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Figure 7. Experimental data 3 days. Below is a data used for verification. tion operation was carried out 4 times a day for

Figure 7 Experimental data 3 days. Below is a data used for verification. tion operation was carried out 4 times a day for

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Figure 1. P-EMG plus type sensors are less expensive to run.
Figure 1. P-EMG plus type sensors are less expensive to run.
Figure 2. Dry type sensor
Figure 2. Dry type sensor
Figure 3. CNN network structure 2.4.2 Regression analysis Regression analysis is a kind of analysis in statistics. Methods of regression analysis are divided linear analysis and nonlinear analysis. In this paper, we used linear analysis. Linear analysis is a model that predicts the value of objective variables from the explanatory vari- ables. We used a least squares method to pre- dict values. Single regression analysis uses an explanatory variable, and multiple regression analysis uses two or more explanatory vari- ables. In this paper, we used multiple regres- sion analysis. Classification used all of the measured data converted to power spectral val- ues. However, regression analysis used data
Figure 3. CNN network structure 2.4.2 Regression analysis Regression analysis is a kind of analysis in statistics. Methods of regression analysis are divided linear analysis and nonlinear analysis. In this paper, we used linear analysis. Linear analysis is a model that predicts the value of objective variables from the explanatory vari- ables. We used a least squares method to pre- dict values. Single regression analysis uses an explanatory variable, and multiple regression analysis uses two or more explanatory vari- ables. In this paper, we used multiple regres- sion analysis. Classification used all of the measured data converted to power spectral val- ues. However, regression analysis used data
Figure 4. Experimental design
Figure 4. Experimental design
Table 1. Results obtained by Support Vector Machine (SVM)
Table 1. Results obtained by Support Vector Machine (SVM)
Figure 9. Cross validation At first, we describe the result obtained by SVM. Below is how to use data for Cross vali- dation.
Figure 9. Cross validation At first, we describe the result obtained by SVM. Below is how to use data for Cross vali- dation.
Figure 6. Hand grip
Figure 6. Hand grip
Figure 5. Discrimination operation
Figure 5. Discrimination operation
Figure 8. Criteria for quantitative evaluation 3.2 Result
Figure 8. Criteria for quantitative evaluation 3.2 Result
Table 3. Results obtained by Regression analysis 4 CONSIDERATION In this paper, we verified two ways based on classification and regression analysis.
Table 3. Results obtained by Regression analysis 4 CONSIDERATION In this paper, we verified two ways based on classification and regression analysis.
Table 2. Results obtained by Convolutional Neural Net- work (CNN) 3.2.2 Regression analysis
Table 2. Results obtained by Convolutional Neural Net- work (CNN) 3.2.2 Regression analysis
Table 4. Total result From the above table, as a result, regression analysis obtained better accuracy than classifi- cation. Classification average resulted in low accuracy less than 35%, but regression anal- ysis average obtained more than 37% accu- racy. From these results, it is suggested that regression analysis is more useful for this pa- per. It is considered that the reason is that class classification learns and identifies dis- crete values, while regression analysis largely uses continuous values for learning discrimina- tion. Furthermore, result of regression analysis suggested that the state of muscle fatigue had some correlation with the state of decreasing number of muscle trainings.
Table 4. Total result From the above table, as a result, regression analysis obtained better accuracy than classifi- cation. Classification average resulted in low accuracy less than 35%, but regression anal- ysis average obtained more than 37% accu- racy. From these results, it is suggested that regression analysis is more useful for this pa- per. It is considered that the reason is that class classification learns and identifies dis- crete values, while regression analysis largely uses continuous values for learning discrimina- tion. Furthermore, result of regression analysis suggested that the state of muscle fatigue had some correlation with the state of decreasing number of muscle trainings.
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multiclass classification
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