Wireless and Mobile Health (mHealth) - Winter 2023

Course Instructor.

Course Description

Wireless and Mobile health (mHealth) aims to improve our health and well-being by utilizing data provided by technologies such as wearables, IoT devices, and mobile phones. This course will cover foundational knowledge and topical work in mHealth. Students will learn the essential steps needed to create a mHealth system from conception to evaluation through assigned reading, group discussions, and some hands-on projects. Since mHeath is an interdisciplinary field, we will cover a range of literature in human-computer interaction, wearable systems, machine learning, and health. Readings and in-class activities will prepare students for their final creative assignment that involves writing and presenting a research proposal for a mHealth system or research idea. Although this course will cover some technical aspects of mHealth, we encourage students with different backgrounds to enroll as they will work in interdisciplinary teams.

By the end of this course, students should be able to:

Understand the process of creating and evaluating a mHealth system Learn about developing an embedded system for mHeath applications using Arduino Understand resource optimization in mHealth systems Critically examine the impact of mHealth systems on people and society Analyze different types of data obtained from mHealth systems, including but not limited to the following sensors: ECG, PPG, accel/gyro, video, audio, proximity, ambient light, piezoelectric Design experiments to collect data and validate mHealth systems Write a proposal for a mHealth system or framework Grading All coursework will be graded and judged as either complete or incomplete. Students are expected to complete all assignments on time (unless they obtain an extension from the instructor). All assignments are due at 9:00 am central time on the due date.

The grading breakdown is as follows:

Class Participation (5%) Lead Class Discussions (15%) Paper Reviews (20%) Projects (30%) Research Proposal (30%)

Class Participation (5%)

Students are expected to attend all class sessions (unless students are granted prior permission to be excused). Additionally, students are expected to engage in class discussions by referencing relevant points from the readings, asking questions, and providing feedback to their peers. Students also participate by collectively annotating the reading assignments on Perusall.

Lead Class Discussions (15%)

mHeath is an interdisciplinary field that encompasses people from different backgrounds. [Insert goal of this activity] Every week, a group of students will lead the class discussion by presenting a topic not covered in the class but is related to mHealth. For example, if you are interested in diabetes management, you can choose to present the topic and engage your peers in a discussion. Another example is to utilize a skill that you have. For example, if you are an expert in 3D printing, you can demonstrate your skills to your peers. You will get the chance to choose a slot in the first week of class. This activity can be performed in a group of 1-4 students.

Paper Reviews (20%)

The paper reviews aim to encourage students to critically read the assigned readings to help students write their proposals. The reviews should mainly consist of the following sections: 1) paper summary, 2) things that you liked about the paper, 3) areas that you believe need more improvement or clarification. In addition, there will be a prompt specific to the topic of the week or previously covered topics in some review assignments. Reviews are due at 9 am on the assigned due date to allow the instructors to read over the reviews and incorporate them into class discussions.

Projects (35%)

We will get familiar with developing mHealth systems. Basically, we can employ embedded systems knowledge to develop mHealth systems that include microcontrollers, sensors, actuators, communication modules, learning algorithms, and firmware. As a result, we will learn about the embedded systems development process. We use an Arduino development board to develop our systems. There will be 4-5 small projects that will help us learn about the mHealth systems development process.

Research Proposal (25%)

Students will integrate in-class discussion and readings knowledge to create a mHeath research proposal. The proposal is divided into seven connected stages (S) that will prepare the students for their final submission. The stages are the following:

S1 - Focus area and idea generation and peer review of ideas (6%): There will be two separate steps for S1 inclusing:

• Focus area: In this stage, students will identify an area in health that they are interested in and would like to improve. Students also determine what type of mhealth contribution they want to make (e.g., building a system, analyzing data, understanding a population/process, etc.). This stage aims to help students understand what has already been investigated and identify gaps that can be filled. This stage’s deliverables will be a 1-2 pages single-spaced document (excluding references) that describes the chosen health focus area and the current mHealth research in that area. The aim is to provide the reader with the big picture of what has been done and is not answered. You do not need to go into detail here. Most of this information can be extracted from the abstract and the paper’s title. Google Scholar is a suitable source for searching for research articles. Once you find a paper, you can also check the citations of these papers, which is a possible way to find other related work.
• Idea generation and peer review of ideas: In this stage, you will produce three ideas related to the focused health area. The deliverables will be three short paragraphs introducing the problem, what has been done, and what you plan to do. In addition, you will be randomly assigned to review six pitches from your peers. This review aims to provide constructive feedback to help make the ideas as solid as possible. Good feedback will involve questions, identifying opportunities and risks, and suggesting modifications or extensions.

S2 - Team formation and Introduction and related work of the final proposal idea (8%): Students will be able to discuss their ideas in class, which will help them form project groups for the final proposal. The group should decide the final ideas they want to pursue and submit a 1-page proposal abstract or summary. A good proposal abstract should summarize the significance of or the need for the proposed work, the project’s main objective/contribution or hypothesis, the method used to achieve the objective or test the hypothesis, and finally, the impact of the work. In addition, students will present more details about their ideas by supporting their work’s significance and positioning it within the existing literature. This will require the team to read and summarize papers related to their research question to help demonstrate their work’s significance and novelty.

S3 - Methods and presentation of results (2%): In this stage, students will provide more details on how they can achieve their objectives. For example, groups proposing a system should describe how they will build such a system in style and explain how they can prove or show that their system archives their objective. Another example is a group that wants to interview a particular population to identify design opportunities; in this case, the group should provide details on how they would reach such communities, the questions they intend to ask in the interview, and why these questions are essential. Students also describe how they intend to present or communicate their results. The usage of graphics, tables, or charts is highly encouraged. Students are expected to get any results; however, planning how results should be analyzed to help find gaps in the experiment design or system evaluation method.

S4 - Final proposal document (3%) and presentation (6%) During finals week, students will get 10 minutes to present their proposal, followed by 3 minutes for Q&A. In the final proposal document, students must incorporate feedback from S2 and S3.

Main Textbooks:

1. Making Embedded Systems: Design Patterns for Great Software 1st Edition by Elecia White, ISBN-13: 978-1449302146, ISBN-10: 9781449302146.
2. TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers 1st Edition by Pete Warden & Daniel Situnayake, ISBN-13: 978-1492052043.
3. Wearable Sensors: Fundamentals, Implementation and Applications by Edward Sazonov, ISBN-13: 978-0124186620, ISBN-10: 0124186629.

Sensors and components to be used in this course:

IMU (inertial measurement unit) including accelerometer and gyroscope

Microphone

Optical Sensor for PPG Monitoring

Heart Rate Monitor (ECG)

Air Quality Sensor

GSR (galvanic skin response) Sensor

EMG (electromyography) Detector

UV Light Sensor

RGB Camera

Projects:

Physical activity recognition using IMU

Keyword spotting for anxiety level monitoring using audio

Stress detection using GSR sensor

Heart rate monitoring for anamoly detection using PPG and ECG signals

Food detection using RGB camera

Class Schedule