Mario Banuelos, Lasith Adhikari, R. Almanza, Andrew Fujikawa, Jonathan Sahagun, Katharine Sanderson, M. Spence, Suzanne S. Sindi, Roummel F. Marcia
{"title":"Nonconvex regularization for sparse genomic variant signal detection","authors":"Mario Banuelos, Lasith Adhikari, R. Almanza, Andrew Fujikawa, Jonathan Sahagun, Katharine Sanderson, M. Spence, Suzanne S. Sindi, Roummel F. Marcia","doi":"10.1109/MeMeA.2017.7985889","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985889","url":null,"abstract":"Recent research suggests an overwhelming proportion of humans have genomic structural variants (SVs): rearrangements of regions in the genome such as inversions, insertions, deletions and duplications. The standard approach to detecting SVs in an unknown genome involves sequencing paired-reads from the genome in question, mapping them to a reference genome, and analyzing the resulting configuration of fragments for evidence of rearrangements. Because SVs occur relatively infrequently in the human genome, and erroneous read-mappings may suggest the presence of an SV, approaches to SV detection typically suffer from high false-positive rates. Our approach aims to more accurately distinguish true from false SVs in two ways: First, we solve a constrained optimization equation consisting of a negative Poisson log-likelihood objective function with an additive penalty term that promotes sparsity. Second, we analyze multiple related individuals simultaneously and enforce familial constraints. That is, we require any SVs predicted in children to be present in one of their parents. Our problem formulation decreases the false positive rate despite a large amount of error from both DNA sequencing and mapping. By incorporating additional information, we improve our model formulation and increase the accuracy of SV prediction methods.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130510869","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}
John D. Ciubuc, Chao Qiu, K. Bennet, Matthew Alonzo, W. Durrer, F. Manciu
{"title":"Raman computational and experimental studies of dopamine molecules on silver nanocolloids","authors":"John D. Ciubuc, Chao Qiu, K. Bennet, Matthew Alonzo, W. Durrer, F. Manciu","doi":"10.1109/MeMeA.2017.7985867","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985867","url":null,"abstract":"Combined theoretical and experimental analysis of dopamine is presented in this work to better understand phenomena related to this neurotransmitter's detection and monitoring at very low concentrations specific to physiological levels. Surface-enhanced Raman spectroscopy (SERS) on silver nanoparticles was employed for recording dopamine concentrations as low as 10−11 molar. Quantum chemical density functional calculations were carried out using Gaussian-09 analytical suite software. Relatively good agreement between the simulated and experimentally determined results indicates the presence of all dopamine molecular forms, such as neutral DA0, ionic DA− and DA+, and of dopaminequinone as well. Disappearance of the strongest bands of dopamine at 750 cm−1 and 795 cm−1, which suggests its adsorption onto the metallic surface, is consistent with the appearance of the latter molecular configuration. Thus, through coordinated experiment and theory, valuable insights into changes observed in the vibrational signatures of this important neurotransmitter can be analyzed and comprehended.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125777037","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}
S. RenganathanB., Preejith Sreeletha Premkumar, Sridhar Nagaiyan, J. Joseph, M. Sivaprakasam
{"title":"System design to prevent Ventilator Associated Pneumonia","authors":"S. RenganathanB., Preejith Sreeletha Premkumar, Sridhar Nagaiyan, J. Joseph, M. Sivaprakasam","doi":"10.1109/MeMeA.2017.7985869","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985869","url":null,"abstract":"Ventilator Associated Pneumonia (VAP) is a major problem in hospitals and is the leading cause of deaths among all hospital-acquired infections. Critically ill subjects who are in the intensive care unit (ICU) and under mechanical ventilator support are more prone to VAP. Traditionally, VAP bundle is used in hospitals for prevention of VAP. VAP bundle consists of five protocols which must be observed by the caregiver at regular intervals of time. One of the critical protocol steps is to always maintain the patient's head up angle at 30–45 degrees. This is not always strictly followed by caregivers due to lack of continuous monitoring and alert mechanisms. Hence a novel method is proposed which includes a wearable sensor which is attached to the patient's body, continuously monitoring the patient's head up angle and a tablet-based system that reminds the caregiver as and when required to help comply with the VAP bundle protocols. Preliminary studies under a controlled setting revealed that the system can continuously monitor and accurately detect the patient's head up angle and remind the caregiver when required.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130982690","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}
{"title":"Design of an artificial neural network and feature extraction to identify arrhythmias from ECG","authors":"V. C. C. Roza, A. M. Almeida, O. Postolache","doi":"10.1109/MeMeA.2017.7985908","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985908","url":null,"abstract":"This paper presents a design of an artificial neural network (ANN) and feature extraction methods to identify two types of arrhythmias in datasets obtained through electrocardiography (ECG) signals, namely arrhythmia dataset (AD) and supraventricular arrhythmia dataset (SAD). No special ANN toolkit was used; instead, each neuron and necessary calculus were modeled and individually programmed. Thus, four temporal-based features are used: heart rate (HR), R-peaks root mean square (R-RMS), RR-peaks variance (RR-VAR), and QSR-complex standard deviation (QSR-SD). The network architecture presents four neurons in the input layer, eight in hidden layer and an output layer with two neurons. The proposed classification method uses the MIT-BIH Dataset (Massachusetts Institute of Technology-Beth Israel Hospital) for training, validation and execution or test phases. Preliminary results show the high efficiency of the proposed ANN design and its classification method, reaching accuracies between 98.76% and 98.91%, when in the identification of NSRD and arrhythmic ECG; and accuracies of 86.37% (AD) and 76.35% (SAD), when analyzing only classifications between both arrhythmias.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134146515","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}
{"title":"Design of an Oxistimulator system for use in clinical trials","authors":"J. Kuhlmann, Steven Deick","doi":"10.1109/MeMeA.2017.7985871","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985871","url":null,"abstract":"Obstructive sleep apnea, especially when undiagnosed, can be a critical issue for surgical patients in the days following surgery due to lingering effects of anesthesia that may depress their auto-response to recover from episodes of apnea. The authors worked in collaboration with medical staff to develop a custom system in support of a clinical research study. The Oxistimulator system provides a low-level electrical stimulation to a patient in response to oxygen saturation levels dropping below a defined threshold for patient safety, and tracks data required to analyze the system's effectiveness. A successful outcome of the study could help justify a new medical device that would improve patient safety during post-anesthesia recovery.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132692066","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}
M. Parvis, S. Corbellini, L. Lombardo, L. Iannucci, S. Grassini, E. Angelini
{"title":"Inertial measurement system for swimming rehabilitation","authors":"M. Parvis, S. Corbellini, L. Lombardo, L. Iannucci, S. Grassini, E. Angelini","doi":"10.1109/MeMeA.2017.7985903","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985903","url":null,"abstract":"The occurrence of light spinal diseases due to the low physical activity of daily life is continuously increasing. Recovering form these diseases requires specific and directed physical activity and can conveniently performed in swimming pools where the apparent weight reduction due to the water helps letting patients perform the relief movements. Unfortunately a way for easily assessing the correctness of the patient's movement is still missing and in most cases everything relies on the capabilities of the trainers, which must be continuously present. This paper describes an attempt to arrange a simple system suitable for a quasi on-line self assessing to the movement correctness. The proposed system is based on two inertial assemblies to be worn on the wrists and capable of sending data to a receiver installed at pool border. Data received from these small assemblies are processed to show the patients the symmetry of their movements, which is connected to the movement efficiency. The inertial assemblies are arranged by using a commercial miniaturized Inertial Measurement Unit, a Teensyduino board, and a μPanel WiFi transmitter which is able to send the data to the received during the swimming. The receiver process the data in-line so that, when the patients stop swimming to take a rest, they can be displayed to the patients as a self-assess of the just performed activity.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"66 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114049916","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}
Q. Viet, Bao Hung Tran, Bang Nguyen Phuong, Lung Vu Duc
{"title":"A combination of Gaussian Mixture Model and Support Vector Machine for speaker verification","authors":"Q. Viet, Bao Hung Tran, Bang Nguyen Phuong, Lung Vu Duc","doi":"10.1109/MeMeA.2017.7985915","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985915","url":null,"abstract":"In this paper, we proposed a speaker verification system to determine whether an input speech comes from outside the set of known speaker robustly. The proposed system consists of preprocessing, feature extraction, distortion measure calculation, and verification stages. The proposed speaker verification firstly catches and segments speech in the preprocessing stage. The segmented speech is extracted to MFCC feature, known as the most popular feature in speech processing, and a Gaussian Mixture Model (GMM) is constructed to model the extracted feature vectors. Next, a high dimensional distance between it and GMM, which is model of pre-trained speech of claimed identity, is calculated as a multi-scoring vector. Finally, a support vector machine decides whether the distance is acceptable or not, by other words, the input speech is verified or rejected. Experiment results show that the proposed system can recognize the claimed speaker with an accuracy of 96%, while the error rate is 6.6% acceptable.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128848451","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}
{"title":"Fuzzy logic supported 3D modeling based orthodontics","authors":"A. Várkonyi-Kóczy, B. Tusor, E. Segatto","doi":"10.1109/MeMeA.2017.7985868","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985868","url":null,"abstract":"Today, the spreading of machine intelligence and the increased computational facilities have opened new possibilities in orthodontics. By combining the methods of computer vision, 3D imaging, and new modeling techniques, new, increased health prevention, aesthetic, and comfortability expectations can be fulfilled together with the requirements of sustainable health promotion and restoration of functional integrity with a decreased burden of harmful radiation load and invasive interventions. In this paper, a new 3D model based designing technique is introduced by which the 3D movements of the teeth (including the roots) can be designed, followed, and kept under control during the whole rehabilitation process. The follow-up of the implementation of the orthodontic treatment planning is important not only when determining the location of the tooth crown but because it enables to carry out the radiation-free monitoring of the planned treatments precisely mapped based on the anatomic aptitudes. This results in the continuous determination of the positions of roots and of their correlation with each other which is an essential condition in regards to the stability of the treatment outcome.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129006408","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}
{"title":"Home automation serving a healthier lifestyle","authors":"Fedwa Laamarti, Abdulmotaleb El Saddik","doi":"10.1109/MeMeA.2017.7985846","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985846","url":null,"abstract":"The increase of obesity and overweight is alarming, and has major human and financial detrimental consequences. The problem of obesity and overweight is caused mainly by an increase in physical inactivity, for which one of the main reasons is the long hours spent every day in front of the TV. The system proposed in this paper targets individuals who are overweight or subjects for whom doctors have prescribed a minimum physical activity. The MPEG-V standard [1] is used in this work in order to control home actuators as a motivation for individuals to transform exercise intention into exercise activity. To evaluate our system, we conducted an experiment with 31 subjects, and the results are promising as they show that our system was successful at motivating subjects to perform physical exercise while watching TV.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122954932","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}
S. Hara, T. Moen, K. Bennet, Kendall H. Lee, Jonathan R. Tomshine
{"title":"Removal and evaluation of non-diamond carbon on boron-doped diamond electrodes","authors":"S. Hara, T. Moen, K. Bennet, Kendall H. Lee, Jonathan R. Tomshine","doi":"10.1109/MeMeA.2017.7985860","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985860","url":null,"abstract":"Boron-doped diamond electrodes possess many qualities that make them promising candidates for chronic in vivo neurochemical sensors. The fabrication process for boron-doped diamond films produces additional forms of non-diamond carbon that can confound electrochemical performance and neurochemical detection. Various removal treatments have been implemented for other applications of boron-doped diamond, but they have not been very well evaluated or compared. In this work, we present the use of electrode double-layer capacitance and quinone surface coverage to evaluate the effectiveness of three different non-diamond carbon removal treatments on boron-doped diamond microelectrodes designed for neurochemical detection. The results indicate that sulfuric acid cycling post-deposition and incorporation of an atomic hydrogen cool-down step into the deposition process reduce the amount of surface non-diamond carbon contaminating boron-doped diamond electrodes.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115226010","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}