Department of Electrical Engineering
Medical Instrumentation, Physiological Signal Processing Algorithms, Remote Monitoring, Autonomic Activity Estimation, Affective Computing, Computer Vision, Machine Learning, Embedded Systems
Physiological Emotion Sensing for Gaming
This is my main project studying techniques for measuring and classifying the emotional state of a video game players from peripheral physiological signals. We have recently developed a video analysis instrument and modified gamepad that incorporates heart rate (PPG/ECG), respiration (IPG), and hand movement (accelerometer) sensors for estimating autonomic activity triggered by emotions during gameplay. This prototype was shown with Texas Instruments at the International Consumer Electronics Show 2014.
Thermal cameras are used to detect seizures in patients at the Stanford Hospital & Clinics Epilepsy Monitoring Unit. Current state-of-the-art seizure detection methods rely on characterizing tonic-clonic motion, or by detecting epileptiform EEG activity. However, not all seizures involve shaking or produce recognizable scalp EEG changes. Thermography can be used to detect temperature change caused by autonomic hyperactivity and the resulting increase in blood flow near exposed skin surfaces.
We demonstrated the use of a ballistocardiograph (BCG) hemodynamic monitoring scale in microgravity, and its utility for space applications by establishing the correlation between ground-based and microgravity measurements. BCG diagnostic methods, such as monitoring cardiac output, stroke volume change, contractility change, central pressures, and arterial stiffening, are useful to detect well-known cardiovascular physiology changes in weightless environments, where astronauts often return to Earth with microgravity-induced deconditioning. I directed this project in it's second year, organizing a week long experiment with 14 participants aboard NASA's reduced gravity aircraft at Ellington Field Air Force Base.
Feature Selection for Hierarchical Classification
A hierarchical classifier is able to distinguish between a large number of confusing classes by exploiting the fact that similar classes according to one feature set may be dissimilar according to another, allowing normally confused classes to be grouped and handled separately. However, determining these macro-classes of similarity is not straightforward when the selected feature set has yet to be determined. A new greedy forward selection algorithm is presented to simultaneously determine good macro-classes and the features that best distinguish them in a K-NN hierarchical classifier. The algorithm was tested on the CMU-MMAC dataset, as well as new aerobic action dataset that we collected from a 9-axis smartphone inertial sensor for this project.
Automated Medication Adherence Monitoring
An inexpensive home-based medication dispensing and monitoring device was developed to enable outpatients to independently manage a complex medication regimen. In the system, an RFID tag containing a small amount of rewritable memory is fixed to each medication container and updated with the precise weight of the container before and after dispensing medication. An Arduino-based embedded system dynamically builds an efficient dosage schedule and can notify the patient or caregiver via cell phone text message if the patient is late or if there is a dosage noncompliance or inconsistency.
Ph.D., Electrical Engineering, Stanford University, (2016).
M.S., Electrical Engineering, Stanford University, 2013.
B.S., Computer Engineering, University of Central Florida, 2011.
Peer-Reviewed Journal Articles
C. McCall, B. Maynes, C. Zou, N. Zhang, "An Automatic Medication Self-management and Monitoring System for Independently Living Patients," Medical Engineering & Physics 35:4, April 2013.
Peer-Reviewed Conference Proceedings
C. McCall, Zachary Stuart, Richard M. Wiard, Omer T. Inan, Laurent Giovangrandi, Charles Marsh Cuttino, Gregory T.A. Kovacs "Standing Ballistocardiography Measurements in Microgravity," Proc. of IEEE Engineering in Medicine and Biology Conference, Chicaco, IL, 2014.
C. McCall, K. Reddy, M. Shah "Macro-class Selection for Hierarchical K-NN Classification of Inertial Sensor Data,"Proc. of Pervasive and Embedded Computing and Communication Systems Conference, Rome, Italy, 2012.
C. McCall, B. Maynes, C. Zou, N. Zhang, "RMAIS: RFID-based Medication Adherence Intelligence System," Proc. of IEEE Engineering in Medicine and Biology Conference, Buenos Aires, Argentina, 2010.
C. McCall, Z. Stuart, R. M. Wiard, O. T. Inan, L. Giovangrandi, C. M. Cuttino, G. T. A. Kovacs., "Ballistocardiography for Monitoring Cardiovascular Deconditioning in Long-Duration Missions," NASA Innovative Advanced Concepts (NIAC) Symposium, Stanford, CA, 2014.
C. McCall, B. Maynes, C. Zou, N. Zhang, "A Prototype Device that Implements RFID and Remote Monitoring Technology to Track Medications for Elderly Healthcare Patients," UCF Showcase for Undergraduate Research Excellence, Orlando, FL, 2010.
C. McCall, "An Automatic Medication Management System for Independently Living Healthcare Patients," Undergraduate Honors in the Major Thesis, UCF Department of Electrical Engineering and Computer Science, Orlando, FL, 2010.
Distinctions and Awards
Honorable Mention Poster Award, UCF Showcase for Undergraduate Research. Awarded for poster "A Prototype Device that Implements RFID and Remote Monitoring Technology to Track Medications for Elderly Healthcare Patients" (3 awards of 33 applicants). 2010.
Invention Competition Winner, UCF Inventing Entrepreneurs Innovation Competition. Awarded for best product prototype (first place of ~20 applicants). 2010.
Grants and Scholarships
Research Assistantship Grant (Annual), Texas Instruments. Awarded for research conducted with Dr. Gregory Kovacs at Stanford. 2012-2014
Graduate Research Fellowship (3 years), National Science Foundation. Awarded for research conducted with Dr. Gregory Kovacs at Stanford (2,000 awards of 12,000 applicants). 2011.
Research Experiences for Undergraduates (REU) Grant, National Science Foundation. Awarded for undergraduate research conducted with Dr. Mubarak Shah at UCF. 2011.
"Inventing Entrepreneurship" Grant, National Collegiate Inventors and Innovators Alliance. Awarded for invention of medication monitoring device. 2010.
Honors College Scholarship, UCF Burnett Honors College. Awarded for best undergraduate research project in UCF Computer Engineering department. 2009.
Research Experiences for Undergraduates (REU) Grant, National Science Foundation. Awarded for undergraduate research conducted with Dr. Cliff Zou at UCF. 2009.
- Institute of Electrical and Electronics Engineers (IEEE)
- IEEE Engineering in Medicine & Biology Society (EMBS)
- IEEE Journal of Biomedical and Health Informatics (JBHI) (Formally Transactions on Information Technology in Biomedicine), 2014.
- IEEE Global Conference on Signal and Information Processing (GlobalSIP), Austin, TX, 2013.
Undergraduate Mentor, Stanford Transducers Lab, Stanford, California. Mentored 4 Stanford undergraduate students working on electronics and signal processing projects for 12 months. 2012.
Conference Session Chair Invitation (Embedded Systems Design). International Conference on Pervasive and Embedded Computing and Communications Systems Conference (PECCS), Rome, Italy, 2012.
Research Assistant, Stanford Transducers Lab, Stanford, CA.
Teaching Assistant (Intro to Electronics), Stanford Department of Electrical Engineering, Stanford, CA.
Research Assistant, UCF Computer Vision Lab, Orlando, FL.
Teaching Assistant (Computer Networking), UCF College of Engineering and Computer Science, Orlando, FL.
Tutor (Engineering and Computer Science), UCF College of Engineering and Computer Science, Orlando, FL.
Research Assistant, UCF Data Systems Group, Orlando, FL.
Student Organization Founder/President, UCF Student Chapter of International Council on Systems Engineering, Orlando, FL.
Internship (Web Development), Florida Department of Transportation, Ft. Lauderdale, FL.
Stanford, CA 94305
Email: cmccall "at" stanford "dot" edu