Real-Time Monitoring System of Sedentary Behavior with Android Wear and Cloud Computing : An office case study
Abstract: Nowadays, prolonged sitting among office workers is a widespread problem, which is highly related to several health problems. Many proposals have been reported and evaluated to address this issue. However, motivating and engaging workers to change health behavior to a healthier working life is still a challenge. In this project, a specific application has been deployed for real-time monitoring and alerting office workers for prolonged sitting. The proposed system consists of three distinct parts: The first one is an android smartwatch, which was used to collect sensor data e.g., accelerometer and gyro data, with a custom android wear app. The second one is an android application, which was developed to act as a gateway for receiving the smartwatch’s data and sending them to IBM Bluemix cloud with MQTT protocol. The final part is a Node-Red cloud application, which was deployed for storing, analyzing and processing of the sensor data for activity detection i.e., sitting or walking/standing. The main purpose of the last one was to return relevant feedback to the user, while combining elements from gaming contexts (gamification methods), for motivating and engaging office workers to a healthier behavior. The system was firstly tested for defining appropriate accelerometer thresholds to five participants (control group), and then evaluated with five different participants (treatment group), in order to analyze its reliability for prolonged sitting detection. The results showed a good precession for the detection. No confusing between sitting and walking/standing was noticed. Communication, storage and analysis of the data was successfully done, while the push notifications to the participants, for alerting or rewarding them, were always accurate and delivered on time. Every useful information was presented to the user to a web-based dashboard accessed through a smartphone, tablet or a PC. The proposed system can easily be implemented at a real-life scenario with office workers. Certainly, there is a lot space for improvement, considering mostly the type of data registered at the system, the method for sitting detection, and the user interface for presenting relevant information.
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