Work Buddy

Work Buddy is a behavioral tracking app on computer that helps people who primarily work on the computer maintain good posture and take breaks in between for long-term health benefits.

UX designer
UX researcher

Contextual Inquiry
Usability testing
Data analysis

4 HCI master students @ Gatech

15 weeks

Ⅰ. Overview

Problem Space

As Computer-based technology has infiltrated many aspects of life, computers have become the primary equipment for many people to work, communicate, and entertain. People spend more time sitting in front of the computer nowadays than in the past.

As a result, it raises the problem of how to help people maintain good physical position and postural stability while interacting with computers to improve long-term posture health.

(The image on the right is us working on laptops for this project)


We designed a behavioral tracking and intervention desktop app, and it monitors and optimizes people's posture, reminds users to take a break from working on a computer, and educates them about good posture and stretching techniques.

Set up Work Buddy on device

Users can turn on and off Work Buddy on the home page and navigate between the home screen and the 'desktop pet' on their devices to optimize the user experience.

Initiate break reminders

Users can create break reminders based on their schedule to balance working and resting time and reduce pain. The system would activate the 'desktop pet' to remind users to take breaks in between work.

Learn good posture and stretch

The system contains a library of posture and stretch knowledge for users to explore and learn about proper posture and methods to relax in order to reduce bodily pain.

Ⅱ. Research

User Research

We came to a realization of common postural problems that we all faced after studying on computers for a long period of time. We began from a vague idea of helping people, especially those who primarily work from home, who may have similar issues to maintain good sitting posture.

To explore the problem space and understand user behavior of interest, we determined to conduct 4 user research methods: exploratory research, public observation, interview, and survey.
(click to check the research details)

Preliminary Research

Since the topic involves a lot of professional health-orientated subjects, we decided to focus on literature reviews and study of existing systems for the preliminary research, so we could understand the existing health solutions and what the health professionals contributed to the topic. We discovered that:
Increased self-reported body pain
Heavily focus on ergonomics products
Intrusive existing postural solutions

Observation in public workspaces

In the exploratory phase, we realized that the postural issue was not exclusive to remote workers rather to all professionals who work on computers. Therefore, we decided to enlarge our target audience group from remote workers to professionals working with computers.

We also found it challenging to step into people's private spaces and observe their working posture, so we decided to conduct a total of 10.8-hours observation sessions at 3 different public spheres that were popular for people to work. By this way, we were able to understand how people posed on various pieces of furniture and interacted with electronic equipment.
Local Coffee Shops
School Libraries
Business Centers

Qualitative Data Coding and Analysis

We took 399 descriptive notes and coded the qualitative data into 29 keywords based on the subject matter of the observation as well as the frequency that appeared on the notes. Below are the top 5 most popular postures that we discovered, which uncovers some common postural patterns among the potential users.
Leg Crossed
Hand on Cheek

User Interviews

Public observation only gave us a glimpse of user behavior, and we wanted to learn about their interests and needs in depth. Therefore, we conducted 30-minutes semi-structured interviews with 4 professionals who primarily worked on computers in a nonconventional office setting on Zoom and asked 40+ questions. We asked the participants to turn on the camera, so we could acquire an image of their working environment.

Interview Data Analysis

We used an affinity diagram to map 203 pieces of interview data and concluded 5 high-level summarized ideas on Miro. The affinity mapping helps understand user behavior and interests and define the common themes for ideation in the next step.

Survey Process

We also wanted to extend the user research and gain insights into how what user siting posture and their working spaces looked like and whether they had experience in improving posture to relieve bodily pain. Therefore, we designed a 11-questions survey on Qualtrics and disseminated it to faculty and staff at Georgia Tech.

Survey Data Analysis

We received 40 responses in total and used Excel and Tableau to analyze the survey data. We discovered that:

Key Research Findings

Although we employed 4 different research methods to collect data, we discovered many similarities and common interests in the different sets of research data. We summarized them into 5 high-level key research findings that helped develop our design solutions in the next phase.

Ⅲ. Ideation


To understand who we are designing for, we created 3 fictional characters who can be our potential users and generated personas for them based on the research data.  

Empathy Maps

Then, we wanted to understand how these 3 potential users feel about our product. We make 3 empathy maps that list their attitudes and behaviors in response to some postural challenges.

Design Solutions

Based on the key research findings, we defined 5 design solutions, and each solution would turn into a key function to address user pain points in the final product.

Design Concepts

To turn our 5 design solutions into a viable product, we proposed 2 design concepts with key functionalities that tackle to user pain points.

Posture Optimization App (left) is a mobile-based application integrating AR technology to help optimize sitting posture. Users can use phone cameras to scan a chair, and based on their input data, the system provides personalized instructions on how to sit on it.

Posture Reminder
(right) is a desktop application with a screen accessory, consisted of both digital and physical forms. The computer camera is activated to track user posture, and the system can read the data and remind users to sit properly and take work breaks.  

Concept Testing

We conducted a 60-minutes testing session with 4 potential users to evaluate the 2 design concepts. We presented the design to the users and asked 15 follow-up questions about their thoughts and reactions. Then, we summarized the feedback and turned it into a chart to compare these two design concepts and evaluate whether they meet the listed design solutions.
Overall, users expressed a positive attitude toward both design concepts. However, they found Posture Reminder more useful, because they believe the user cases of Posture Optimization App are limited to acquiring a new chair, which is not a frequent event for them. Further, based on their feedback, Posture Reminder does a better job of fulfilling the 5 design solutions. Therefore, we decided to move on with Posture Reminder and turned the latter design concept into a wireframe.

Ⅳ. Design


Based on the feedback we received from the users, we turned Design Concept 2 into a wireframe to clarify the initial layout, key features, and user flow maps in preparation for wireframe testing and a high-fidelity prototype.

Wireframe Testing

We invited 4 target users, of which 3 of them were UX professionals and 2 experienced chronic back pain, to participate in 60-minutes cognitive-walkthrough. We walked them through the flow diagrams and asked them 18 follow-up questions to evaluate whether the wireframe design meets the 5 design solutions and incorporate accessibility consideration.


Based on the wireframe feedback we received, we made changes to the wireframe and turned it into a hi-fi prototype on Figma by redesigning the user flows, finalizing functional details, and standardizing the design system. This step also prepared for the usability testing in the the next stage.

Navigate from home screen to desktop reminder

Remind users to take breaks in between work

Track metrics of user postural progress

Educate users about good posture for work

Encourage users to stretch to relieve pain

Help users to adjust sitting posture with camera

Ⅴ. Testing

Usability Testing

To test the functionality of the main features, we utilized 3 usability testing methods and invited 9 participants (2 UX professionals, 1 physical therapist, and 6 target users). The testing sessions were an hour long and taken placed online and on-site, depending on the availability of the participants.

Testing Methods & Justification

Heuristics Evaluation
Expert Testing with UX Professionals
Since UX experts had prior knowledge of usability testing and Heuristics evaluations, it was most appropriate to ask them to look for problems across 10 categories of heuristics and see if the system is usable.
Think Aloud
User Testing with Target Users
We invited 6 users who primarily worked from home to use the system and complete 8 tasks on a high-fidelity interactive prototype on Figma. Users were encouraged to share their thoughts when working on the tasks. It helped gain knowledge from actual users of the system.
Subject-Matter Evaluation
Expert Testing with Physical Therapist
Since the effectiveness of Work Buddy relies on its ability to gather appropriate data and provide meaningful feedback to users about their physical well-being, we invited a physical therapist to participate in a subject-matter expert evaluation to give feedback on the content.

User Tasks & Metrics

For the testing sessions with the UX experts and target users, we designed 8 user tasks for the participants to finish in a mocked realistic situation, which is a high-fidelity interactive prototype on Figma.

The tasks cover all the main functionalities of the system with the intention of checking whether the system converges with the 10 Heuristics Evaluations.

We aimed to observe their reactions and hear their opinions while performing the assigned tasks, so we could understand whether our design meets the user’s expectations and addresses their difficulties. Also, it could inform us how to iterate the design and optimize the user experience in the next stage.
(click the image on the right for task details and its Heuristics measurements)

Outcomes & Next Steps

Based on the feedback that we received from the participants, we summarized 6 areas that could be improved to ensure that the interface and user flows are clear, understandable, and usable.
Many participants found the wording confusing and inconsistent, so some wording choices may need to be revised for clarification.
There were many UI problems; for example, the buttons were not in alignment. The interface may need to adjust for visual clarity and aesthetics.
Data Visualization
Some color choices of the graphs may contain negative connotations that diverge from the intention of our design, so we need to redesign the data visualization.
Many users complained about the filters, which caused confusion. The filters need to redesign for users to quickly understand and easily navigate.
Some interaction designs violated the conventional design rules, such as the toggle button, and we need to follow the Heuristics rules to resolve these problems.
Many users had a difficult time understanding and using the calendar, so the calendar implementation and design may need to reconsider.

Ⅵ. Reflection

Lesson Learned

Tailored Testing for User Groups

We made the mistake of assuming everyone has prior knowledge of UX and usability testing, so I learned that customizing usability tests according to user groups can make the best out of the testing sessions.  

Learn from Users

Our users helped us to investigate the problem deeper and gain valuable insights. They were also able to offer ideas and resources helpful in the product development process.

Cross-functional Collaboration

Teamwork is the key to success, and I had a chance to work with 3 amazing team members with different expertise. We were able to bring our skill sets to the project and worked on the areas that we were good at doing it.