SAN FRANCISCO, June 23, 2026 /PRNewswire/ — Dojo, the AI-native consciousness training platform behind a guided meditation and mindfulness app focused on measurable personalization, today released early findings from “The State of Meditation 2026: What Actually Calms the Human Body,” an aggregate analysis of first-party meditation session data with second-by-second heart-rate measurement that was cleaned into research-ready session metrics.
Across hundreds of qualified meditation sessions, heart rate decreased in 76.8% of sessions. The average heart-rate drop was 6.5 beats per minute, the median heart-rate drop was 5.11 beats per minute, and the median time to first heart-rate decrease was 1.0 minute. On average, sessions reached their minimum heart rate after 7.63 minutes. Among sessions with resting-heart-rate data, 27.0% went below the user’s recorded resting heart rate during meditation.
Dojo created the analysis to better understand how meditation affects the body during real practice sessions. The company analyzed completed meditation sessions with sufficient per-minute heart-rate coverage from H1 2026, using anonymized aggregate data from its research warehouse. Sessions without enough usable physiological data were excluded from the research cohort.
“Meditation should be measurable,” said Asaf Shamir, Founder and CEO of Dojo. “People should be able to see when their body is responding, not just guess whether a practice worked. Heart rate is not the whole story, but it gives us a real physiological signal that can help make meditation more concrete.”
Meditation is often described through subjective experience: calmer, clearer, less reactive, or more grounded. Dojo’s research adds a physiological layer by looking at how the body changes second by second during actual sessions. In the analyzed dataset, the average session duration was 12.36 minutes, the median first heart-rate decrease occurred after 1.0 minute, and the average session reached its minimum heart rate after 7.63 minutes.
Dojo is built for people who want more than static audio libraries. The company creates personalized meditation sessions that adapt based on user goals, preferences, and physiological signals such as heart rate. The product is designed to help users discover which meditation exercises and techniques, from focus and visualization to breath work, body scans, and other practice structures, appear to shift their state.
“People should not have to guess what works for them,” said Shamir. “The future of AI meditation is not just generating more audio. It is building a feedback loop between the mind, the body, and the practice, so each person can train in a way that reflects their real response.”
The strongest aggregate finding was that 76.8% of research-qualified sessions lowered heart rate from the beginning of the session to the end. The analysis also found that sessions had an average start heart rate of 73.64 bpm and an average end heart rate of 67.14 bpm. The average absolute heart-rate change was 8.96 bpm, and the average largest heart-rate drop from session start was 11.37 bpm. Dojo also analyzed resting-heart-rate response where that data was available. In sessions with resting-heart-rate data, 27.0% went below the user’s recorded resting heart rate, with a median time to first below-resting-heart-rate point of 2.0 minutes. This release focuses on the strongest aggregate findings from sessions that met Dojo’s data-quality criteria. More detailed breakdowns by session length, meditation technique, time of day, and experience level are reserved for future reports.
The analysis was conducted on anonymized aggregate data and designed to protect user data privacy rights. Dojo used completed sessions with sufficient heart-rate coverage and treated missing heart-rate data as missing rather than inferred. The dataset includes heart-rate data, but Dojo is not making device-specific claims from this analysis. The report focuses on aggregate physiological response during meditation rather than comparisons by device type or demographic segment.
Dojo’s long-term goal is to make meditation more personalized, measurable, and responsive. Through AI-guided session generation and physiological feedback, the company is developing a system that can help users understand which practices are most likely to support calm, focus, emotional regulation, sleep preparation, recovery, and stress reduction.
“AI can personalize mind training in a way static content never could,” said Shamir. “If the system can learn from what someone says they need and how their body responds, meditation can become less generic and more useful.”
Available as a meditation app for iOS, Dojo supports custom meditation, breath work, body scan meditation, meditation music, meditation with binaural beats, morning meditation, evening meditation, meditation for sleep, meditation for gratitude, and energizing breath-work. The app is designed for both meditation beginners and advanced users who want a personal meditation guide that can respond to their goals and physiological feedback.
Learn more about Dojo at https://www.medidojo.com/
Download Dojo on the App Store: https://apps.apple.com/us/app/dojo-master-meditation/id6503365052
Research blog post: https://www.medidojo.com/blog/state-of-meditation-2026/
Access the complete findings: research paper (PDF) and full report (PDF).
About Dojo
Dojo is an AI-native consciousness training platform built in California. The company creates adaptive meditation experiences based on user goals and physiological feedback, including heart rate and related signals. Unlike traditional apps built around static content libraries, Dojo helps users generate personalized meditation sessions in real time, making meditation more measurable, customizable, and responsive.
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SOURCE Medidojo, Inc.
