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Electromyography-Based Quantitative Representation Method for Upper-Limb Elbow Joint Angle in Sagittal Plane.

Pang M, Guo S, Huang Q, Ishihara H, Hirata H - J Med Biol Eng (2015)

Bottom Line: The results were calculated in real-time and used as control reference to drive an exoskeleton device bilaterally.The experimental results indicate that the proposed method can provide suitable prediction results with root-mean-square (RMS) errors of below 10° in continuous motion and RMS errors of below 10° in stepping motion with 20° and 30° increments.It is also easier to calibrate and implement.

View Article: PubMed Central - PubMed

Affiliation: Graduate School of Engineering, Kagawa University, Takamatsu, 761-0396 Japan.

ABSTRACT

This paper presents a quantitative representation method for the upper-limb elbow joint angle using only electromyography (EMG) signals for continuous elbow joint voluntary flexion and extension in the sagittal plane. The dynamics relation between the musculotendon force exerted by the biceps brachii muscle and the elbow joint angle is developed for a modified musculoskeletal model. Based on the dynamics model, a quadratic-like quantitative relationship between EMG signals and the elbow joint angle is built using a Hill-type-based muscular model. Furthermore, a state switching model is designed to stabilize the transition of EMG signals between different muscle contraction motions during the whole movement. To evaluate the efficiency of the method, ten subjects performed continuous experiments during a 4-day period and five of them performed a subsequent consecutive stepping test. The results were calculated in real-time and used as control reference to drive an exoskeleton device bilaterally. The experimental results indicate that the proposed method can provide suitable prediction results with root-mean-square (RMS) errors of below 10° in continuous motion and RMS errors of below 10° in stepping motion with 20° and 30° increments. It is also easier to calibrate and implement.

No MeSH data available.


Related in: MedlinePlus

Side view of proposed muscular skeleton model in vertical plane
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Fig2: Side view of proposed muscular skeleton model in vertical plane

Mentions: A side view (in the sagittal plane) of the proposed musculoskeletal model is shown in Fig. 2. The distance between the attachment point of the tendon to the skeleton and elbow joint is l. According to a previous study [24], the tendon in the upper arm can be regarded as having high stiffness and thus the tendon deformation is zero. The deformation of the muscle–tendon that results in elbow rotation can thus be regarded as resulting only from muscle contraction. The elbow angle θ is the one to be predicted. L is the distance between the forearm centroid and the elbow joint. In the sagittal plane, it can be considered that the biceps muscle contracts to pull the forearm against the force of gravity during the motion of elbow flexion and extension and that the triceps muscle remains almost unactivated. No obvious EMG signal changes from the triceps muscle can be observed during elbow flexion and extension in the sagittal plane. In the transverse plane, the triceps has to pull the forearm to extend the elbow. As only voluntary motion in the sagittal plane is discussed, the effect from triceps brachii is ignored in this paper.Fig. 2


Electromyography-Based Quantitative Representation Method for Upper-Limb Elbow Joint Angle in Sagittal Plane.

Pang M, Guo S, Huang Q, Ishihara H, Hirata H - J Med Biol Eng (2015)

Side view of proposed muscular skeleton model in vertical plane
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4414936&req=5

Fig2: Side view of proposed muscular skeleton model in vertical plane
Mentions: A side view (in the sagittal plane) of the proposed musculoskeletal model is shown in Fig. 2. The distance between the attachment point of the tendon to the skeleton and elbow joint is l. According to a previous study [24], the tendon in the upper arm can be regarded as having high stiffness and thus the tendon deformation is zero. The deformation of the muscle–tendon that results in elbow rotation can thus be regarded as resulting only from muscle contraction. The elbow angle θ is the one to be predicted. L is the distance between the forearm centroid and the elbow joint. In the sagittal plane, it can be considered that the biceps muscle contracts to pull the forearm against the force of gravity during the motion of elbow flexion and extension and that the triceps muscle remains almost unactivated. No obvious EMG signal changes from the triceps muscle can be observed during elbow flexion and extension in the sagittal plane. In the transverse plane, the triceps has to pull the forearm to extend the elbow. As only voluntary motion in the sagittal plane is discussed, the effect from triceps brachii is ignored in this paper.Fig. 2

Bottom Line: The results were calculated in real-time and used as control reference to drive an exoskeleton device bilaterally.The experimental results indicate that the proposed method can provide suitable prediction results with root-mean-square (RMS) errors of below 10° in continuous motion and RMS errors of below 10° in stepping motion with 20° and 30° increments.It is also easier to calibrate and implement.

View Article: PubMed Central - PubMed

Affiliation: Graduate School of Engineering, Kagawa University, Takamatsu, 761-0396 Japan.

ABSTRACT

This paper presents a quantitative representation method for the upper-limb elbow joint angle using only electromyography (EMG) signals for continuous elbow joint voluntary flexion and extension in the sagittal plane. The dynamics relation between the musculotendon force exerted by the biceps brachii muscle and the elbow joint angle is developed for a modified musculoskeletal model. Based on the dynamics model, a quadratic-like quantitative relationship between EMG signals and the elbow joint angle is built using a Hill-type-based muscular model. Furthermore, a state switching model is designed to stabilize the transition of EMG signals between different muscle contraction motions during the whole movement. To evaluate the efficiency of the method, ten subjects performed continuous experiments during a 4-day period and five of them performed a subsequent consecutive stepping test. The results were calculated in real-time and used as control reference to drive an exoskeleton device bilaterally. The experimental results indicate that the proposed method can provide suitable prediction results with root-mean-square (RMS) errors of below 10° in continuous motion and RMS errors of below 10° in stepping motion with 20° and 30° increments. It is also easier to calibrate and implement.

No MeSH data available.


Related in: MedlinePlus