Health Monitoring

Program Title: Health Monitoring

Program Description: The Health Monitoring program at the University of California is an innovative and comprehensive course designed to equip students with the skills and knowledge necessary to assess, interpret, and respond to various health indicators in diverse populations. This program delves into the fundamental principles of health surveillance, data collection, and analysis, emphasizing the importance of continuous health monitoring to improve public health outcomes. Students will explore a wide array of topics, including epidemiology, biostatistics, data management, and the use of advanced technology in health tracking. The curriculum combines theoretical instruction with practical training, ensuring graduates are proficient in designing and implementing health monitoring systems, interpreting health data, and communicating findings effectively to stakeholders. The coursework also covers ethical issues related to health data privacy and security, fostering responsible practices among future health professionals. Through interdisciplinary coursework and collaborative projects, students will gain hands-on experience with current health monitoring tools and platforms, preparing them for careers in public health agencies, research institutions, healthcare organizations, and policy development. The program emphasizes the importance of proactive health surveillance in identifying emerging health threats, managing chronic diseases, and promoting wellness initiatives. Graduates will be well-equipped to contribute to the development of evidence-based health policies and programs, utilizing innovative approaches to improve population health on local, national, and global scales. With expert faculty renowned in epidemiology, data science, and health technology, the Health Monitoring program offers a dynamic learning environment that fosters critical thinking, problem-solving, and leadership skills vital for advancing public health initiatives. This program is ideal for individuals passionate about advancing health systems, leveraging technology for health data analysis, and making a meaningful impact on community well-being.

Many courses currently offered within the Jacobs School of Engineering may be grouped into numerous focus sequences within each technology area, as shown in the following list:

A. Sensing Technology Area

1. Sensing Methodologies Focus Sequence

SE 252 Experimental Mechanics and NDE
MAE 261 Cardiovascular Fluid Mechanics (not offered 2011-12) 
MAE 268 Frontier Micro-Electro-Mechanical Systems(MEMS) Materials and Devices (not offered 2011-12)

2. Data Acquisition Systems Focus Sequence

ECE 257B Principles of Wireless Networks
ECE 258A,B Digital Communications
ECE 259C Advanced Coding and Modulation for Digital Communications  
MAE 261 Cardiovascular Fluid Mechanics (offered 2012-13) 
CSE 237A Introduction to Embedded Computing
CSE 237B Software for Embedded Computing
CSE 237C Validation/Testing of Embedded Systems
CSE 237D Design Automation and Prototyping for Embedded Systems

3. Controls Focus Sequence

MAE 280A Linear Systems Theory
MAE 280B Linear Control Design
MAE 282 Adaptive Control
MAE 284 Robust and Multi-Variable Control
MAE 285 Optimal Control and Estimation (to be split into MAE 285A and 285B in Fall 2005)

B. Data Interrogation Technology Area

1. Signal Processing Focus Sequence

ECE 161A Introduction to Digital Signal Processing 
ECE 251AN/SIO 207B Digital Signal Processing I
ECE 251B/SIO 207C Digital Signal Processing II 
ECE 251C Filter Banks and Wavelets 
ECE 251D or SIO 207D Array Processing 
ECE 253A Fundamentals of Digital Image Processing
ECE 253B Digital Image Analysis
ECE 254 Detection Theory
ECE 255A Information Theory

2. System Identification Focus Sequence

MAE 283A Parameter Identification: Theory and Methods
MAE 283B Approximate Identification and Control
ECE 256A,B Time Series Analysis and Applications
ECE 275A Parameter Estimation I
ECE 275B Parameter Estimation II

3. Pattern Recognition Focus Sequence

CSE 250A Artificial Intelligence: Search and Reasoning
CSE 250B Artificial Intelligence: Learning
CSE 254 Statistical Learning
ECE 270A,B,C Neurocomputing

4. Statistical/Probabilistic Methods Focus Sequence

MTH 281A, B,C Mathematical Statistics
CSE 254 Statistical Learning
SE 206 Random Vibrations
SE 224 Structural Reliability and Risk Analysis

C. Predictive Modeling Technology Area

1. Structural Analysis Focus Sequence

SE 201A Advanced Structural Analysis 
SE 202 Structural Stability
SE 203 Structural Dynamics
SE 204 Advanced Structural Dynamics -- added
SE 224 Structural Reliability and Risk Analysis

2. Finite Element Focus Sequence

SE 276A Finite Element Methods in Solid Mechanics I 
SE 276B Finite Element Methods in Solid Mechanics II 
SE 276C Advances in Materials Computations 
SE 274 Nonlinear Finite Elemental Methods

3. Solid Mechanics Focus Sequence

SE 235 Wave Propagation in Elastic Media
SE 252 Experimental Mechanics and NDE
SE 271 Solid Mechanics for Structural and Aerospace Engineering
SE 272 Theory of Elasticity
SE 273/MAE 231C Anelasticity

4. Material Behavior/Modeling

MAE 233B Micromechanics
SE 276C/MAE 232C Finite Element Methods in Solid Mechanics III
MAE 273A Dynamic Behavior of Materials
  

5. Advanced Structural Behavior

SE 204 Advanced Structural Dynamics
SE 205 Nonlinear Mechanical Vibrations 
SE 206 Random Vibrations
SE 224 Structural Reliability and Risk Analysis
SE 252 Experimental Mechanics and NDE
SE 265 Structural Health Monitoring Principles

6. Earthquake Engineering Focus Sequence

SE 203 Structural Dynamics
SE 206 Random Vibrations
SE 221 Earthquake Engineering
SE 222 Geotechnical Earthquake Engineering
SE 223 Advanced Seismic Design of Structures

7. Advanced Composites Focus Sequence

SE 253A Mechanics of Laminated Composite Structures I 
SE 254 FRP Rehabilitation of Civil Structures

Two degree plans in SHMP&VS will be offered: MS Thesis Plan and MS Comprehensive Examination Plan. Students in both plans must complete forty-eight units of credit for graduation. For both plans, students must complete thirty-six units of coursework consisting of one focus sequence from each of the three Technology Areas A, B and C listed above. Any three of the courses listed under a specific topic area constitutes a focus sequence. Courses must be chosen in consultation with the student’s adviser. The remaining twelve units must be completed as graduate research SE 299.

For the M.S. SHMP&VS Comprehensive Examination Plan, the 12-unit graduate research SE 299 must be conducted as a mentored research project. This project is intended to provide a mentored practicum whereby students integrate knowledge learned from their technology areas into comprehensively solving a problem from structural health monitoring/prognosis or model validation and uncertainty quantification, at their discretion. This project will emphasize professional practice, with both oral and written communication of technical data, and will include a strong design component. The project will be presented to a committee of two faculty members in Structural Engineering and one from another department within the Jacobs School of Engineering or an adjunct faculty member in an appropriate area of focus.

For the M.S. SHMP&VS Thesis Plan, the 12-unit graduate research SE 299 culminates with the preparation of a research thesis. The thesis must be successfully defended in an oral examination and public presentation conducted by a committee composed of three faculty members. The committee will be comprised of two faculty members in Structural Engineering and one from another department within the Jacobs School of Engineering or an adjunct faculty member in an appropriate area of focus. A complete copy of the student’s thesis must be submitted to each member of the MS thesis committee at least two weeks prior to the defense.

Because of the inherent multidisciplinary nature of the M.S. SHMP&VS degree, conduction of research within SE 299 can be performed at outside locations (industry or government facilities). In this case a scientist on location, with an adjunct faculty appointment at UCSD, will be part of the student’s committee. The degree is also available to students working in industry or government laboratories that cannot be released from their duties for periods of more than 1-2 quarters. In these cases, UCSD courses taken via distance learning may be used to satisfy the course requirements. A scientist on location, with an adjunct faculty appointment at UCSD, must be part of the student’s committee.

Each quarter they are registered, all students in the M.S. SHMP&VS Comprehensive Examination Plan and all first-year students in the M.S. SHMP&VS Thesis Plan are required to enroll in the seminar course SE 290 (Invited Speakers). Each quarter they are registered, all second- and third-year students in the M.S. SHMP&VS Thesis Plan are required to enroll in the seminar course SE 291 (Graduate Student Presentations), although their attendance to the seminar course SE 290 (Invited Speakers) is strongly encouraged. For those students working in industry or government laboratories that cannot be released from their duties, successful completion of SE 290 or SE 291 will be obtained by attending an equivalent number of seminars at the off-site location that must be approved by a scientist on location with an adjunct faculty appointment at UCSD.

Requirements

• Please note that successful applicants must hold a bachelor's degree or the equivalent from an accredited institution in the United States or from a recognized university-level academic institution abroad and at least a B average (3.0 GPA) or its equivalent by the time they enroll.
• A test of English language proficiency is required for international applicants whose native language is not English and who have not studied full-time for one uninterrupted academic year at a university-level institution in which English is the language of instruction and in a country where English is a dominant language.The university-wide minimum TOEFL score required for consideration for graduate admission is 550 for the paper based test (PBT), and 80 for the internet based test (iBT). The university-wide minimum IELTS Academic Training exam score required for consideration for graduate admission is Band Score 7.
• GRE General Test is required.
• Minimum of 3 recommendations required.
• Statement of Purpose 200 word limit.
• Resume/CV

Scholarships

• Global Education
• Different Fellowships and Traineeships

The University of California offers a comprehensive program in Health Monitoring that is designed to prepare students with the skills and knowledge necessary to assess, analyze, and improve health outcomes across various populations. This program emphasizes the integration of technological, biological, and social sciences to enable effective monitoring of health parameters and the development of interventions to promote wellness and prevent disease. Students enrolled in this program will engage in a multidisciplinary curriculum that covers topics such as biostatistics, epidemiology, health informatics, biomedical engineering, and public health policy. The program aims to equip graduates with the ability to utilize advanced data collection and analysis tools, including wearable health devices, remote sensing technologies, and electronic health records, to track and interpret health indicators. Practical training components are incorporated through laboratory work, field studies, and internships with healthcare organizations, research institutes, and technology companies. Throughout the course of study, students will also explore ethical considerations related to health data privacy and security, ensuring responsible management of sensitive information. Graduates of the program are prepared for careers in health technology development, public health surveillance, clinical research, or further specialization through advanced degrees. The program aligns with California’s leadership in health innovation and technology, providing students with opportunities to collaborate on cutting-edge projects that address current and emerging health challenges. Admission requirements typically include a strong academic record in science and mathematics, relevant extracurricular experience, and a demonstrated interest in health sciences. The program’s faculty comprises renowned experts in epidemiology, biomedical engineering, health policy, and data science, fostering an environment of research and innovation. Graduates can expect to contribute significantly to improving health monitoring systems, advancing personalized medicine, and supporting evidence-based decision making in healthcare. Overall, the University of California’s Health Monitoring program offers a rigorous, forward-looking education that combines theoretical knowledge with practical skills, designed to meet the demands of a rapidly evolving healthcare landscape.