title: An EMG-driven musculoskeletal model of the shoulder.
abstract: This paper aims to develop an EMG-driven model of the shoulder that can consider possible muscle co-contractions. A musculoskeletal shoulder model (the original model) is modified such that measured EMGs can be used as model-inputs (the EMG-driven model). The model is validated by using the in-vivo measured glenohumeral-joint reaction forces (GH-JRFs). Three patients carrying instrumented hemi-arthroplasty were asked to perform arm abduction and forward-flexion up to maximum possible elevation, during which motion data, EMG, and in-vivo GH-JRF were measured. The measured EMGs were normalized and together with analyzed motions served as model inputs to estimate the GH-JRF. All possible combinations of input EMGs ranging from a single signal to all EMG signals together were tested. The 'best solution' was defined as the combination of EMGs which yielded the closest match between the model and the experiments. Two types of inconsistencies between the original model and the measurements were observed including a general GH-JRF underestimation and a GH-JRF drop above 90° elevation. Both inconsistencies appeared to be related to co-contraction since inclusion of EMGs could significantly (p<.05) improve the predicted GH-JRF (up to 45%). The developed model has shown the potential to successfully take the existent muscle co-contractions of patients into account.
authors.affiliation: Department of Biomechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands. a.asadinikooyan@tudelft.nl
authors.forename: A A
authors.initials: AA
authors.lastname: Nikooyan
authors.forename: H E J
authors.initials: HE
authors.lastname: Veeger
authors.forename: P
authors.initials: P
authors.lastname: Westerhoff
authors.forename: B
authors.initials: B
authors.lastname: Bolsterlee
authors.forename: F
authors.initials: F
authors.lastname: Graichen
authors.forename: G
authors.initials: G
authors.lastname: Bergmann
authors.forename: F C T
authors.initials: FC
authors.lastname: van der Helm
mesh_terms: D000368:Aged; D004576:Electromyography / Q000295:instrumentation*; D005260:Female; D006801:Humans; D007537:Isometric Contraction / Q000502:physiology; D007595:Joint Prosthesis; D008297:Male; D008953:Models, Anatomic; D009043:Motor Activity / Q000502:physiology; D018482:Muscle, Skeletal / Q000503:physiopathology*; D016571:Neural Networks, Computer; D010003:Osteoarthritis / Q000503:physiopathology / Q000601:surgery; D011183:Postoperative Complications / Q000503:physiopathology; D016059:Range of Motion, Articular / Q000502:physiology; D012016:Reference Values; D012782:Shoulder / Q000503:physiopathology*; D012785:Shoulder Joint / Q000503:physiopathology* / Q000601:surgery*; D012815:Signal Processing, Computer-Assisted; D016474:Weight-Bearing / Q000502:physiology