Current healthcare systems face numerous challenges such as large cost, lack of preventive care, massive increases in chronic disease conditions and age-related illnesses, widespread obesity, poor adherence to medical regimens, and shortage of healthcare professionals. Smart Health solutions utilize new sensing technologies, smart mobile devices, wireless networks, and big data analytics to provide significantly improved care to anyone, at anytime, and anywhere, while increasing the coverage, quality, and efficiency of healthcare. This course studies how mobile, wireless, sensing, cloud, and big data technologies can be used to implement this vision of future healthcare. Class discussions will touch topics such as prevention techniques, continuous health monitoring, wireless and mobile technologies and standards for medical devices, personalized healthcare solutions, body area networks, implantable devices, mHealth applications, intelligent emergency management systems, pervasive healthcare data access, personal and electronic medical record systems, mobile telemedicine, context-awareness, and case studies of pervasive solutions for various health conditions and challenges. There is no textbook for this course; instead, the course will be based on recent publications in the areas of healthcare and wellness. Student will work on a semester-long development project in the area of smart health and also investigate and present a specific healthcare concern or technology via a brief oral and written report.

Upon successful completion of this course, students will be able to:

  1. Understand the fundamentals of the basic building blocks of smart health solutions, such as sensors, mobile devices, edge and cloud computing technologies, data fusion, electronic health record systems, and medical analytics.

  2. Establish a connection between the needs of specific medical and wellness challenges and the opportunities provided by new technologies.

  3. Discuss current and future opportunities and challenges in smart health, including growing concerns in the areas of privacy, security, and ethics.

  4. Identify specific healthcare challenges and opportunities and effectively present their insights to others.

  5. Develop solutions to specific healthcare challenges, covering at least one of the following areas: sensing, fusion, biomarker development, intervention, diagnostics, and healthcare analytics.

Class Information

Lecture Time
Mondays/Wednesdays/Fridays 9.25am-10.15am
Note that several lecture slots will be "independent project time", where we will not meet in the classroom, but either the TA or instructor will be available for questions. Please play close attention to the schedule below for actual lecture times.
O'Shaughnessy Hall 116


Christian Poellabauer (
Teaching Assistant
Afzal Hossain (
Office Hours
- Time: Tue 9-10am, Wed 12-1pm, and by appointment
- Location: 323B Cushing Hall
Teaching Assistant:
- Time: Mon 2-3pm, Fri 1-2pm, during "LAB" times in schedule, and by appointment
- Location: 212 Cushing Hall
Final Project Report Due
Unit Date Topics Assignments
Introduction and Background January 15th Introduction, Syllabus, Administrative Items
January 17th Healthcare Fundamentals and Challenges
Smart Health Basics January 20th Definitions and Terminology
The P4 Health Spectrum (Sagner et al., 2017)
January 22nd Smart-X Concepts
Tracking the Evolution of the Internet of Things Concept Across Different Application Domains (Ibarra-Esquer et al., 2017)
January 24th Project Discussion and Case Studies
Systems and Devices January 27th Mobile Computing and mHealth
The Case for mHealth in Developing Countries (Mechael 2009)
January 29th Wireless Networks I
January 31st Wireless Networks II
Project Proposal Due
Systems and Devices February 3rd Wireless Sensor Networks
February 5th Body Area Networks
Wireless Body Area Networks: Challenges, Trends and Emerging Technologies (Antonescu et al. 2013)
February 7th Mobile Cloud Computing
Sensing February 10th Sensor Basics
February 12th Smartphones/Wearables/Implantables Activity Recognition with Smartphone Sensors (Su et al. 2014)
February 14th LAB
Sensing February 17th Context Awareness
February 19th LAB
February 21st Medical Sensors
Sensing February 24th Crowdsensing
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions and Opportunities (Capponi et al., 2019)
February 26th Data Collections, Human Subjects
February 28th Sensor Data Fusion
Processing March 2nd Data Analysis
Receiver-Operating Characteristic Analysis for Evaluating Diagnostic Tests and Predictive Models (Zou et al., 2007)
March 4th Digital Biomarkers Emergence of Digital Biomarkers to Predict and Modify Treatment Efficacy: Machine Learning Study (Guthrie et al., 2019)
March 6th LAB Mid-Semester Progress Report Due
Interventions March 16th Cancelled due to COVID-19
March 18th Cancelled due to COVID-19
March 20th Cancelled due to COVID-19
Interventions March 23rd Questions and Answers Session (Optional)
Zoom Link
March 25th Digital Biomarkers
Slides with Narration
Zoom Link
March 27th Chronic Conditions
Slides with Narration
Zoom Link
Smartphone Applications for Patients' Health and Fitness (Higgins et al., 2016)
Seminar Topic Proposal Due
Interventions March 30th LAB (no reading assignment/slides)
Zoom Link
April 1st Rehabilitation
Slides with Narration
Zoom Link
Designing Informed Game-Based Rehabilitation Tasks Leveraging Advances in Virtual Reality (Lange et al., 2012)
April 3rd Neurological Conditions
Slides with Narration
Zoom Link
Support for a Clinical Diagnosis of Mild Cognitive Impairment Using Photoplethysmography and Gait Sensors (Gwak et al., 2018)
Ecosystem April 6th Psychological Conditions
Slides with Narration
Zoom Link
MoodScope: Building a Mood Sensor from Smartphone Usage Patterns (LiKamWa et al., 2013)
April 8th Healthy Aging, Smart Homes
Slides with Narration
Zoom Link
A Review of Smart Homes – Past, Present, and Future (Alam et al., 2012)
Written Report Due
Seminar April 15th LAB (no reading assignment/slides)
Zoom Link
Seminar Slides Due
April 17th Student Presentations
Zoom Link
"Incentivized Fitness Apps"
"Technology and COVID-19"
"Telehealth for Psychotherapy"
"Robot Assisted Surgery"
"Concussion Helmet Technology"
Seminar April 20th Student Presentations
Zoom Link
"Medical Imaging"
"Respiratory Monitoring"
"Healthcare Companies"
"Mobile Health and Fitness"
"Camera Sensing"
"Healthcare and Blockchain"
April 22nd Student Presentations
Zoom Link
"EEG and EMG in Prosthetics"
"Smart Thermometers"
"Pandemic Control and Mitigation"
"Apple Watch Cardio Health"
"Telemedicine During COVID-19"
April 24th Student Presentations
Zoom Link
"Sleep Tracking"
"Neonatal Nutrition"
"Virtual Reality"
"Chatbots in Mental Health"
"Brain-Computer Interfaces"
"3D Printing"
"COVID-19 Technologies"
Project April 27th LAB (no reading assignment/slides)
Zoom Link
Alzheimer's Assistant
Understanding Autism
Maternal Health Chatbot
April 29th LAB (no reading assignment/slides)
Zoom Link
Gamified Fitness
Smoked Out


Component Points
Readings Reading assignments. 35%
Homework Written report. 15%
Homework Oral presentation. 15%
Class Project Mid-semester progress report. 15%
Class Project Final project report. 20%
Total 100%

Due Dates

Submission details for all deliverables are TBD. Unless specified otherwise, all readings are due before the class starts on the day it is assigned and all other deliverables are due by midnight of the date indicated in the schedule above.

Reading Assignments

For each reading assignment, a brief summary is due immediately before the lecture where the assignment will be discussed. Submission will be via Sakai and the submitted file should be in PDF format and should have the name of the first author (e.g., Sagner.pdf would be the name of the submission for the first reading assignment). In no more than 250 words, the summary should describe the main takeaways of the publication, e.g., what specific problem is being discussed or what solution is proposed or what is the most important lesson you learnt from the assignment, etc. The main purpose of these assignments is to prepare you for the lecture discussions and to provide you with additional detail beyond what is discussed in class.
Late Policy: Reading reports can be submitted up to 24 hours past the deadline for partial credit (75% for reports up to 6 hours late, 30% for reports up to 24 hours late).

Project Proposal

The project proposal (one proposal per team) should be no more than 3 pages, submitted as PDF file via Sakai and contain the following pieces of information: You should begin with your project immediately after proposal submission. The instructor will provide feedback (e.g., suggestions for changes in project scope, etc.) within a week after submission. Note that it is understood that many details may not be known/decided at time of proposal submission; additional details can then be submitted as part of the mid-semester progress report.

Mid-Semester Progress Report

This report is due by midnight on March 6th; submission is via Sakai (it is sufficient if one team member submits the report), the submitted file must be a PDF document. Submissions that are late by up to 6 hours will automatically lose 25%; and another 25% for each 4-hour window afterwards. This report is the only graded project component in the first half of the semester and essential to providing the instructor with a comprehensive view of your efforts and achievements so far! There are no page limitations, but the report should consist of the following components:

Seminar Topic Proposal

For the seminar report/presentation, choose a topic that you would like to explore in more depth, e.g., how technology is being used to address a specific healthcare concern. This part of the course is to be done individually. The proposal is submitted as PDF file via Sakai and is a short document that provides a title of your investigation, your name, and one paragraph (about 1/2 of a page) describing some details about your investigation.

Written Seminar Report

The written seminar report is due April 8th (midnight); submission is via Sakai. For your report, choose 3-5 publications or reports that you will read and describe in your report. Your written report should be a PDF file of up to 5 pages (everything included) where you describe the topic you investigated and your findings from the publications you read. Provide references for the publications and feel free to reuse images/graphs from the publications as you see fit. The audience for your report is the class, i.e., the goal is to provide an overview of a specific healthcare challenge, technology, etc., that goes beyond what has been discussed in the class lectures.

Oral Seminar Report

The oral report is a brief narrated Powerpoint presentation of the topic of your seminar report. You can submit this either as a powerpoint presentation with narration added or as a video file that shows your slides while you describe their content. There are no strict constraints, but typically a presentation would be about 12-15 slides or 7-10 minutes. Submission is via Sakai and the deadline is April 15th (midnight).

Final Project Report

The deadline for the project report is April 29 (midnight), submission is via Sakai. The format for this is intentionally flexible, i.e., there are no length requirements, etc. However, the report should describe the problem you investigated and how you addressed it, i.e., provide as much detail about your solution as possible. This can include things such as:

Useful Links

Conflict of Interest (COI) Management

Prof. Christian Poellabauer has a financial interest in a local startup company in the area of healthcare technologies (HealthyPoints, LLC). If you are concerned about actual, potential, and perceived conflicts of interests due to Dr. Poellabauer's involvement in this entity, please contact his COI oversight manager and CSE department chair, Dr. Pat Flynn!