Evidence map›Paper›PMID 41922620›Full record

ArticleScientific reports2026

Technical validation of a multimodal emotion-adaptive biofeedback system for autonomic regulation using guided breathing.

C R Srinivasan, Pulkit Kumar, S Meenatchi Sundaram

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

C R SrinivasanManipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India.
Pulkit KumarManipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India.
S Meenatchi SundaramManipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India. meena.sundar@manipal.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breathing interventions delivered through biofeedback have been shown to support physiological modulation consistent with resonance breathing responses. However, most biofeedback systems on the market are based on fixed procedures, provide limited physiological feedback, and do not adapt to user comfort or emotional state. The system is designed to work under a typical 20-min biofeedback timeframe and uses a two-stage adaptive respiration rate (RR) algorithm that gradually converges toward resonance frequency while dynamically responding to signs of emotional discomfort. System-level testing was conducted using reference-grade measurement instruments. Respiration rate estimation showed low mean absolute error, while heart rate and heart rate variability measures demonstrated high agreement with reference standards. During adaptive biofeedback, the system was associated with a decrease in respiratory rate and electrodermal activity, along with increased heart rate variability, consistent with increased parasympathetic influence inferred from HRV trends. These results indicate the technical validity and system-level feasibility of an emotion-aware multimodal biofeedback framework. The proposed framework provides a scalable foundation for future controlled and longitudinal validation studies.

Indexed as

Autonomic Nervous SystemBiofeedback, PsychologyEmotionsRespirationAlgorithmsHeart RateHumansRespiratory RateAdaptive algorithmsAutonomic modulationClosed-loop biofeedbackDigital healthEmotion recognitionMultimodal biofeedbackResonance breathing

Identifiers

PMID41922620
PMCPMC13181121

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.