Wearable Inertial Sensor-Based Hand-Guiding Gestures Recognition Method Robust to Significant Changes in the Body-Alignment of Subject

The accuracy of the wearable inertia-measurement-unit (IMU)-sensor-based gesture recognition may be significantly affected by undesired changes in body-fixed frame and sensor-fixed according to change subject sensor attachment. In this study, we proposed a novel IMU-sensor-based hand-guiding method robust significant subject’s body alignment based on floating bi-directional long short-term memory (bi-LSTM). Through comparative experimental studies with other two methods, it was confirmed that aligning reference human updating body-heading direction helped improve generalization performance model. As result, showed 91.7% test accuracy, confirming appropriate for under during gestures.