Chronic pain is a common syndrome that affects 18 percent of the adult population in Sweden. It often takes a long time to receive the diagnosis causing a lot of suffering for the people affected.
MUNI is a product that assists people with chronic pain to find faster ways of coping through tracking activity behaviour and pain levels. MUNI finds correlations between activity patterns and reported pain levels while making suggestions for actions that have pain reducing effects.
Inspiration and Method
In this project, I have been in contact with pain specialist at Umeå University Hospital and people living with chronic pain to get an understanding of the topic. The people that I was in contact with suffered from pain located in different areas, back pain, headaches and general pain states. Even though having pain at different locations, there were commonalities how the pain affected them, the effects on social relations, the importance of physical activity and the need for pacing their activities.
The topic of chronic pain is extremely large and the problem is complex, to get an understanding of what could be helpful in coping with the pain, three sacrificial concepts were created that served as probes to get feedback on what could be meaningful for the users. The insights of these three concepts were evaluated and transformed into the fourth and final concept, MUNI.
MUNI is a tool that is provided by the primary care physician when they suspect that the patient might be suffering from chronic pain. The wearable tracker provided collects information from the user's activity and sleeping behaviors along with their reported pain levels. In the patient application, an AI processes the data collected from the tracker and looks for correlations. When the AI finds a correlation it suggests an action the user can take to reduce the pain.
For example, the AI finds a correlation between being inactive for longer durations increase the pain, it suggests to set an action, in this case, a reminder to move 5min every 1hour being inactive.
The processed data is uploaded to a clinician tool that allows the user and physician to get a better overview of the patient's condition when taking decisions for medical treatments.