Axiom H2
Biohacking companion app for the Axiom H2 hydrogen therapy machine.
What's
The Problem?
What's
The
Scope?
The project involved designing a companion iOS app for a hydrogen therapy machine. The primary challenge was to prioritize product features through user research.
What's
The Challenge?
User Needs Identification: Understanding the diverse needs of users ranging from athletes to those with chronic conditions.
Lack of Connectivity: Designing an app for a non-connected device.
Market Competition: Differentiating the product in a market with similar offerings.
The Machine
The Axiom H2 machine produces molecular hydrogen. It’s odorless and tasteless. You can inhale the hydrogen through your nose, apply the hydrogen to your eyes, or through your ear canal, for brain health. You can also use the machine, with an attachment, to create your own hydrogen enriched water.
The Competion
The Axiom H2 machine has a lot of competitors out there, but they all do basically the same thing. The key differences are mostly in terms of advertising and marketing.
Analysis
All About Hydrogen
Hydrogen, besides being the most abundant element on earth, has a lot to offer.
Antioxidant Activity
Anti-Inflammatory
Effects Gene Expression
Immune Modulation
Safe / Not New
How to Measure Hydrogen Therapy's Effectiveness
That depends on the user.
User 1
User 2
User 3
Main Users
1) Athletic recovery and biohacking customers, of which there were not many.
2) People suffering from chronic conditions, that are receptive to alternative, healing therapies.
3) And finally, people who use hydrogen as a preventative measure.
How to Measure These User's Hydrogen Therapy's Effectiveness
1) They like hard data, data from other wearables, like respiratory rates and blood o2 saturation numbers.
2) These users are most concerned about staying “young”. They could monitor their “cellular age” through epigenetic testing, which we’ll revisit later.
3) These folks have probably exhausted the limits of the current medical system and are looking for relief on their own terms, so monitoring and self-reported metrics of their symptoms may prove useful.
Qualitative User Research
I wanted to conduct actual user research, to learn more about the machine’s users.
I found 5 of them.
I spoke with them about their background, why they use the machine, how often they use it, and how they measure success.
Key Findings
1) Mostly used as healing from autoimmune disease, like lupus.
2) All owners expressed interest in epigenetic testing, but wanted more information about it.
3) All user’s want to improve their health, and the machine may be just one element.
Synthesis
Once I could take a step back and study my research, I formulated a new problem statement so I could have a narrower focus going forward.
Competitive Research
Once I could look at the problem from a wider perspective, the perspective of over-all health, I could also look for examples from indirect competitors.
Building Components
The cancer.net app proved a very useful study, showing a way that I could structure the Axiom app around a health dashboard of sorts.
I gathered a list of common symptoms for autoimmune disease sufferers, things like anxiety, fatigue, constipation, etc... These symptoms are really just a starting point, though.
Symptoms Tracking
I gathered a list of common symptoms for autoimmune disease sufferers, things like anxiety, fatigue, constipation, etc...These symptoms are really just a starting point, though. There is also a space for the user to name, and therefore, track a symptom of their choosing. Once the user selects a symptom, and date (with a current time default) they can quickly rate the severity.
This data will be logged and can be referred to on the dashboard.
Tracking Hydrogen Usage
No matter what kind of user you are. Hydrogen intake is what makes this app unique.
Users can easily select their intake type and time from convenient, predetermined intervals.
Once they log their event, the data is stored and can be referred to on the dashboard.
Logging Data
This dashboard is where all the logged data can be seen in a visual representation.
Of course you can apply different to the graph, based on H2 delivery methods, timeframes, etc…
This data can be downloaded and shared, allowing users the ability to connect with each other over individual successes and failures.
The Main Dashboard
Logging data and tracking graphs is all well and good, however, the living beating heart of the app is the dashboard--where all the data comes together, to help the user.
At the very top of the dashboard we have trends and reminders.
Trends are just factoids of data movement direction. For example – they could report on symptoms that are improving or hydrogen use that is declining or point out the correlations between medications and symptoms.
Reminders, on the other hand, kind of goad the user into taking actions – like reminding the user to change the filter of the machine (every two weeks), or reminding the user to continue to log their symptoms after a delay. Reminders could be extrapolated into OS notifications, as well.
Design Summary
Feature Set: Logging hydrogen usage, tracking health symptoms, and integrating reminders for maintenance and usage.
Dashboard: Centralized user data to visualize trends and correlations.
User Testing: Prototypes tested with initial users, leading to positive feedback on usability and potential health management benefits.
Personal Reflections
This was a short, explorative project. Axiom may go forward with the app or they may not. I, however, learned a lot in the design process. I really had to push past the initial problem (of tracking hydrogen usage) until I got a broader view of things. Once I was able to see a user, with their needs and frustrations, I could begin looking for comparable solutions. Then, I still needed to implement a fresh system to bring everything together, which would be the dashboard.
In retrospect a dashboard is obvious, but it was only going through the entire process that I understood the dashboard's true meaning and usage. Because I used a methodical design process, once I got to the dashboard element, I could feel the usefulness of the solution, relative to the project constraints. And that was a good feeling.
If Axiom chooses to move forward, they would really have to focus their engineering on creating the logic for the dashboard's reminders and trends.