Advancing Gait Analysis in Physiotherapy: Sensor-Based Insights from the Ten Meter Walk Test

The Ten Meter Walk Test is a mobile application designed to improve gait analysis in physiotherapy, particularly for older adults. The application uses sensor-based data collection from wearable SensorTile.Box devices attached to shin pads to collect comprehensive lower limb movement data. Data was collected from 90 older adults aged 65–93 years. Machine learning techniques were applied to classify participant characteristics using Neural Networks, AdaBoost, Naive Bayes, and Decision Trees. Key findings showed up to 89% accuracy in gender classification, improved accuracy in disease classification to a binary task, and perfect accuracy in predicting walking aid usage. The study highlights the potential of integrating wearable sensors and mobile technology in clinical practice to enhance gait analysis.