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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

One set of experimental results of simplified musculotendon prediction results obtained using only EMG. The solid blue line is the simplified prediction results and the green dashed line is the prediction results with EMG and MTx sensor
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Fig5: One set of experimental results of simplified musculotendon prediction results obtained using only EMG. The solid blue line is the simplified prediction results and the green dashed line is the prediction results with EMG and MTx sensor

Mentions: To evaluate the proposed musculoskeletal model, all recorded data from the ten subjects during the 4 days were fitted using the curve fitting tools of MATLAB with quadratic polynomial equations. The inputs were values of the muscle activation level during the flexion motion and the outputs were values of cos2θ. Some bad data caused by electrodes sliding on the skin surface were ignored. Figure 5 shows one set of model evaluation results from the ten subjects. The dashed lines are the results calculated with data recorded from EMG electrodes (to get the muscle activation level) and from the MTx sensor (to get elbow joint angles). The solid lines are prediction results based on the proposed model. Table 1 lists detailed information (mean ± SD). The experimental results show that the average values of the correlation coefficient is above 0.97 for all ten subjects. Although a linear relationship between muscle activation level and cos2θ was found for some subjects (in Fig. 5, subjects B and F have correlation coefficients of 0.95 and 0.94, respectively), the quadratic-like relationship has a higher correlation coefficient (with correlation coefficients of 0.97 and 0.98) than that of the linear one in the same case. In other cases (in Fig. 5, subjects I and J), the quadratic-like relationship is more suitable (linear relationship has correlation coefficients of 0.86 and 0.85 and quadratic-like one has 0.97 and 0.98).Fig. 5


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)

One set of experimental results of simplified musculotendon prediction results obtained using only EMG. The solid blue line is the simplified prediction results and the green dashed line is the prediction results with EMG and MTx sensor
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig5: One set of experimental results of simplified musculotendon prediction results obtained using only EMG. The solid blue line is the simplified prediction results and the green dashed line is the prediction results with EMG and MTx sensor
Mentions: To evaluate the proposed musculoskeletal model, all recorded data from the ten subjects during the 4 days were fitted using the curve fitting tools of MATLAB with quadratic polynomial equations. The inputs were values of the muscle activation level during the flexion motion and the outputs were values of cos2θ. Some bad data caused by electrodes sliding on the skin surface were ignored. Figure 5 shows one set of model evaluation results from the ten subjects. The dashed lines are the results calculated with data recorded from EMG electrodes (to get the muscle activation level) and from the MTx sensor (to get elbow joint angles). The solid lines are prediction results based on the proposed model. Table 1 lists detailed information (mean ± SD). The experimental results show that the average values of the correlation coefficient is above 0.97 for all ten subjects. Although a linear relationship between muscle activation level and cos2θ was found for some subjects (in Fig. 5, subjects B and F have correlation coefficients of 0.95 and 0.94, respectively), the quadratic-like relationship has a higher correlation coefficient (with correlation coefficients of 0.97 and 0.98) than that of the linear one in the same case. In other cases (in Fig. 5, subjects I and J), the quadratic-like relationship is more suitable (linear relationship has correlation coefficients of 0.86 and 0.85 and quadratic-like one has 0.97 and 0.98).Fig. 5

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