## 3 Results
### Statistical Analysis  
An analysis of variance (ANOVA) was implemented using the _Systat 12_ package software in Sigmaplot 12. A five-way ANOVA on the 480 group means (averaged data for each factorial combination) was performed for a Cartesian Analysis Plan \(\mathbf{S_{3}\times H_{2}\times E_{2}\times M_{4}\times G_{2}}\)  
comparing the average data of five participants (random factor \(\mathbf{P_{5}}\)) from the three sensors recorded from the two hands across two eye, four music, and two grip conditions. The results from this analysis are shown in Tables 1 and 2 here below. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{3}{c}{**Cartesian Analysis Plan \(\mathbf{S_{3}\times H_{2}\times E_{2}\times M_{4}\times G_{2}}\)**} \\ \hline Factor/Interaction & _df_ & F & \(p\) \\ \hline Sensor (\(\mathbf{S_{3}}\)) & 2/479 & 119.73 & \textless{}0.001 \\ \hline Hand (\(\mathbf{H_{2}}\)) & 1/479 & 41.66 & \textless{}0.01 \\ \hline Grip (\(\mathbf{G_{2}}\)) & 1/479 & 10.34 & \textless{}0.01 \\ \hline Music (\(\mathbf{M_{4}}\)) & 3/479 & 3.71 & \textless{}0.05 \\ \hline Sensor \(\times\) Hand (\(\mathbf{S_{3}\times H_{2}}\)) & 2/479 & 55.39 & \textless{}0.01 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Results of the five-way ANOVA in terms of F values signalling significant effects of factors or interaction thereof, degrees of freedom (_df_) associated with the metric, and probability limits (_p_). The five-way ANOVA signals statistically significant effects of sensor position, hand, eye condition, music, and grip style, and a statistically significant interaction between sensor position (S\({}_{3}\)) and hand (H\({}_{2}\)). Given this interaction, _post-hoc_ tests using the Holm-Sidak method were performed to determine which of the differences between means (_d_) for factor level combinations S\({}_{3}\)\(\times\) H\({}_{2}\) were statistically significant. The results of these Holm-Sidak tests are shown in Table 3 here below. In the next step, the average data were plotted graphically, with error bars, to show the direction and magnitude (effect size) of the different effects and interactions. These plots are displayed in Figure 7. They show the direction of significant interactions between the factor levels of the sensor (S\({}_{3}\)) and hand (H\({}_{2}\)) factors (Figure 7, top left), where sensor M3 on the middle phalanx of the ring finger produced significantly stronger grip strength signals in the dominant hand, while sensors M1 and M2 on the middle phalanges of index and middle fingers displayed no significant difference between the dominant and non-dominant hands. Sensor M3 produced the strongest signals, sensor M1 the weakest in the dominant, sensor M2 the weakest in the non-dominant hand (Figure 7, middle left). Significantly stronger grip signals were generated in the dynamic grip condition (Figure 7, top right), and with both eyes shut (blindfolded condition) (Figure 7, bottom). No significant interaction between the grip style and the hand, eyes, or music factors were observed. The \"rock\" condition produced, as might have been expected, the strongest grip signals, the \"classic\" music condition the weakest grip on average (Figure 7, middle right). To disentangle which of the differences between means (_d_) are, indeed, statistically significant across the four different levels of the music factor, further post-hoc tests using the Holm-Sidak method were performed. The results of these tests are shown in Table 4 here below. The Holm-Sidak analysis on the differences between the different levels of the