## 3 Representative Samples and Kansei Words Selection
### Classification of Sound Design Elements  
By dividing sound design elements into five items (including A-weighted sound pressure level, loudness, sharpness, roughness, and tonality), this research constructed linear and non-linear correlation models between sound elements and Kansei words through QTTI and artificial neural networks. A-weighted sound pressure level [26], for which the symbol is \(L_{A}\), in dB mainly reflects the effect of frequency on the perception of loudness of sound. The sound pressure level can be derived from the effective values of the sound pressure (\(pe\)). A-weighted sound pressure level is a more accurate representation of the impact of loudness at different frequencies [27], as shown in Equation (1), and this research introduces the IEC 61672-1 [28] standard as the calculation model, as shown in Equation (2). The formula \(n\) is the total number of octave bands; \(L_{pi}\) and \(\Delta A_{i}\) are the weighted correction values for the sound pressure level in the \(i\)-th octave band. \(A_{1000}\) are normalization constants, in decibels, representing the electrical gain needed to provide frequency weightings of zero decibels at 1 kHz [28], \(A_{1000}=-2.000\) dB. \[L_{A}=10\lg\sum_{i=1}^{n}10^{0.1(L_{pi}+\Delta A_{i})}. \tag{1}\]  
\[A(f)=20\lg\left[\frac{f_{4}^{2}f^{4}}{(f^{2}+f_{1}^{2})(f^{2}+f_{2}^{2})^{ \frac{1}{2}}(f^{2}+f_{3}^{2})^{\frac{1}{2}}(f^{2}+f_{4}^{2})}\right]-A_{1000} \tag{2}\]  
Loudness [29], for which the symbol is \(N\), in some is used to reflect the user's perception of volume level, and, in this research, electric shaver loudness affects the user's perception of power strength. It is usually calculated using the method of deriving loudness (\(N\)) based on the specific loudness (\(N\)) [30], where the specific loudness reflects the regional distribution of loudness in the frequency band in someG/Bark. The specific loudness can be calculated from the excitation (\(E\)), as shown in Equation (3) [27]. \(N^{\prime}\) in the formula stands for the critical band specific loudness, \(z\) stands for the corresponding critical band (pure tone frequency as the central frequency of the noise frequency within a certain band width), \(E_{QT}\) stands for the absolute listening value under the excitation, and \(E_{0}\) stands for the benchmark sound intensity under the excitation, for which the integration of the specific loudness in the Bark domain can be obtained by the total loudness (\(N\)). \[\left\{\begin{array}{l}N^{\prime}=0.08\big{\{}\frac{F_{QT}}{E_{0}}\big{\}} \par\par\par\par\par\par\par\par\par\par\par\par\par\par\  
20 Hz, the fluctuation characteristics are shown, and above 20 Hz the roughness characteristics are shown. When the roughness is larger, it conveys fluctuation and complex feelings, and vice versa, it conveys stable feelings, as the electric shaver sounds are above 20 Hz; thus, this research did not consider fluctuation due to its unsuitability. The traditional roughness calculation method was proposed by [PERSON] and optimized by [PERSON] and [PERSON] [36], as shown in Equation (5). The formula \(f_{mod}\) denotes the modulation frequency, \(\Delta L_{E}(z)\) denotes the excitation level difference calculation model in the characteristic frequency band, and \(N^{\prime}_{max}\) and \(N^{\prime}_{min}\) denote the maximum and minimum values of the specific loudness, respectively. \[\left\{ \begin{array}{l}R=0.3f_{mod}\int_{0}^{24 Bark}\Delta L_{E}(z)dz\;\;\; \text{{\em Asper}}\\ \Delta L_{E}(z)=2 log_{10}\left\{\frac{N^{\prime}\text{max}(z)}{N^{\prime}\text {min}(z)}\right\}\end{array} \right. \tag{5}\]  
In this research, the roughness procedure of the software ArtemiS 13.6 (version 13.6.22143.02, HEAD Acoustics Company, Herzogenrath, Germany) was used, as shown in Figure 6 (data from HEAD acoustics company), and the results were calculated based on loudness rather than sound pressure alone and, therefore, were more appropriate to human ear perception [37].