A recent study demonstrates how smart devices and machine learning can objectively monitor loneliness levels with 82% accuracy.
Key insights:
- Multi-Device Integration: Combining data from smartphones, smartwatches, and rings enhanced predictive accuracy.
- Behavioral Insights: Phone usage and notifications were the most predictive of loneliness.
- Innovative Methodology: Leveraging passive sensing eliminated the need for active user input, reducing participant burden.
At Centralive, we support researchers by offering seamless platforms for IoT and data integration, driving innovation in mental health studies.
📖 Explore the full findings
Authors:
Salar Jafarlou ,Iman Azimi,Jocelyn Lai,Yuning Wang,Sina Labbaf,Brenda Nguyen,Hana Qureshi,Christopher Marcotullio,Jessica L. Borelli,Nikil D. Dutt,Amir M. Rahmani
