Balance evaluation system using wearable IMU sensing

The evaluation of balance and postural stability holds significant importance in both medical rehabilitation and daily life. However, the clinical method is hindered by the inconvenience of immobility and relatively high costs associated with the force platforms. Wearable sensors, such as accelerometers, have emerged as an alternative solution, overcoming the limitations of traditional force platforms. Thus, the purpose of this study is to utilize data obtained from a low-cost, portable, small-sized IMU (specifically an accelerometer) to predict indicators derived from force platform devices. A miniaturized and portable acceleration test equipment was proposed. Together with the random forest algorithm, our classification method achieved classification results with accuracy, recall, precision, f1-score, and specificity scores above 95%, This study provides a more portable and highly accurate tool for assessing balance ability.