Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke: An EMG-Driven Model of Elbow Joint

Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke: An EMG-Driven Model of Elbow Joint

Hujing Hu (First Affiliated Hospital, Sun Yat-sen University, China & Guangdong Provincial Work Injury Rehabilitation Center, China) and Le Li (First Affiliated Hospital, Sun Yat-sen University, China)
DOI: 10.4018/978-1-4666-6090-8.ch007


Neuromusculoskeletal modeling provides insights into the muscular system which are not always obtained through experiment or observation alone. One of the major challenges in neuromusculoskeletal modeling is to accurately estimate the musculotendon parameters on a subject-specific basis. The latest medical imaging techniques such as ultrasound for the estimation of musculotendon parameters would provide an alternative method to obtain the muscle architecture parameters noninvasively. In this chapter, the feasibility of using ultrasonography to measure the musculotendon parameters of elbow muscles is validated. These parameters help to build a subject-specific EMG-driven model, which could predict the individual muscle force and elbow voluntary movement trajectory using the input of EMG signal without any trajectory fitting procedure involved. The results demonstrate the feasibility of using EMG-driven neuromusculoskeletal modeling with ultrasound-measured data for prediction of voluntary elbow movement for both unimpaired subjects and persons after stroke.
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Stroke: A Public Disease

The term ‘stroke’, or cerebro-vascular accident, refers to the neurological symptoms and signs, usually focal and acute, which result from diseases involving blood vessels. Stroke occurs when the blood supply to a part of the brain is cut off, and the brain cells in that part cannot function. Hemiparesis, partial weakness of the contralateral side of the body because of an injury to one side of the brain, commonly occurs after the onset of stroke. Strokes are either occlusive (due to occlusion of a blood vessel supplying the brain) or hemorraghic (due to bleeding from a vessel). On average, occlusive strokes account for about 80% and hemorrhagic strokes for about 20% of all strokes (Westcott, 2000). There is a large population of humans that suffer from stroke. Stroke is one of the leading medical problems, mostly in elderly subjects (Popovic & Sinkjaer, 2000). In the U.S, there are approximately 730,000 new cases each year and an estimated 4 million survivors (Carr, 2003).

Therefore, there is a need to help stroke survivors to evaluate the disabilities and to regain their independence through rehabilitation as much as possible and, in addition, to reduce the burden of care on institutions and families.

Rationale and Scope of the Study

Cerebrovascular accident, or stroke, can cause significant impairment of neural or motor functions in survivors. Subsequent to these impairments, morphological changes in the architecture of the paretic muscles often occur, which affect the muscles’ functions. Previous studies have revealed a reduction in muscle volume, a shortening of muscle fiber, and a reduction in the number of motor units in the paretic muscles in people after stroke (Halar et al., 1978; Becher et al., 1998; Metoki et al., 2003). These muscle deformations are highly related to syndromes of paretic muscles, such as muscle weakness, spasticity, contracture, etc (Patten et al., 2004; McCrea et al., 2002; Chae et al., 2002). Evaluating muscle structural variations in people after stroke is clinically important for both diagnosis and rehabilitation treatment.

Stroke rehabilitation often includes muscle strengthening, resistance training, constrained-induced therapy and robotic-assisted therapy. These are applied to counteract the muscle changes and the affected functions after stroke (Dean & Shepherd, 1997; Lum et al., 2004; Fasoli et al., 2003). In order to evaluate muscle impairment after stroke and the efficiency of different stroke rehabilitation programs, kinematics analysis and clinical scales have been used to evaluate neuromuscular changes and functional outcomes after interventions (Ju et al., 2002). Often, kinematics evaluations have focused on the results of motor execution (Yeh et al., 2004), while the clinical experiences of the examiners usually determined how clinical scales such as the Modified Ashworth Scale (MAS) were used (Pizzi et al., 2005; Bohannon & Smith, 1987). However, these evaluations do not reveal the specific changes at the level of muscle structure. Studies on skeletal muscle have shown that the moment across the joint generated by the associated muscle is highly related to the muscle’s architectural parameters, such as the cross-sectional area, moment arm and the muscle’s force–length behaviour (Huijing & Baan, 1992; Naici, 1999). Therefore, a technique that can measure these muscle architectural changes after the onset of stroke may help to evaluate the functional improvement of the affected muscle after an intervention program, and to enhance the understanding of the mechanism underlying the rehabilitation treatment.

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