Smart Yoga Mat Using IoT for Real-Time Posture Monitoring

The IoT-enabled Smart Yoga Mat proposed in this study is designed to assist beginners in performing yoga exercises correctly without continuous supervision from an instructor. Many home users struggle to maintain proper posture, which can reduce the effectiveness of yoga and may cause physical strain. The system combines a webcam for posture capture with an ultrasonic sensor to monitor body position on the mat. Image frames are processed using pose-estimation tools such as OpenCV and MediaPipe to identify joint locations and calculate body angles. These values are compared with stored reference data to detect incorrect posture and provide feedback through a mobile interface. Experiments conducted on several common yoga poses showed quick response time and high detection accuracy in indoor conditions. The developed solution is portable, low-cost, and suitable for personal fitness practice, demonstrating how IoT technology can enhance safe and guided yoga training at home.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-24
DOI
https://doi.org/10.5281/zenodo.19200543
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Yoga Mat Using IoT for Real-Time Posture Monitoring

Pranil A Patil, D.R. Kamble, Shreya Patil, Pranjali Panwal et al.
Zenodo (CERN European Organization for Nuclear Research)
Hand Gesture Recognition Systems
article

Smart Yoga Mat Using IoT for Real-Time Posture Monitoring

Pranil A Patil, D.R. Kamble, Shreya Patil, Pranjali Panwal, Priti Deshmukh
article en

Abstract

The IoT-enabled Smart Yoga Mat proposed in this study is designed to assist beginners in performing yoga exercises correctly without continuous supervision from an instructor. Many home users struggle to maintain proper posture, which can reduce the effectiveness of yoga and may cause physical strain. The system combines a webcam for posture capture with an ultrasonic sensor to monitor body position on the mat. Image frames are processed using pose-estimation tools such as OpenCV and MediaPipe to identify joint locations and calculate body angles. These values are compared with stored reference data to detect incorrect posture and provide feedback through a mobile interface. Experiments conducted on several common yoga poses showed quick response time and high detection accuracy in indoor conditions. The developed solution is portable, low-cost, and suitable for personal fitness practice, demonstrating how IoT technology can enhance safe and guided yoga training at home.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 14%
Hand Gesture Recognition Systems
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