A washable, stretchable fabric sensor embedded directly into clothing can recognize yoga postures with 94.4% accuracy, offering a comfortable alternative to rigid wearable motion trackers.
Researchers from the Institute of Intelligent Systems Research and Innovation at Deakin University have developed a smart textile strain sensor that can identify yoga postures with 94.4% accuracy, marking a significant advance in wearable motion-tracking technology. Integrated directly into stretchable fabric, the sensor provides comfortable, continuous movement monitoring without relying on rigid electronics components, making it suitable for fitness, rehabilitation and healthcare applications.
The device uses an interdigitated capacitive (IDC) sensor made by integrating laser-cut conductive silver fabric into a flexible Spandex textile. As the fabric stretches during movement, changes in the spacing of the conductive electrodes alter the sensor’s electrical capacitance, allowing body motion to be measured accurately. The soft, lightweight design maintains flexibility while offering greater comfort than conventional rigid wearable sensors.
To evaluate its performance, researchers incorporated the sensor into commercial sports leggings and tested it on nine participants performing four yoga postures: high lunge, forward lunge, squat and tree pose. The system recorded variations in capacitance, resistance and phase, which were analysed using machine-learning models, including logistic regression, random forest and extra-trees algorithms. The resulting system achieved an overall posture classification accuracy of 94.4%, with an F1 score of 94.2%.
Durability testing showed the textile sensor remained functional after 6,500 loading-unloading cycles, demonstrating strong resistance to repeated stretching. It also continued to operate reliably after 25 washing cycles, while temporary changes caused by moisture exposure were fully reversible, highlighting its suitability for everyday wearable use.
The researchers believe the technology could enable smart clothing capable of monitoring posture during exercise, supporting physiotherapy and rehabilitation, and tracking patient recovery remotely. Future work will focus on integrating wireless communication and low-power electronics, while validating the system with larger and more diverse participant groups to support practical deployment in healthcare, fitness and other wearable applications.
