Sakshi Sense
An AI-assisted meditation companion integrating respiratory, motion and autonomic signals for real-time attentional biofeedback.
Research area
Translational research on meditation, attention and human performance through wearable sensing, real-time biofeedback, immersive environments and AI-assisted applications.
Scope
This translational theme develops tools grounded in the centre’s research on attention, contemplative practice and physiological regulation. Wearable and contactless sensing, biofeedback and immersive environments are explored as ways to support practice and measure change outside tightly controlled laboratories.
Evaluation includes efficacy, safety, privacy, accessibility and the limits of inference from personal data. The goal is useful, evidence-aware technology that supports human agency rather than replacing judgement or making ungrounded clinical claims.
Current directions
An AI-assisted meditation companion integrating respiratory, motion and autonomic signals for real-time attentional biofeedback.
Ultra-short-term autonomic markers designed to identify mind wandering and support sustained attention.
Non-compressive sensors and deep-learning analysis of breathing, movement and heart-rate variability.
Evaluation of meditation in real and virtual settings using physiological, cognitive and affective outcomes.
Research record
Peer-reviewed work, chapters and current manuscripts connected with this research theme.
IEEE Sensors Journal 26(1), 1088–1102
https://doi.org/10.1109/JSEN.2025.3628683Manuscript under review
Springer · Cognitive Biomarkers and BCI Applications
https://doi.org/10.1007/978-3-032-20634-3_10Academic Press · Biological Measures of Well-Being
https://doi.org/10.1016/B978-0-443-28842-5.00001-6