Adults who have finished cancer treatment often carry a heavy physiological burden long after the last chemotherapy session or surgery. Stress responses that were once adaptive can become chronic, and one window into that burden is heart rate variability, the natural beat-to-beat variation in the heart’s rhythm. A new early-phase study, published in BioPsychoSocial Medicine, reports mixed but intriguing signals that a structured yoga therapy program may influence both heart rate variability and how people perceive their own autonomic nervous system functioning. The researchers are careful about what the findings mean: this was a small, unblinded, single-subject experimental study designed to detect an early signal, not to confirm that yoga therapy works.
The study enrolled 20 adults, with a mean age of 55.7 years, 85 percent of them women, and an average of 2.8 years since their cancer diagnosis. Participants had completed curative-intent treatment at least three months earlier and were not scheduled for further treatment for at least five months. People taking cardiac medications, including beta-blockers, were excluded, as were anyone who had practiced yoga therapy since their diagnosis. Recruitment had originally targeted 30 participants, but it stopped at 25 when the COVID-19 pandemic began, and five participants withdrew before the intervention started, leaving 20 for analysis. Enrollment ran from May 2017 to September 2019 at the Centre for Health Innovation in Ottawa, Canada.
The intervention itself was deliberately distinct from a typical drop-in yoga class. Yoga therapy is defined as the process of empowering individuals to progress toward improved health and wellbeing through the application of the teachings and practices of yoga, and it is personalized, non-prescriptive, and progressive. Participants first received a 90-minute one-on-one session that included a detailed assessment, followed by six weekly 60-minute small group sessions with two to three participants per therapist. Sessions combined postures, mindful somatic movements, breathing exercises, meditation, and imagery-based relaxation, adapted continuously to each person’s needs. Attendance was high, with participants attending 138 of 140 possible sessions, and no adverse events were recorded.
Measuring the body’s response required more than questionnaires. Each participant wore a Hexoskin Smart Shirt, a garment with embedded textile electrocardiograph sensors, during seven assessment visits. After sitting quietly for 30 minutes in a quiet room, without reading, music, or phone use, the last 30 minutes of resting electrocardiographic data were analyzed. The researchers deliberately avoided a controlled breathing protocol, because asking people to pace their breathing would override the spontaneous autonomic regulation they wanted to observe. From these recordings they computed heart rate plus metrics in three domains: time-domain measures including the coefficient of variation, SDNN, and RMSSD; frequency-domain measures including low-frequency power, high-frequency power, and the LF/HF ratio; and a nonlinear complexity index, sample entropy.
Self-reported autonomic functioning was captured with the state and trait versions of the autonomic regulation scales, which ask about orthostatic-circulatory, rest/activity, and digestive regulation. Higher scores reflect better perceived self-regulation. The study design, a single-subject experimental approach with multiple baseline assessments, meant each participant completed three assessments before the intervention began, two during it, and two after it ended, at weeks 7 and 12. This structure allowed the team to model each person’s baseline trend before yoga therapy started, rather than assuming everyone began from a stable state.
The statistical approach, hierarchical linear modeling, estimated four quantities for each outcome: the average level at the start of the intervention, the linear rate of change over time, the immediate shift when yoga therapy was introduced, and whether the rate of change differed between the baseline and intervention phases. The results were genuinely mixed. Significant time, phase, and time-by-phase effects appeared for state autonomic functioning, the coefficient of variation, and high-frequency power. Trait autonomic functioning showed a significant time-by-phase effect, and sample entropy showed significant time and phase effects. For the remaining heart rate variability metrics, including mean heart rate, SDNN, RMSSD, LF power, and the LF/HF ratio, only the intercept reached significance, meaning no intervention-related effects were detected.
Some of the significant patterns are physiologically interesting. High-frequency power, which is associated with respiratory fluctuations and reflects parasympathetic activation, increased immediately after the first one-on-one session and continued to rise more steeply once the intervention was underway. The authors suggest this could reflect augmented vagal modulation of the heart, a shift toward parasympathetic dominance that would support cardiovascular recovery and down-regulation of the stress response. Sample entropy, which quantifies the unpredictability of inter-beat intervals, also rose immediately after the first session, which the authors interpret as possibly indicating a more adaptable autonomic state rather than rigid system dynamics.
Other findings are harder to interpret. The coefficient of variation actually decreased immediately after the first session, and the authors note that the physiological significance of this metric is less clearly established in the literature than traditional heart rate variability indices, so they urge caution. Self-reported state autonomic functioning showed an immediate increase after the first session and a steeper upward trajectory afterward, while trait autonomic functioning improved in slope but not in overall rate of change. The authors emphasize that effect sizes were small, their clinical significance is unclear, and inferring therapeutic benefit from heart rate variability changes alone is not possible without linking those changes to meaningful clinical outcomes.
Several limitations shape how these results should be read. The sample was predominantly female, White/Caucasian, well-educated, higher-income, and largely diagnosed with breast cancer, limiting generalizability. The multiplicity of statistical tests raises the risk of false positives, and no adjustment for multiple testing was made because the goal was sensitivity to any potential signal. Participants were not screened for autonomic dysfunction, disease status such as remission or recurrence was not recorded, and breathing during recordings was not standardized. Music played during sessions, inconsistent assessment timing, and the absence of any control condition all add potential confounding. The single-subject design cannot disentangle the intervention’s effects from time-related maturation or historical influences, so the findings are explicitly preliminary and hypothesis-generating rather than causal.
What the study does establish, in the authors’ words, is the initial proof of concept needed to justify larger studies. The registered trial, ISRCTN64763228, was retrospectively registered in December 2021. The team recommends that future research employ a control condition, recruit larger and more diverse samples, test varying dosages and formats including one-on-one-only delivery, evaluate long-term effects, and incorporate heart rate variability measured during stress-eliciting tasks to capture how flexibly the autonomic system responds under challenge. They also suggest exploring what participants themselves feel drives any effects, through qualitative work. For now, the message is measured: a seven-week yoga therapy program produced detectable shifts in some, but not all, markers of autonomic regulation in adults after cancer treatment, and those shifts are worth pursuing with the rigor only larger, controlled trials can provide.
Subject of Research: Effects of yoga therapy on heart rate variability and autonomic nervous system functioning in adults after cancer treatment
Article Title: Detecting effects of yoga therapy on heart rate variability and autonomic nervous system functioning in adults after cancer treatment: results from a study using single-subject experimental methods
Article References: Brunet, J., Hussien, J., Pitman, A., Wurz, A., Conte, E., Herry, C., Polskaia, N., Seely, A., & Seely, D. (2026). Detecting effects of yoga therapy on heart rate variability and autonomic nervous system functioning in adults after cancer treatment: results from a study using single-subject experimental methods. BioPsychoSocial Medicine, 20(1), Article 13. https://doi.org/10.1186/s13030-026-00367-x
Image Credits: AI Generated
DOI: 10.1186/s13030-026-00367-x
Keywords: yoga therapy, heart rate variability, autonomic nervous system, cancer survivors, single-subject experimental design, parasympathetic activity, hierarchical linear modeling, wearable sensors, proof-of-concept study, supportive cancer care, Detecting, effects
News Source: Nathaniel Bowman. (October 29, 2026). Yoga Therapy Shows Early Signals of Shifting Heart Rate Variability After Cancer. Scienmag.
