护理(PoC)设备可以在床边快速和早期诊断败血症。我们开发了一种名为Septiflo的便携式比色试剂盒,可以在10分钟内对血液中败血症相关细菌感染负荷进行浓度依赖的定性估计。然而,这种肉眼评估的结果仍然有些主观。在本文中,我们提出了一种手持式光学读取器,可以量化Septiflo设备的信号输出,使其成为诊断败血症的更稳健和准确的方法。该仪器在5个参考盒上的重复性变异系数(CoV) < 9%,在2种阅读器上的重复性CoV < 8.2%。在临床有效内毒素浓度范围为1 ~ 1000 pg/mL的人血浆样品中,对原型仪器进行了测试。仪器标定值与已知内毒素浓度显著相关,R2值为0.97。详细介绍了读卡器的硬件结构和软件算法。
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引用次数: 0
3D Printed Microfluidic Actuation System for Multi-step Paper-based Assays 用于多步骤纸质检测的3D打印微流体驱动系统
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962668
Sumeyra Agambayev, Mark S. Bailly, J. Christen
We present a novel 3D printed Microfluidic Actuation System for lateral flow assay in low resource settings. The system is used to deliver reagents for multi-step assays from blisters placed into cavities in the 3D printed assembly. The system is operated by manually depressing the blister housing and rotating to the next blister location. This is repeated for each step in the assay to enable a simple and repeatable method of delivering specified volumes to the assay at arbitrary time intervals as required by the assay. The blisters provide for robust storage while maintaining consistent aliquots for the assay. We characterize the percent of the total volume delivered to the lateral flow assay from the blisters including the volume dispensed at given time intervals.
我们提出了一种新的3D打印微流体驱动系统,用于低资源环境下的横向流动分析。该系统用于从放置在3D打印组件空腔中的水泡中输送试剂,用于多步骤分析。该系统通过手动压低吸泡外壳并旋转到下一个吸泡位置来操作。这在分析中的每一步都是重复的,以实现一种简单和可重复的方法,根据分析要求在任意时间间隔向分析提供指定的体积。泡罩提供了强大的存储,同时保持一致的定量分析。我们描述了从水疱输送到侧流分析的总体积的百分比,包括在给定时间间隔分配的体积。
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引用次数: 0
Weighted Extreme Learning Machine for Dengue Detection with Class-imbalance Classification 基于类不平衡分类的登革热检测加权极值学习机
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962825
Wanchaloem Nadda, W. Boonchieng, E. Boonchieng
Dengue is a disease caused by mosquitoes that may even be lethal to some patients. It is important to detect this disease as soon as possible to decrease the death toll. In this research, we use machines to classify patients as Dengue patients and Non-Dengue patients. The dataset is the treatment data from the patients with fever, cold, flu, pneumonia, and Dengue, from Sarapee Hospital, Chiangmai province, Thailand, during September 2015 to September 2017. The dataset includes 248 records of Dengue patients and 4,960 records of Non-Dengue patients including patient with fever, cold, flu, and pneumonia. We use the text of symptoms of the patients for input data. Weighted Extreme Learning Machine (WELM) is used to solve the class imbalance problems. It was compared for accuracy with neural network and Extreme Learning Machine (ELM). The result shows, that if the number of records of Non-Dengue patients are increasing, the accuracy of the neural network and ELM are decreasing, but the accuracy of WELM is stable.
登革热是一种由蚊子引起的疾病,对一些病人来说甚至可能致命。重要的是尽快发现这种疾病,以减少死亡人数。在本研究中,我们使用机器将患者分为登革热患者和非登革热患者。该数据集是2015年9月至2017年9月期间泰国清迈省Sarapee医院发烧、感冒、流感、肺炎和登革热患者的治疗数据。该数据集包括248个登革热患者记录和4960个非登革热患者记录,包括发烧、感冒、流感和肺炎患者。我们使用患者的症状文本作为输入数据。采用加权极值学习机(WELM)来解决类不平衡问题。并与神经网络和极限学习机(ELM)进行了精度比较。结果表明,随着非登革热患者病历数量的增加,神经网络和ELM的准确率均下降,而WELM的准确率保持稳定。
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引用次数: 5
A Motion Free Image Based TRF Reader for Quantitative Immunoassay 一种用于定量免疫分析的无运动图像TRF阅读器
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962655
S. Karthik, M. Shah, Satheesh Natarajan, Mahesh Shetty, J. Joseph
Time resolved acquisition of fluorescence provides advantages of reduced background reflection and reduced analyte autofluorescence, considerably improving the signal to background ratio. Europium chelate with its relatively longer fluorescence decay in milliseconds can be analyzed with inexpensive detectors with simpler timing considerations. In this work we present a Time Resolved Fluorescence (TRF) reader using a monochrome camera and its associated exposure trigger circuit to capture TRF from Europium chelate striped on nitrocellulose membrane. The reader is imaging based and does not require complex mechanical moving parts to read the test strip under investigation. Ten different concentrations of Europium between 100 ng/ml and 1000 ng/ml were imaged and the output of the developed TRF reader was found to be linear (R2=0.9873) over the range of concentrations. An improvement of 70% was observed in the signal to background ratio using TRF technique.
时间分辨的荧光采集提供了减少背景反射和减少分析物自身荧光的优点,大大提高了信本比。铕螯合物的荧光衰减相对较长,以毫秒为单位,可以用便宜的检测器进行分析,时间考虑更简单。在这项工作中,我们提出了一种时间分辨荧光(TRF)阅读器,使用单色相机及其相关的曝光触发电路,从硝酸纤维素膜上的铕螯合物条纹中捕获TRF。阅读器是基于成像的,不需要复杂的机械运动部件来读取正在调查的测试条。在100 ng/ml到1000 ng/ml之间对10种不同浓度的铕进行成像,发现所开发的TRF阅读器的输出在浓度范围内呈线性(R2=0.9873)。采用TRF技术后,信本比提高了70%。
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引用次数: 3
A Novel Nanoscale Electrode for Biosensing 一种新型纳米生物传感电极
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962645
Alperen Guver, P. Milas, M. Guy, Mustafa T. Sigindere, M. Yigit, Birol Ozturk
Nanoscale electrodes are becoming increasingly popular in Scanning Electrochemical Microscopy (SECM) due to their unique inherent properties. However, their preparation with current methods is laborious and not cost-effective, hindering the effective use of SECM in nanoscale detection and imaging. We have developed a novel and cost-effective nanoscale SECM electrode preparation method with electrochemically grown gold nanowires. Our method allows simple diameter tuning of nanowires and their direct interfacing with tungsten wires, enabling facile electrode preparation. The method is very cost-efficient as salt solutions of target noble metals are used in growing nanowires directly from tapered tungsten wires. The selective detection of target molecule is achieved by attaching DNA aptamers on the electrode surface. DNA aptamers are terminated with Methylene Blue redox molecules and an electronic signal is recorded with standard voltammetry due to target induced conformal change in the aptamers. The aptamer-based nanowire electrodes were successfully utilized in the detection of picomolar concentration ATP molecules.
纳米级电极由于其独特的固有性质在扫描电化学显微镜(SECM)中越来越受欢迎。然而,用目前的方法制备它们既费力又不划算,阻碍了SECM在纳米级检测和成像中的有效应用。我们开发了一种新颖的、具有成本效益的用电化学生长的金纳米线制备纳米级SECM电极的方法。我们的方法可以简单地调整纳米线的直径,并直接与钨丝连接,使电极制备变得容易。该方法使用目标贵金属盐溶液直接从锥形钨丝中生长纳米线,具有很高的成本效益。通过在电极表面附着DNA适体来实现靶分子的选择性检测。用亚甲基蓝氧化还原分子终止DNA适体,用标准伏安法记录由于靶诱导适体的保形变化而产生的电子信号。基于适配体的纳米线电极成功地用于皮摩尔浓度ATP分子的检测。
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引用次数: 0
Acoustic Assessment of Treatment Response for Children with Acute Asthma Exacerbation 儿童急性哮喘加重治疗反应的声学评价
Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962830
Adam Rao, Grant Pemberton, Sean Rubin, E. Wu, Aaron E. Kornblith
Asthma is the most common pediatric chronic illness and acute asthma exacerbations in children lead to numerous emergency department (ED) visits each year. Current methods to gauge a child’s response to treatment rely on a mixture of qualitative and quantitative measures and require experienced practitioners. In this work, we present a child-friendly acoustic device developed with the aim of expediting and quantifying assessment of treatment responsiveness for this vulnerable population. The device acquires measurements from a digital stethoscope as sound is sent through the chest using a custom chest exciter. In this work, we compared sound transmission from patients before and after administration of hospital albuterol sulfate nebulizer. One hundred and forty recordings were collected from ten children that presented to the ED for acute asthma exacerbation. Preliminary data is presented for these patients, demonstrating a shift of approximately 2 dB after treatment and relief of symptoms. This improvement was also validated using an established asthma assessment scoring system.
哮喘是最常见的儿科慢性疾病,儿童急性哮喘加重每年导致大量急诊(ED)就诊。目前衡量儿童对治疗反应的方法依赖于定性和定量措施的混合,需要有经验的从业人员。在这项工作中,我们提出了一种儿童友好的声学装置,旨在加速和量化评估这一弱势群体的治疗反应。该设备从数字听诊器获取测量值,同时使用定制的胸部激励器将声音发送到胸部。在这项工作中,我们比较了患者在使用医院硫酸沙丁胺醇雾化器前后的声音传播。从10名因急性哮喘加重而到急诊科就诊的儿童中收集了140段录音。这些患者的初步数据显示,在治疗和症状缓解后,血压升高约2db。使用已建立的哮喘评估评分系统也验证了这种改善。
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引用次数: 0
期刊
2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)
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