# ZotCare: A Flexible, Personalizable, and Affordable mHealth Service Provider

arXiv: https://arxiv.org/abs/2307.01905 · HTML: https://mlsanity.com/paper/2307.01905/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jul 2023.

## Built on by (most cited first, 6 of 6)

- [Conversational Health Agents: A Personalized LLM-Powered Agent Framework](https://mlsanity.com/paper/2310.02374/) (2023)
- [Differential Private Federated Transfer Learning for Mental Health Monitoring in Everyday Settings: A Case Study on Stress Detection](https://mlsanity.com/paper/2402.10862/) (2024)
- [Integrating Wearable Sensor Data and Self-reported Diaries for Personalized Affect Forecasting](https://mlsanity.com/paper/2403.13841/) (2024)
- [Enhancing Performance and User Engagement in Everyday Stress Monitoring: A Context-Aware Active Reinforcement Learning Approach](https://mlsanity.com/paper/2407.08215/) (2024)
- [Graph-Augmented LLMs for Personalized Health Insights: A Case Study in Sleep Analysis](https://mlsanity.com/paper/2406.16252/) (2024)
- [Loneliness Forecasting Using Multi-modal Wearable and Mobile Sensing in Everyday Settings](https://mlsanity.com/paper/2410.00020/) (2024)

## Abstract (arXiv)

The proliferation of Internet-connected health devices and the widespread availability of mobile connectivity have resulted in a wealth of reliable digital health data and the potential for delivering just-in-time interventions. However, leveraging these opportunities for health research requires the development and deployment of mobile health (mHealth) applications, which present significant technical challenges for researchers. While existing mHealth solutions have made progress in addressing some of these challenges, they often fall short in terms of time-to-use, affordability, and flexibility for personalization and adaptation. ZotCare aims to address these limitations by offering ready-to-use and flexible services, providing researchers with an accessible, cost-effective, and adaptable solution for their mHealth studies. This article focuses on ZotCare's service orchestration and highlights its capabilities in creating a programmable environment for mHealth research. Additionally, we showcase several successful research use cases that have utilized ZotCare, both in the past and in ongoing projects. Furthermore, we provide resources and information for researchers who are considering ZotCare as their mHealth research solution.