UStEMG: an Ultrasound Transparent Tattoo-based sEMG System for Unobtrusive Parallel Acquisitions of Muscle Electro-mechanics

Abstract

Human machine interfaces follow machine learning approaches to interpret muscles states, mainly from electrical signals. These signals are easy to collect with tiny devices, on tight power budgets, interfaced closely to the human skin. However, natural movement behavior is not only determined by muscle activation, but it depends on an orchestration of several subsystems, including the instantaneous length of muscle fibers, typically inspected by means of ultrasound (US) imaging systems. This work shows for the first time an ultra-lightweight (7 g) electromyography (sEMG) system transparent to ultrasound, which enables the simultaneous acquisition of sEMG and US signals from the same location. The system is based on ultrathin and skin-conformable temporary tattoo electrodes (TTE) made of printed conducting polymer, connected to a tiny, parallel-ultra-low power acquisition platform (BioWolf). US phantom images recorded with the TTE had mean axial and lateral resolutions of 0.90 +/- 0.02 mm and 1.058 +/- 0.005 mm, respectively. The root mean squares for sEMG signals recorded with the US during biceps contractions were at 57 +/- 10 mu V and mean frequencies were at 92 +/- 1 Hz. We show that neither ultrasound images nor electromyographic signals are significantly altered during parallel and synchronized operation.