Wireless and Mobile Health (mHealth) - Winter 2022

Undergraduate and graduate course, Northwestern University, McCormick School of Engineering, 2022

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 (10%) Paper Reviews (25%) Projects (20%) Research Proposal (40%)

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 (10%)

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 (25%)

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 (20%)

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 (40%)

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 - Research Selection and Team formation (10%): Each group decides 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 main objective/contribution or hypothesis of the project, the method used to achieve the objective or test the hypothesis, and finally, the impact of the work.

S2 - Introduction and related work (5%): In this stage, students will present more details about their ideas by supporting the significance of their work and positioning their work within the existing literature. This will require the team to read and summarize papers related to their research question to help in demonstrating the significance and the novelty of their work.

S3 - Methods and presentation of results (5%) In this stage, students will provide more details on how they plan to 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 (10%) and presentation (10%) During the finals week, students will get 10 minutes to present their proposal followed by 3 minutes for Q&A. In the final proposal document, students are expected to incorporate feedback that they received from S5 and S6.

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.