A Novel Physical Human Robot Interface with Pressure Distribution Measurement Based on Electrical Impedance Tomography

Measurements of pressure distribution on physical human-robot interfaces are crucial for ensuring the comfort and safety of human-exoskeleton interactions. To address this need, we propose a novel sensorized physical human robot interface with pressure distribution measurement based on Electrical Impedance Tomography (EIT). EIT sensors have the advantages of a simple structure and the ability to continuously measure pressure over a large area, making it a promising solution for wearable robots. A piezoresistive composite made of Carbon Black (CB) and flexible polymer was fabricated and embedded in a physical interface to compose the EIT sensor. To improve the spatial solution of the EIT inverse problem, a Convolutional Neural Network (CNN) enhanced Tikhonov regularization (referred to as CNN-TR) approach was adopted. The original compressed image is first reconstructed with Tikhonov regularization and then enhanced by the CNN model that trained with simulation data. Then a validation platform is built based on a MARK-10 force tester. The experimental results showed that developed EIT sensor with cNn-TR reconstruction method achieves accurate localization and size estimation of the compressed area, and is capable of distinguishing multiple compressed areas. Additionally, the EIT sensor is embedded into a physical interface to measure the compressed areas between the physical interface and human lower limb. The results validate that the proposed EIT pressure sensor is suitable for physical interfaces.