Subject-specific muscle activation patterns in athletic and orthopedic populations: Considerations for using surface electromyography in assistive and biofeedback device applications

This chapter presents the subject-specific nature of muscle activation patterns measured by surface electromyography (sEMG) both when elite athletes perform complicated whole-body maneuvers and when patients perform activities of daily living. Examples are provided to highlight the vast differences in muscle activation patterns across two ballet dancers, baseball pitchers (n = 16), and preoperative reverse total shoulder arthroplasty patients (n = 6). These subjectspecific muscle activations correspond to subject-specific movement mechanics and are relevant to consider while designing and testing devices that use sEMG signals as inputs. This "sample course" suggests that thresholds, normalization, and filtering of electromyography signals as inputs to assistive or biofeedback devices need to be carefully selected per individual. Recently, there have been exciting advances in machine learning (Campopiano et al., Behav. Brain Res. 347:425-435, 2018) and electromyography technology (i.e., multi-node sEMG arrays (Farina et al., J. Appl. Physiol. 117:1215-1230, 2018)) that may assist in personalizing devices, more robustly normalizing signals, and/or identifying control commands.