title: Assessment of a Wearable Force- and Electromyography Device and Comparison of the Related Signals for Myocontrol.
abstract: In the frame of assistive robotics, multi-finger prosthetic hand/wrists have recently appeared, offering an increasing level of dexterity; however, in practice their control is limited to a few hand grips and still unreliable, with the effect that pattern recognition has not yet appeared in the clinical environment. According to the scientific community, one of the keys to improve the situation is multi-modal sensing, i.e., using diverse sensor modalities to interpret the subject's intent and improve the reliability and safety of the control system in daily life activities. In this work, we first describe and test a novel wireless, wearable force- and electromyography device; through an experiment conducted on ten intact subjects, we then compare the obtained signals both qualitatively and quantitatively, highlighting their advantages and disadvantages. Our results indicate that force-myography yields signals which are more stable across time during whenever a pattern is held, than those obtained by electromyography. We speculate that fusion of the two modalities might be advantageous to improve the reliability of myocontrol in the near future.
authors.affiliation: Cognitive Robotics, Institute of Robotics and Mechatronics, German Aerospace Center (DLR) Wessling, Germany.
authors.forename: Mathilde
authors.initials: M
authors.lastname: Connan
authors.affiliation: Cognitive Robotics, Institute of Robotics and Mechatronics, German Aerospace Center (DLR) Wessling, Germany.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Ruiz Ramírez
authors.affiliation: Cognitive Robotics, Institute of Robotics and Mechatronics, German Aerospace Center (DLR) Wessling, Germany.
authors.forename: Bernhard
authors.initials: B
authors.lastname: Vodermayer
authors.affiliation: Cognitive Robotics, Institute of Robotics and Mechatronics, German Aerospace Center (DLR) Wessling, Germany.
authors.forename: Claudio
authors.initials: C
authors.lastname: Castellini
keywords: force myography; human-machine interfaces; machine learning; multi-modal intent detection; rehabilitation robotics; surface electromyography