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- Creators: Arizona State University
Description
In recent years, machine learning and data mining technologies have received growing attention in several areas such as recommendation systems, natural language processing, speech and handwriting recognition, image processing and biomedical domain. Many of these applications which deal with physiological and biomedical data require person specific or person adaptive systems. The greatest challenge in developing such systems is the subject-dependent data variations or subject-based variability in physiological and biomedical data, which leads to difference in data distributions making the task of modeling these data, using traditional machine learning algorithms, complex and challenging. As a result, despite the wide application of machine learning, efficient deployment of its principles to model real-world data is still a challenge. This dissertation addresses the problem of subject based variability in physiological and biomedical data and proposes person adaptive prediction models based on novel transfer and active learning algorithms, an emerging field in machine learning. One of the significant contributions of this dissertation is a person adaptive method, for early detection of muscle fatigue using Surface Electromyogram signals, based on a new multi-source transfer learning algorithm. This dissertation also proposes a subject-independent algorithm for grading the progression of muscle fatigue from 0 to 1 level in a test subject, during isometric or dynamic contractions, at real-time. Besides subject based variability, biomedical image data also varies due to variations in their imaging techniques, leading to distribution differences between the image databases. Hence a classifier learned on one database may perform poorly on the other database. Another significant contribution of this dissertation has been the design and development of an efficient biomedical image data annotation framework, based on a novel combination of transfer learning and a new batch-mode active learning method, capable of addressing the distribution differences across databases. The methodologies developed in this dissertation are relevant and applicable to a large set of computing problems where there is a high variation of data between subjects or sources, such as face detection, pose detection and speech recognition. From a broader perspective, these frameworks can be viewed as a first step towards design of automated adaptive systems for real world data.
ContributorsChattopadhyay, Rita (Author) / Panchanathan, Sethuraman (Thesis advisor) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
Description
This work involved the analysis of a public health system, and the design, development and deployment of enterprise informatics architecture, and sustainable community methods to address problems with the current public health system. Specifically, assessment of the Nationally Notifiable Disease Surveillance System (NNDSS) was instrumental in forming the design of the current implementation at the Southern Nevada Health District (SNHD). The result of the system deployment at SNHD was considered as a basis for projecting the practical application and benefits of an enterprise architecture. This approach has resulted in a sustainable platform to enhance the practice of public health by improving the quality and timeliness of data, effectiveness of an investigation, and reporting across the continuum.
ContributorsKriseman, Jeffrey Michael (Author) / Dinu, Valentin (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
Engineers have a strong influence on everyday lives, ranging from electronics and trains to chemicals and organs [1]. However, in the United States, there is a large knowledge gap in the roles of engineers, especially in K-12 students [2] [3]. The National Academy of Engineering (NAE) recognizes the current problems in engineering, such as the dominance of white males in the field and the amount of education needed to become a successful engineer [4]. Therefore, the NAE encourages that the current engineering community begin to expose the younger generations to the real foundation of engineering: problem-solving [4]. The objective of this thesis is to minimize the knowledge gap by assessing the current perception of engineering amongst middle school and high school students and improving it through engaging and interactive presentations and activities that build upon the students’ problem-solving abilities.
The project was aimed towards middle school and high school students, as this is the estimated level where they learn biology and chemistry—key subject material in biomedical engineering. The high school students were given presentations and activities related to biomedical engineering. Additionally, within classrooms, posters were presented to middle school students. The content of the posters were students of the biomedical engineering program at ASU, coming from different ethnic backgrounds to try and evoke within the middle school students a sense of their own identity as a biomedical engineer. To evaluate the impact these materials had on the students, a survey was distributed before the students’ exposure to the materials and after that assesses the students’ understanding of engineering at two different time points. A statistical analysis was conducted with Microsoft Excel to assess the influence of the activity and/or presentation on the students’ understanding of engineering.
The project was aimed towards middle school and high school students, as this is the estimated level where they learn biology and chemistry—key subject material in biomedical engineering. The high school students were given presentations and activities related to biomedical engineering. Additionally, within classrooms, posters were presented to middle school students. The content of the posters were students of the biomedical engineering program at ASU, coming from different ethnic backgrounds to try and evoke within the middle school students a sense of their own identity as a biomedical engineer. To evaluate the impact these materials had on the students, a survey was distributed before the students’ exposure to the materials and after that assesses the students’ understanding of engineering at two different time points. A statistical analysis was conducted with Microsoft Excel to assess the influence of the activity and/or presentation on the students’ understanding of engineering.
ContributorsLlave, Alison Rose (Author) / Ganesh, Tirupalavanam (Thesis director) / Parker, Hope (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
This thesis dissertation presents design of portable low power Electrochemical Impedance Spectroscopy (EIS) system which can be used for biomedical applications such as tear diagnosis, blood diagnosis, or any other body-fluid diagnosis. Two design methodologies are explained in this dissertation (a) a discrete component-based portable low-power EIS system and (b) an integrated CMOS-based portable low-power EIS system. Both EIS systems were tested in a laboratory environment and the characterization results are compared. The advantages and disadvantages of the integrated EIS system relative to the discrete component-based EIS system are presented including experimental data. The specifications of both EIS systems are compared with commercially available non-portable EIS workstations. These designed EIS systems are handheld and very low-cost relative to the currently available commercial EIS workstations.
ContributorsGhorband, Vishal (Author) / Blain Christen, Jennifer (Thesis advisor) / Song, Hongjiang (Committee member) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2016
Description
With the recent rise in opioid overdose and death1<br/><br/>, chronic opioid therapy (COT) programs using<br/>Center of Disease Control (CDC) guidelines have been implemented across the United States8<br/>.<br/>Primary care clinicians at Mayo Clinic initiated a COT program in September of 2017, during the<br/>use of Cerner Electronic Health Record (EHR) system. Study metrics included provider<br/>satisfaction and perceptions regarding opioid prescription. Mayo Clinic transitioned its EHR<br/>system from Cerner to Epic in October 2018. This study aims to understand if provider perceptions<br/>about COT changed after the EHR transition and the reasons underlying those perceptions.
ContributorsPonnapalli, Sravya (Author) / Murcko, Anita (Thesis director) / Wallace, Mark (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05