Seeme
Proactive digital self-tracking tool to encourage engagement and persistence in weight control
Duration
3 Weeks
Oct 2020
Project Feature
Mobile interaction design
Datafication of health care
Digital self-tracking
Health and wellbeing
My Role
Research & Strategy Lead
Concept and Story Design
Prototyping
Team
This is a solo project
Background
Overweight and obesity are important lifestyle-related public health problems worldwide. In China, due to the improvement of people's health awareness and income level, the fitness industry has risen rapidly in recent years. Nevertheless, the retention rate of such services is high and the obesity rate in China has still been rising.
“Technology that is static, that is passive, doesn’t persist and doesn’t engage you.” ”
The Challenge
How might we empower average users suffering from overweight and obesity issues to better practice weight control?
The Solution
A mobile app service that features proactive visual projections of people’s body shape based on their daily health data input
How I got there?
01 — Exploration
Desktop Research
I conducted secondary research on the health trend in China and also the domestic fitness industry. The research includes publications, data, academic journals, and business reports. This step helped me to better understand the problem space and hypothesize the potential causes of the rising obesity and overweight rate in China.
Analysis
The speed of China’s weight gain and the quirks of its consumer culture suggest that the economic and social impact of a fatter population could be particularly significant
Why do people give up weight control?
02 — Primary Research
Market research and analysis
Despite their good intentions, many fitness products and services today are inaccessible and difficult to use. Devices that simply collect and display numerical information about users’ behavior are unlikely to spur them to make durable changes in their habits.
User Interview
I talked to 6 people for in-depth interviews on their experience of weight control. This step helped me generate insights from the users’ perspectives and understand their pain points and needs.
03 — Opportunities
User Persona
04 — Ideation and Prototyping
Finding the right cognitive model for design intervention
Based on our research finding, effective self-control and monitoring is key to successful weight control to our target users. Therefore, we decide to look upon an integrative dual systems model of self-regulation drawn from cognitive neuroscience to guide design efforts (Figure 1).
In brief, this model distinguishes between automatic, non-conscious ‘System 1’ control, that is, well-learned habits or instinctive responses triggered by external stimuli and internal states; and deliberate, conscious ‘System 2’ control triggered by goals, intentions, and rules held in working memory.
Ideation
Technical Research
Algorithms for Prediction
Currently, many types of algorithms have been adopted for predictions. After research, I found the Autoregressive time series algorithm to be a good model for predicting the user’s future body-shape changes. The autoregressive model learns the behavioral pattern of the past data in order to do time series forecasting of future trends.
Low-fidelity prototype
Wireframe
05 — Final Design
How does it work?
Simple weight change calculations
Users let the app know their basic information and typical meals in a day. The app will generate their basal metabolism (BM) and average daily calorie intake as the basis for calculating weight change. Users do not need to enter what they eat every day, which is tedious and hard to persist.
As for daily energy expenditure, users will be asked to give the app permission to share health and fitness data with Apple’s Health app. The app then knows how many calories the user has burned in a day.
Customized user avatar
Users can customize their avatars to reflect their true body images. The changes include hairstyle, body measurement, and accessories. This helps them to better relate to the avatar and achieve optimal results.
“Confess”
If users ate anything high in calories besides their typical meals, they can choose to “confess” their guilty pleasure. After hitting “confess,” the avatar will turn into a red demon for a second. This data will be counted towards everyday calorie intake for calculation and projection.
Future projection
Users can move the sidebar to see the future projections of themselves through the avatar. Based on the accumulative calorie intake, the system will calculate whether the users will gain weight or not. If the user is on the right track to lose weight, the avatar will show green light; otherwise, it will show red light so as to alarm.
06 - Reflection
In this project, I explored datafication of self-care practice. I learned how today’s data-tracking tools and analytics could help render up previously elusive insights and predictions. I found this capacity of data collection and representation to be particularly useful in the case of assisting people’s weight control. By visualizing their projected future-self, people could be more informed about the impacts of their daily behaviors - every step, every bite, etc. This kind of data visualization is more proactive, making a statement itself to encourage behavior changes, rather than simply collecting displaying data.
Admittedly, it is difficult to accurately predict how one’s body will change, given that weight change involves complicated biological mechanisms. However, I believe in the future, with more advancements in data tracking and analytics, we will have accurate weight change predictions to help people understand their health data more easily and empower them to make a change.