Towards Precision Yoga Rehabilitation: Integrating Computer Vision, Wearable Inertial Sensors and Heart Rate Variability Monitoring: A Narrative Review

Aishwarya Sathishraj *

Department of Yoga Therapeutics, SDM College of Naturopathy and Yogic Sciences, Ujire, Karnataka, India.

Shivaprasad Shetty

Department of Yoga Therapeutics, SDM College of Naturopathy and Yogic Sciences, Ujire, Karnataka, India.

Prashanth Shetty

Department of Yoga Therapeutics, SDM College of Naturopathy and Yogic Sciences, Ujire, Karnataka, India.

*Author to whom correspondence should be addressed.


Abstract

Background: Prop-assisted yoga is used to accommodate movement limitations during orthopaedic rehabilitation, but assessment of posture, effort and recovery often depends on clinician observation.

Aims: To provide a narrative review of the evidence for prop-assisted yoga in common orthopaedic conditions and to propose a digital health framework that combines camera-based posture assessment, wearable inertial measurement units (IMUs) and heart rate variability (HRV) monitoring for objective, individualised rehabilitation.

Study Design: Narrative review with a conceptual framework.

Place and Duration of Study: SDM College of Naturopathy and Yogic Sciences, Ujire, India; the literature was reviewed and synthesised between 2025 and 2026.

Methodology: Peer-reviewed journal articles were identified through targeted searches of PubMed/MEDLINE and publisher databases, supplemented by citation tracking, covering yoga for chronic low back pain, knee osteoarthritis and neck pain; markerless pose estimation; wearable IMU kinematics; HRV methodology and wearable photoplethysmography; and telerehabilitation. Sources were synthesised thematically into movement, physiological and feedback layers.

Results: Randomised trials and systematic reviews support yoga, including Iyengar-based and prop-supported programmes, as a moderately effective option for chronic low back pain and show encouraging but smaller or less certain effects in knee osteoarthritis and neck pain, with mostly minor and transient adverse events. Markerless pose estimation can estimate joint angles from ordinary video with errors that depend on the joint, plane, camera position and posture, and is weakest where limbs are occluded or the pose is unusual, as in many yoga postures. Wearable IMUs measure segment orientation with fewer line-of-sight constraints but introduce set-up burden and drift. HRV indices such as the root mean square of successive differences (RMSSD) can quantify autonomic responses and support breath-paced practice, yet wrist-worn photoplethysmography is vulnerable to motion artefact during active postures. Telerehabilitation evidence suggests outcomes comparable to in-person care for musculoskeletal conditions. No study has yet validated a combined camera, IMU and HRV system in prop-assisted yoga for orthopaedic patients.

Conclusion: A layered, clinician-supervised ecosystem is plausible and may improve safety, adherence and dose individualisation, but it remains a hypothesis. Validation against reference systems in yoga-specific postures, standardised HRV acquisition protocols and pragmatic trials with safety outcomes are priorities.

Keywords: Yoga, orthopaedic rehabilitation, pose estimation, inertial measurement unit, heart rate variability, digital health, telerehabilitation, biofeedback


How to Cite

Sathishraj , Aishwarya, Shivaprasad Shetty, and Prashanth Shetty. 2026. “Towards Precision Yoga Rehabilitation: Integrating Computer Vision, Wearable Inertial Sensors and Heart Rate Variability Monitoring: A Narrative Review”. Journal of Complementary and Alternative Medical Research 27 (11):239-47. https://doi.org/10.9734/jocamr/2026/v27i11810.

Downloads

Download data is not yet available.