Design Challenges for Wearable EMG Applications
Bojan Milosevic2,a, Simone Benatti1 and Elisabetta Farella2,b
1DEI, University of Bologna, Italy.
simone.benatti@unibo.it
2ICT Center - FBK, Trento, Italy.
amilosevic@fbk.eu
befarella@fbk.eu
ABSTRACT
Wearable technologies are changing the way we deal with health and fitness in our daily life. Nevertheless, while MEMS-enabled inertial sensors have conquered the consumer market, physiological monitoring has still to face barriers due to the complexity and costs of physical interfaces (e.g. electrodes), the degree of intuitiveness of the interaction and the processing required to reach satisfying performance. These limitations are mitigated by the embedded systems' growing integration of interfacing capabilities and efficient computing power. In this paper, we describe the main applications and the related technologies for the acquisition and processing of myoelectric (EMG) signals. Starting from well established active sensors and bench-top setups, we introduce a recent design based on the combination of an integrated Analog Front End (AFE) and embedded processing. This solution provides high quality signal acquisition and on-board digital processing capabilities with a contained power consumption. The system was tested within the prosthesis control application scenario, one of the most stringent EMG applications, achieving a 90% gesture recognition accuracy with real time on-board processing at a power consumption of 30mW. Such promising results highlight the current trend in shifting EMG applications from dedicated analog solutions towards integrated digital devices, favouring the development of advanced, modular and low-power wearable solutions.
