Precise sensing of force magnitude and direction in massage therapy can significantly enhance treatment effectiveness. Despite advancements in flexible multidimensional force sensors, achieving comprehensive spatial force sensing with soft materials remains challenging. This study presents a novel flexible six-axis force/torque sensor, calibrated using a deep neural network. The calibrated sensor exhibits a maximum class I error of 0.603%F.S. and a maximum class II error of 0.751%F.S., indicating excellent measurement performance. Demonstrated in massage physiotherapy, the sensor effectively distinguishes between various techniques and accurately detects subtle force variations within the same technique. The present work introduces a novel strategy for designing flexible six-axis force/torque sensors, thereby laying the groundwork for advancements in intelligent robotics, human–computer interfaces, as well as in the fields of rehabilitation and medicine.
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