Comparing Surface and Intramuscular Electromyography for Simultaneous and Proportional Control Based on a Musculoskeletal Model: A Pilot Study

Abstract

Simultaneous and proportional control (SPC) of neural-machine interfaces uses magnitudes of smoothed electromyograms (EMG) as control inputs. Though surface EMG (sEMG) electrodes are common for clinical neural-machine interfaces, intramuscular EMG (iEMG) electrodes may be indicated in some circumstances (e.g., for controlling many degrees of freedom). However, differences in signal characteristics between sEMG and iEMG may influence SPC performance. We conducted a pilot study to determine the effect of electrode type (sEMG and iEMG) on real-time task performance with SPC based on a novel 2-degree-of-freedom EMG-driven musculoskeletal model of the wrist and hand. Four able-bodied subjects and one transradial amputee performed a virtual posture matching task with either sEMG or iEMG. There was a trend of better task performance with sEMG than iEMG for both able-bodied and amputee subjects, though the difference was not statistically significant. Thus, while iEMG may permit targeted recording of EMG, its signal characteristics may not be as ideal for SPC as those of sEMG. The tradeoff between recording specificity and signal characteristics is an important consideration for development and clinical implementation of SPC for neural-machine interfaces.

Meta-biomaterials

“…In particular, the theoretical models of bone tissue growth and adaptation [136][137][138] could be used to predict the effects of geometrical design on adjusting the bone tissue regeneration performance of meta-biomaterials. Moreover, more realistic mechanical loading conditions could be obtained using largescale musculoskeletal models [139][140][141][142][143] or at least simpler massspring-damper models [144][145][146][147] that describe the dynamics of the human body movement. More realistic loading conditions can further improve the predictive capability of computational models.…”

Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges

“…By decomposing EMG signals, the motor unit action potentials can be reconstructed in vivo without the need to resort to invasive techniques [119]. Lately, implantable EMG systems (iEMG) have been introduced in prosthetic control research [120][121][122] due to their ability to overcome some surface EMG (sEMG) limitations (mitigate the effects of cross talk by specific insertion to the targeted muscle and changes in limb position [122]). However, so far iMEG shows moderate clinical implementation [123].…”

“…Their chronic implementation is impeded by the small pick-up area and a limited number of MUs measured [123]. However, iEMG is currently being explored for a broad range of applications in robotic rehabilitation for clinical scenarios such as SCI, stroke, and amputation [119,[124][125][126], even though for some applications sEMG is still performing better [122]. The development of those measurement methods in combination with a variety of EMG decoding algorithms [124] led to EMG evolving into one of the most common control interfaces for assistive robotics [7] for cases where the residual muscle structure is intact.…”

Additively manufactured porous metallic biomaterials

“…Moreover, more thorough characterization of the human tissues is required to better understand the exact properties that need to be replicated by the designer biomaterials. The natural discipline to use for this purpose is biomechanics where the properties of human tissues are studied using computational [262][263][264][265][266] and experimental [267][268][269][270][271] techniques and the musculoskeletal loads are estimated using musculoskeletal models [272][273][274][275] and massspring-damper models [276][277][278][279] of the human body.…”