Pub Date : 2019-11-01DOI: 10.1109/HI-POCT45284.2019.8962890
Imran M. Saied, Syed Ali Akbar Hussainy
In recent years, there have been considerable developments in smart wearable devices and unobtrusive monitoring systems that can be used in detecting and monitoring a patient’s health. However, these technological advances have not been implemented for head diagnostics, where the majority of hospitals still relying on MRI or CT scans which are bulky and expensive. In this paper, a wearable and portable device is presented that can be used for microwave head diagnostic systems. The device contains 8 RF sensors that are placed in the inner lining of a hat. The sensors are then connected to a miniaturized vector network analyzer (VNA) that generates and receives signals from the sensors. The signals from the VNA can be captured and processed in a laptop, or it can transfer the data via a Bluetooth module to a mobile device that can process the data in an app. Experiments were performed on a brain phantom to verify the performance of the device. Objects of different sizes were placed in the phantom and measured to represent diseases such as stroke and tumour. Results from the experiments showed that the deice was capable of detecting different levels of diseases in the brain. As a result, the proposed device provides a promising technique for non-invasive head diagnostics that is wearable, portable, and inexpensive.
{"title":"Portable and Wearable Device for Microwave Head Diagnostic Systems","authors":"Imran M. Saied, Syed Ali Akbar Hussainy","doi":"10.1109/HI-POCT45284.2019.8962890","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962890","url":null,"abstract":"In recent years, there have been considerable developments in smart wearable devices and unobtrusive monitoring systems that can be used in detecting and monitoring a patient’s health. However, these technological advances have not been implemented for head diagnostics, where the majority of hospitals still relying on MRI or CT scans which are bulky and expensive. In this paper, a wearable and portable device is presented that can be used for microwave head diagnostic systems. The device contains 8 RF sensors that are placed in the inner lining of a hat. The sensors are then connected to a miniaturized vector network analyzer (VNA) that generates and receives signals from the sensors. The signals from the VNA can be captured and processed in a laptop, or it can transfer the data via a Bluetooth module to a mobile device that can process the data in an app. Experiments were performed on a brain phantom to verify the performance of the device. Objects of different sizes were placed in the phantom and measured to represent diseases such as stroke and tumour. Results from the experiments showed that the deice was capable of detecting different levels of diseases in the brain. As a result, the proposed device provides a promising technique for non-invasive head diagnostics that is wearable, portable, and inexpensive.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117222180","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}
Pub Date : 2019-11-01DOI: 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。
{"title":"Get Up!: Assessing Postural Activity & Transitions using Bi-Directional Gated Recurrent Units (Bi-GRUs) on Smartphone Motion Data","authors":"kar 2402565399 ku, Luke Buquicchio, Walter Gerych, E. Agu, Elke A. Rundensteiner","doi":"10.1109/HI-POCT45284.2019.8962729","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962729","url":null,"abstract":"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.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130701753","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}
Pub Date : 2019-11-01DOI: 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.
{"title":"Gaze-based video games for assessment of attention outside of the lab","authors":"J. Snider, L. Chukoskie","doi":"10.1109/HI-POCT45284.2019.8962737","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962737","url":null,"abstract":"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.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115894568","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}
Pub Date : 2019-11-01DOI: 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.
{"title":"3D Printing for Whole Blood Filters Designed for Simple Integration with a Variety of Sensor Platforms","authors":"Benjamin Ingis, Eon Soo Lee","doi":"10.1109/HI-POCT45284.2019.8962623","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962623","url":null,"abstract":"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.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123034024","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}
Pub Date : 2019-11-01DOI: 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.
{"title":"A Portable Colorimetric Reader for Early and Rapid Diagnosis of Sepsis","authors":"M. Shah, J. Joseph, R. Kedia, Shalini Gupta, V. Sritharan","doi":"10.1109/HI-POCT45284.2019.8962853","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962853","url":null,"abstract":"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.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123419712","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}
Pub Date : 2019-11-01DOI: 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.
{"title":"3D Printed Microfluidic Actuation System for Multi-step Paper-based Assays","authors":"Sumeyra Agambayev, Mark S. Bailly, J. Christen","doi":"10.1109/HI-POCT45284.2019.8962668","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962668","url":null,"abstract":"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.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130270421","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}
Pub Date : 2019-11-01DOI: 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.
{"title":"Weighted Extreme Learning Machine for Dengue Detection with Class-imbalance Classification","authors":"Wanchaloem Nadda, W. Boonchieng, E. Boonchieng","doi":"10.1109/HI-POCT45284.2019.8962825","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962825","url":null,"abstract":"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.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132210035","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}
Pub Date : 2019-11-01DOI: 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.
{"title":"A Motion Free Image Based TRF Reader for Quantitative Immunoassay","authors":"S. Karthik, M. Shah, Satheesh Natarajan, Mahesh Shetty, J. Joseph","doi":"10.1109/HI-POCT45284.2019.8962655","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962655","url":null,"abstract":"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.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115396110","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}
Pub Date : 2019-11-01DOI: 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.
{"title":"A Novel Nanoscale Electrode for Biosensing","authors":"Alperen Guver, P. Milas, M. Guy, Mustafa T. Sigindere, M. Yigit, Birol Ozturk","doi":"10.1109/HI-POCT45284.2019.8962645","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962645","url":null,"abstract":"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.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113955823","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}
Pub Date : 2019-11-01DOI: 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.
{"title":"Acoustic Assessment of Treatment Response for Children with Acute Asthma Exacerbation","authors":"Adam Rao, Grant Pemberton, Sean Rubin, E. Wu, Aaron E. Kornblith","doi":"10.1109/HI-POCT45284.2019.8962830","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962830","url":null,"abstract":"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.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124449674","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}
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