Passive Health Monitoring Using Large Scale Mobility Data

In this paper, Prof Vas Kostakos team report on the feasibility of using mobility patterns and demographic data to predict hospital visits. They collect cellular mobility traces from two thousand users in China for a period of two months and show that hospital visits can be predicted with 79% accuracy. Their results show people are more likely to visit hospitals if they exhibit less absolute mobility, less visit diversity, visit few sports facilities, and there exist more diverse entertainment venues near their visited locations. These results shed light on how to use readily available cellular mobility data to monitor a population’s health.

Read the publication here

Continue reading

Evaluating the opportunity for technology use in bariatric surgery dietetic care and health services: A mixed methods study
MRFF Grant Success for HaBIC R2 – ATLAS+
Berlin-Melbourne University Alliance: A 2-Day Study Hackathon
Has Covid-19 boosted adoption of Telehealth around the world?
View all news