Wearable Tactile Sensor Suit for Natural Body Dynamics Extraction: Case Study on Posture Prediction Based on Physical Reservoir Computing

We propose a wearable tactile sensor suit, which can be regarded as tactile sensor networks, for monitoring natural body dynamics to be exploited as a computational resource for estimating the posture of a human or robot that wears it. We emulated the periodic motions of a wearer (a human and an android robot) using a novel sensor suit with a 9-channel fabric tactile sensor on the left arm. The emulation was conducted by using a linear regression (LR) model of sensor states as readout modules that predict the next wearer's movement using the current sensor data. Our result shows that the LR performance is comparable with other recurrent neural network approaches, suggesting that a fabric tactile sensor network can monitor the natural body motions, and further, this natural body dynamics itself can be used as an effective computational resource.

Automated summary

The study introduces a wearable tactile sensor suit for monitoring natural body dynamics and estimating human or robot postures. By using linear regression models to emulate wearer's movements, the research demonstrates that fabric tactile sensor networks can effectively monitor natural body motions.