Abstract
We report results from a pilot study that focuses mainly on understanding the everyday life quality of patients suffering from multiple sclerosis through the lens of connected Nokia Health devices. Our dataset comprises of 198 individuals (184 females and 14 males) and the study lasted over six months. By analyzing carefully crafted user-studies and correlating with personal sensor data collected with Nokia devices, we found that the level of fatigue is one of the main sources of discomfort across the majority of the patients. We further perform an exploratory analysis, which provides an early indication that by actively monitoring and perturbing users' daily activity levels, such as increasing daily step-counts, sleep duration and decreasing body weight, patients can potentially reduce their daily fatigue level.
Original language | English |
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Title of host publication | UbiComp'18 |
Subtitle of host publication | Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers |
Place of Publication | New York, NY |
Publisher | ACM |
Pages | 666-669 |
Number of pages | 4 |
ISBN (Print) | 978-145035966-5 |
DOIs | |
Publication status | Published - 2018 |
Event | 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 - Singapore, Singapore Duration: 8 Oct 2018 → 12 Oct 2018 |
Conference
Conference | 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 |
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Country/Territory | Singapore |
City | Singapore |
Period | 8/10/18 → 12/10/18 |
Keywords
- Connected devices
- Health
- Machine learning
- Statistical analysis