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Video link: https://youtu.be/3vn_TF-ezTE
In this episode of The Heart Rate Variability Podcast, host Matt Bennett sits down once again with Stephanie White, HRV coach and educator known affectionately as “the HRV Guru.” Together, they dive deep into advanced heart rate variability concepts—especially heart rate fragmentation (HRF), very high frequency (VHF) activity, and new HRV metrics that can reveal hidden issues in autonomic health.
Stephanie shares insights from her work with clinicians, coaches, and patients—explaining why sometimes clients can’t reach the “Optimal Zone” in the Optimal HRV app and what physiological patterns might be behind it. She also outlines the importance of minerals, CO₂ balance, and careful data interpretation when working with HRV readings.
Stephanie’s Background – Her recovery journey from chronic illness using HRV biofeedback and her work with VCU’s Comprehensive Autonomic Center.
Why HRV Data Sometimes “Doesn’t Make Sense” – How heart rate fragmentation can hijack HRV signals and confuse traditional measures like RMSSD.
RMSSD vs. SDNN – Why SDNN may better capture resonance frequency breathing and coherent sine wave patterns.
Understanding Heart Rate Fragmentation (HRF) – How alternating or sawtooth heart rhythms create misleading HRV statistics and mask underlying autonomic issues.
Introducing “Very High Frequency (VHF)” – What happens when HRF shifts heart power above 0.4 Hz, and why current HRV software often misses it.
The Role of CVNN and PSS – New or underused HRV metrics that can quantify fatigue, allostatic load, and fragmentation.
Practical Clinical Applications – How coaches and clinicians can identify HRF, interpret data accurately, and help clients avoid “false high” HRV readings.
Mineral Balance and HRV Health – Why calcium, sodium, potassium, and magnesium are crucial for healthy cardiac rhythm and recovery.
Building an HRV Coaching Certification Pathway – Stephanie’s vision for “HRV Behavioral Health Coaches” and measurable, data-driven client progress.
By Optimal HRV3.5
1010 ratings
Video link: https://youtu.be/3vn_TF-ezTE
In this episode of The Heart Rate Variability Podcast, host Matt Bennett sits down once again with Stephanie White, HRV coach and educator known affectionately as “the HRV Guru.” Together, they dive deep into advanced heart rate variability concepts—especially heart rate fragmentation (HRF), very high frequency (VHF) activity, and new HRV metrics that can reveal hidden issues in autonomic health.
Stephanie shares insights from her work with clinicians, coaches, and patients—explaining why sometimes clients can’t reach the “Optimal Zone” in the Optimal HRV app and what physiological patterns might be behind it. She also outlines the importance of minerals, CO₂ balance, and careful data interpretation when working with HRV readings.
Stephanie’s Background – Her recovery journey from chronic illness using HRV biofeedback and her work with VCU’s Comprehensive Autonomic Center.
Why HRV Data Sometimes “Doesn’t Make Sense” – How heart rate fragmentation can hijack HRV signals and confuse traditional measures like RMSSD.
RMSSD vs. SDNN – Why SDNN may better capture resonance frequency breathing and coherent sine wave patterns.
Understanding Heart Rate Fragmentation (HRF) – How alternating or sawtooth heart rhythms create misleading HRV statistics and mask underlying autonomic issues.
Introducing “Very High Frequency (VHF)” – What happens when HRF shifts heart power above 0.4 Hz, and why current HRV software often misses it.
The Role of CVNN and PSS – New or underused HRV metrics that can quantify fatigue, allostatic load, and fragmentation.
Practical Clinical Applications – How coaches and clinicians can identify HRF, interpret data accurately, and help clients avoid “false high” HRV readings.
Mineral Balance and HRV Health – Why calcium, sodium, potassium, and magnesium are crucial for healthy cardiac rhythm and recovery.
Building an HRV Coaching Certification Pathway – Stephanie’s vision for “HRV Behavioral Health Coaches” and measurable, data-driven client progress.

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