Comparison between sEMG and force as control interfaces to support planar arm movements in adults with Duchenne: a feasibility study

Abstract

BackgroundAdults with Duchenne muscular dystrophy (DMD) can benefit from devices that actively support their arm function. A critical component of such devices is the control interface as it is responsible for the human-machine interaction. Our previous work indicated that surface electromyography (sEMG) and force-based control with active gravity and joint-stiffness compensation were feasible solutions for the support of elbow movements (one degree of freedom). In this paper, we extend the evaluation of sEMG- and force-based control interfaces to simultaneous and proportional control of planar arm movements (two degrees of freedom).MethodsThree men with DMD (18–23 years-old) with different levels of arm function (i.e. Brooke scores of 4, 5 and 6) performed a series of line-tracing tasks over a tabletop surface using an experimental active arm support. The arm movements were controlled using three control methods: sEMG-based control, force-based control with stiffness compensation (FSC), and force-based control with no compensation (FNC). The movement performance was evaluated in terms of percentage of task completion, tracing error, smoothness and speed.ResultsFor subject S1 (Brooke 4) FNC was the preferred method and performed better than FSC and sEMG. FNC was not usable for subject S2 (Brooke 5) and S3 (Brooke 6). Subject S2 presented significantly lower movement speed with sEMG than with FSC, yet he preferred sEMG since FSC was perceived to be too fatiguing. Subject S3 could not successfully use neither of the two force-based control methods, while with sEMG he could reach almost his entire workspace.ConclusionsMovement performance and subjective preference of the three control methods differed with the level of arm function of the participants. Our results indicate that all three control methods have to be considered in real applications, as they present complementary advantages and disadvantages. The fact that the two weaker subjects (S2 and S3) experienced the force-based control interfaces as fatiguing suggests that sEMG-based control interfaces could be a better solution for adults with DMD. Yet force-based control interfaces can be a better alternative for those cases in which voluntary forces are higher than the stiffness forces of the arms.

Offering a helping hand

“…These findings clearly point out the problem to develop a single design that would fit everyone. This has already been pointed out by endusers describing their perceptions about existing wearable robotic devices for the upper limb in the study of Elnady et al [39], and similar results were found when men with Duchenne Muscular Dystrohpy used different control modalities to control arm movements [93]. Endusers in their study suggest that a one-size-fits-all device does not exist since every stroke survivor has his/her own situation [39].…”

“…In a study with men with Duchenne Muscular Dystrophy was also found that subjective preference for a control modality; surface electromyography or force-based control, differed between participants. This variety in preferences was depending on the level of arm function [93]. Unfortunately, the majority of AT for the hand are currently controlled by either one of those subconscious or conscious control modalities [40].…”

2nd Workshop on upper-extremity assistive technology for people with Duchenne: Effectiveness and usability of arm supports Irvine, USA, 22nd–23rd January 2018

“…Dr. Joan Lobo Prat presented his early work on the control of robotic arm supports for people with DMD using surface EMG and force signals [27,28] . In addition, he presented the development of MOVit, a novel, arm exercise-enabling driving interface for powered wheelchair users.…”

Hand neuro-motor characterization and motor intention decoding in Duchenne muscular dystrophy

“…Force and sEMG were identified as promising methods to decode motor intention in individuals with DMD. Despite the unintuitive concept of using muscular signals to decode motor intention in a group of individuals suffering from a muscular disease, myocontrol has shown potential and even more surprising for individuals with DMD, where the disease was in later stages [54]. sEMG signals with enough merit for motor intention decoding, were identified even in a very late stage individual with DMD [55].…”

“…This can be achieved by a positionbased compensator. The impedance compensation controller needs to be calibrated beforehand in order to compensate for joint-stiffness induced torques, similar to the active stiffness compensation proposed by Lobo-Prat et al [217]. Additionally, the impedance compensation controller can be used to provide active gravity compensation including weight compensation of handheld objects.…”