Path Loss Analysis and Transceiver Development for Human Body Communication-Based Signal Transmission for Wearable Robot Control

Abstract

Human body communication (HBC) technology is attracting a lot of attention for monitoring vital data and controlling wearable robot. In this paper, we focused on electroencephalogram (EEG) signal transmission from head to wrist in the 10-60 MHz HBC band. This is based on an idea to transmit an EEG signal to control a wearable robot. First, we clarified the basic transmission mechanism and characteristics using a highly simplified human body model. Next, we performed a detailed path loss analysis by finite difference time domain simulation using an anatomical human body model with various postures. Based on the analysis results, we identified the optimum transmitter position on the head and developed an impulse radio transceiver for verifying the feasibility of the technique. The results show that the developed transceiver can provide a data rate of 10 Mbps and the bit error rate can be kept below 10-3 for transmitting the EEG signals from the head to the wrist. Experimental validation with a bio-equivalent gel phantom also demonstrated high feasibility of transmitting the EEG signals along the human arm.