Skip to content

Using Generative Artificial Intelligence in Mindfulness Technology Within an Everyday Digital Context

Frances Anne Belleza, Jing-Yi Xie

Proceedings of the Human Factors and Ergonomics Society Annual Meeting September 7, 2026 DOI: 10.1177/10711813261485202 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Topics Meditation
Key points The authors present Recalibrate, a web application that uses generative AI and neural text-to-speech to generate personalized one-minute meditations and journal prompts based on a user's mood and somatic check-in. They argue that combining adaptive AI-generated guidance with lightweight reflective practices yields a transferable set of design considerations for supportive, low-demand reflective systems.

Abstract

Chronic stress contributes to adverse physical and mental health outcomes. Regular mindfulness practice has been shown to reduce stress and improve well-being. Although digital mindfulness tools are widespread, most applications rely on pre-recorded guided content and offer limited support for monitoring users’ internal processes or evaluating practice effectiveness. To address this gap, this project presents Recalibrate , a user-centered web application that integrates generative AI, a large language model (LLM), and neural text-to-speech (TTS) to support brief, personalized mindfulness practices within everyday digital contexts. Using a research-through-design approach, the system emphasizes reduced cognitive workload through short guided meditations, breath awareness, and optional reflective journaling. A typical session begins with a mood and somatic check-in, which informs the generation of a personalized one-minute meditation script and journal prompt. The meditation is delivered through natural voice output, followed by optional journaling, intention setting, and feedback. By combining adaptive AI-generated guidance with lightweight reflective practices, Recalibrate contributes a transferable set of design considerations for creating supportive, low-demand reflective systems.

Comparable studies

Other theoretical and historical papers on meditation, most cited first.

Citations in the library

Explore topics