UX Researcher, UX Designer
2023
Figma, Notion, Maze, Zoom, Photoshop, Illustrator, Miro
Competitive Analysis, User Interviews, Journey Maps, Storyboarding, Usability Testing, Prototype, Project Management, Visual Design
Christine Lee Chiang, Arcadiy Avrorov, Logan Perez
2023 Capstone Award Winner
Maryland Institute College of Art
Healing Heads is a migraine management tool that helps migraine patients manage their condition. The project aims to alleviate the burden migraine patients face, improve their quality of life and overall well-being.
This case study is from my capstone project, which I completed as a final requirement from my masters degree in UX Design at Maryland Institute College of Art.
A migraine is much more than a bad headache. This neurological condition can cause debilitating throbbing pain that can leave patients in bed for days. It affects people from all ages, gender, races and social classes and can significantly impact a person’s quality of life, including their ability to work, socialize and participate in daily activities.
How might we help migraine patients manage their condition so that they can improve their overall well-being?
The main beneficiary of this project are individuals suffering from migraine. I identified both chronic and episodic migraine sufferers as my target audience.
To approach the problem, I drafted a timeline of activities and methodologies. For project management, I used Notion to create a timeline of deliverables. The following product strategy was accomplished:
My competitive analysis showed that there are already a few migraine apps in the market. I found that they have a comprehensive tracking feature and a good user base. However, while a lot of data is being collected from tracking, the data derived was underutilized. What do users do with this data beyond tracking?
Migraine Buddy is a headache and migraine tracking application. It has a community of around 3.5 million people who contribute to migraine awareness and research. It is very widely used, has good interface and a comprehensive migraine tracking feature. However, there are limited personalization options and a lack on integration with other health applications.
Migraine Monitor connects patients with specialists. It helps migraine patients record their symptoms, track triggers and treatments, and connect anonymously with other migraine patients. It helps specialists in remote patient monitoring by providing a platform to effectively monitor migraine care. It has a robust symptom tracking feature, user-friendly interface and customizable tracking options.
Migraine Insight is a migraine app that helps patients track their migraines, communicate their records better in emergencies with their care team, and automate their tracking. It has a user-friendly interface and data-driven insights. However, there is limited availability of content in some languages, potential reliance on user-generated content and competition from other educational platforms.
What do users do with this data beyond tracking?
l interviewed 6 migraine patients to learn:
l interviewed 2 subject matter experts to understand:
Synthesizing results with an affinity map helped me find themes and insights from my interviews:
I created an affinity map to synthesize my results. This helped me find themes, patterns and generate insights from my results.
I created a total of three personas for two user types: the migraine sufferer and the doctor.
The migraine sufferer is an individual suffering from migraines and is experiencing migraine attacks regularly in their lives.
The doctor is a neurologist specializing in the diagnosis, treatment and management of neurological conditions. He has his own practice and consults with patients in person and online.
Mind mapping helped me find better solutions faster, help retain information and express ideas visually and hierarchically. To further support my ideation phase, I drafted some crazy eights at a cafe to help me brainstorm for ideas. Napkin sketches have often been my go-to companion when I find that spur of the moment inspiration.
I envisioned my output to be a functional app for users to input their information. In return, Healing Heads will utilize this data to help users in migraine management. A unique value proposition of this app is the integration of AI and Machine Learning into its features. The overall concept of this integration revolves around data gathering, finding patterns and insights, and synthesizing this data into predictions and recommendations.
Information architecture helped me organize, structure and label content in an effective way. This provided the foundation as I proceeded to creating my prototype.
Wireflows helped me visualize the user and system flow. I added arrows and annotations between wireframes to indicate the paths a user may take while using the app. Low fidelity wireframes and prototypes helped me to visualize solutions at an early stage. These outputs enabled me to gather early feedback and design iterations.
I used Maze to conduct unmoderated tests, where users completed tasks independently. I had a total of 8 testers with the following objectives:
My design system consisted of a style guide and components. My choice of using dark mode was made to address light sensitivity. I also chose monochromatic tones to create a sense of calmness and serenity. The shades of blue also reflect calmness, healing, soothing, knowledge and wisdom.
The purpose of the onboarding flow is to gather initial data to understand user’s background and identify user type. This initial data gathering allows the app to tailor fit the content for them, and to train models from the data gathered.
To determine which age demographic to categorize the user.
To determine which set of hormonal triggers is applicable to the user.
To categorize the user as an episodic or chronic migraine sufferer.
To determine which data sets can be automated or should be manually asked to input.
The objective of this flow is to understand the user’s unique condition and help them recognize triggers by identifying patterns from their inputs. This data gathering process allows the app to improve the accuracy of predictions given to the user.
To log the onset and end of an attack.
To log the intensity level of pain the user experiences.
To pinpoint specific areas where the user feels pain.
To log migraine symptoms the user experiences.
To log triggers the user was exposed to which led to this particular attack.
I created an alternative method for users to log their migraine attacks. This method give the users an option to record their answers during an attack. The phone will ask the same set of questions as the one above. Instead of presenting the questions in text format, it will read it out loud for the user to hear. The user can communicate their answers with their phone by recording themselves.
Phone reads questions out loud for the user to hear.
Follow up questions may be asked depending on users answer.
User taps to record their answer.
All answers are collated into a summary for the user to review and submit.
This flow lets users input their everyday lifestyle and habits. It can help users understand the correlation between their lifestyle and migraines, and to help them consolidate their records.
To log the users lifestyle record such as water intake and hours of sleep.
To log the users daily stress level.
To log triggers the user was exposed to during the day.
To log medication or supplements taken during the day.
With the data collected from the three user flows, the data model generates predictions. The information is relayed to the user in various parts of the app.
Lists down days with a probability of getting an attack.
Provides a high level overview showing days with available predictions.
A percentage of attack probability is listed.
Predictions are labelled as high, mid or low probability with color representation.
I also included a statistics page that collates all the data gathered from user inputs, summarizes and presents them in infographics. The purpose of presenting data into visualization is to make data easier for the human brain to understand and pull insights from. Visualization helps users recognize relationships and patterns between data and gives it greater meaning.
Environmental factors such as pressure, weather and humidity.
Lifestyle patterns such as hours of sleep, water intake and stress levels.
Migraine patterns like duration, symptoms and pain spots.
Because of the nature of my project, accessibility played a big role in my project. During pain days, the last thing a user would want to do is to spend a lot of time interacting with an app. Migraine patients also suffer from light sensitivity, which is made worse during an ongoing attack. I ideated solutions to consider making my product accessible to the unique needs of my users.
Reducing screen time by giving the user an option to record answers instead of manually inputting them.
An option to play binaural beats to provide relief during an ongoing attack.
Easing visual strain for users with light sensitivity and photophobia.
Here is my presentation deck and a video walkthrough of my final prototype.
If I were to continue working on this project, I would refine my research, and continue to iterate and test. I would also improve accessibility further by incorporating gestures and shortcuts. Since I focused on the needs of only one of my persona for this project, I could iterate solutions for my other personas. Some features I can look into incorporating are: