# A Comparative Analysis of IMUs and Optical Systems in Layup Shot Biomechanics
## 3 Results
### Statistical Parametric Mapping (SPM) Analysis
This pattern was also evident in the shoulder flexion-extension, abduction-adduction and internal-external rotation angles (Figure 9), where ensemble plots showed strong alignment in trajectory trends between systems, and SPM analysis confirmed that significant condition-based differences occurred at comparable time points, with a high degree of overlap in significant clusters (\(p\) < 0.001). (2) Both systems detected comparable condition-based changes, although these occurred in different time windows (Figure 8b). The knee flexion-extension and shoulder internal-external rotation angles displayed this characteristic, as ensemble means revealed similar overall trends, but the timing of condition-specific variations differed. SPM analysis detected statistically significant differences between conditions in both systems; however,  
Figure 5: **(Top half)** a single participant example of the mean trajectories and standard deviations for the flexion-extension and external-internal ankle joint angles of the Xsens (blue line and shaded area) and Vicon (red line and shaded area) systems during the layup shot. **(Bottom half)** (**a**) The paired-samples \(t\)-test statistic SPM \(\{t\}\) shows the critical threshold of 3.391 (red dashed line) being exceeded at time \(\sim\)5-14%, with a supra-threshold cluster probability of \(p\) < 0.001 indicating a significantly more dorsiflexed angle detected by the Xsens than the Vicon system. **(b)** Supra-threshold clusters at time 0–8 and 15–20% of the ankle external-internal joint angle (\(p\) = 0.011, \(p\) = 0.013) indicated a more everted ankle joint from the Xsens system, but then, a more everted ankle joint from the Vicon system before the two waveforms displayed no significant difference across the remaining part of the task. cluster sizes and locations were misaligned, suggesting a timing offset in how each system captured condition-based changes. (3) High offsets were observed between systems, notably in the external-internal shoulder rotation, where the largest offset of 4.9\({}^{\circ}\) was recorded (Table 1). Despite this, SPM analysis demonstrated that both systems consistently identified condition-specific differences (\(p<0.001\)), though alignment of significant clusters was limited, indicating potential challenges in time synchronization. Figure 6: (**Top half**) a single participant example of the mean trajectories and standard deviations for the wrist joint angle of the Xsens (blue line and shaded area) and Vicon (red line and shaded area) systems during the layup shot. (**Bottom half**) The paired-samples \(t\)-test statistic SPM [\(t\)], indicating homogenous waveforms from the two systems, as no supra-threshold clusters exceeded the critical-\(t\) lines. Figure 7: _Cont._  
Figure 8: SPM plots of the between-condition differences as detected by the Xsens and Vicon systems for the elbow external-internal angle (**a**) and knee flexion-extension angle (**b**) during the layup task under two conditions: defended and undefended. Significant but consistent differences were detected between the conditions from the two systems, as revealed by the supra-threshold clusters exceeding critical-\(t\) value for the elbow external-internal angle in Xsens (**t*** = 3.615, \(p\) < 0.001, \(p\) = 0.041) and Vicon (**t*** = 3.617, \(p\) < 0.001, \(p\) = 0.019) appearing roughly within the same time windows (Xsens: 40–60%, 65–70% and 97–100%, Vicon: 37–57%, 65–70% and 96–100%). Consistency in the detection of change was also observed for the knee flexion-extension angle for Xsens (**t*** = 3.575, \(p\) = 0.003, \(p\) = 0.010) and Vicon (**t*** = 3.603, \(p\) = 0.036), spanning approximately 8–15% and 30–38% and 12–14% of the task, respectively.