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. The course will be based on recent publications in the fields of healthcare and engineering and each paper will be discussed in terms of the underlying healthcare problem, the technological foundations of the proposed solution or implementation, unresolved challenges, and open opportunities. Further, students will also choose a specific healthcare concern or technology and prepare 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.

Class Information

Lecture Time
Mondays 10am-12pm
HS i4 (MDEG160G)


Christian Poellabauer (
Office Hours
TBD and by appointment
Office Location
Date Topics Assignments
March 4th, 2019 Introduction, Syllabus, Administrative Items
The Future of Pervasive Health (Connelly et al., 2017) (optional)
The P4 Health Spectrum (Sagner et al., 2017) (optional)
2018 Global Health Care Outlook (Deloitte, 2018) (optional)
A Journey Towards Smart Health (Deloitte, 2018) (optional)
March 11th, 2019 Sensors for Healthcare and Wellness
A Survey of Mobile Phone Sensing (Lane et al., 2010)
Mobile Crowdsensing: Current State and Future Challenges (Ganti et al., 2011)
March 18th, 2019 Wireless Medical Sensor Networks
A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments (Ghamari et al., 2016)
March 25th, 2019 Wearables and Implantables
Wearable Health Devices - Vital Sign Monitoring, Systems and Technologies (Dias et al., 2018)
April 1st, 2019 Digital Biomarkers and Health Analytics
mCerebrum: A Mobile Sensing Software Platform for Development and Validation of Digital Biomarkers and Interventions (Hossain et al., 2017)
April 29th, 2019 Smart Health for Rehabilitation
Designing Informed Game-Based Rehabilitation Tasks Leveraging Advances in Virtual Reality (Lange et al., 2012)
Wearable Movement Sensors for Rehabilitation: A Focused Review of Technological and Clinical Advances (Porciuncula et al., 2018)
May 6th, 2019 Smart Health for Neurological Conditions
Support for a Clinical Diagnosis of Mild Cognitive Impairment Using Photoplethysmography and Gait Sensors (Gwak et al., 2018)
Comparison of Video-Based and Sensor-Based Head Impact Exposure (Kuo et al., 2018)
May 13th, 2019 Smart Health for Psychological Conditions
Rainer/Michael (Time-critical Health Applications based on Bluetooth Low Energy)
Karl/Stefan (Analysis of Biomarkers Contained in Sweat)
MoodScope: Building a Mood Sensor from Smartphone Usage Patterns (LiKamWa et al., 2013)
May 20th, 2019 Smart Health for Healthy Aging
A Review of Smart Homes - Past, Present, and Future (Alam et al., 2012)
June 3rd, 2019 Smart Health for Chronic Conditions
Hannah (Alzheimer's: Using Smart Technologies for Prediction and Patients' Support During Disease Progression)
Oliver (Reading Brain Activity: What Can Be Measured Using Which Sensors?)
Stanley (IoT Solutions for Early Stage Detection and Management of Charcot Arthropathy)
Christian (What Role Does a Potentiostat Have in the Area of Health Care?)
Smartphone Applications for Patients' Health and Fitness (Higgins et al., 2016)
June 17th, 2019 Ethics and Regulatory Considerations
Tarik (Wearable Sensor Bracelets for Detection of Health Emergencies)
Andrea/Martin (Data Privacy for Health Applications)
Markus/Benjamin (Smart Pill - Record Internal Data of the Gastrointestinal Tract for Use in Medical Topics)
Lukas (Smart Home Health)
Digital Health: Meeting the Ethical and Policy Challenges (Effy et al., 2018)
June 24th, 2019 Review & Final Exam


Component Points
Readings Weekly reading assignments. 20%
Homework Written report. 20%
Homework Oral presentation. 20%
Exams Final Exam. 30%
Participation Regular class attendation and contribution to course discussions. 10%
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.