# Three-Dimensional Assessment of Upper Limb Proprioception via a Wearable Exoskeleton
## 3 Results  
Multi-Joint Condition Leads to a Decrease of Proprioceptive Acuity Resulting in an Underestimation of the Matching Target  
All participants were able to perform the experiments involving the two conditions and the multiple target sets. However, performance was significantly different when considering the DoFs and the testing modality. In detail, Figure 2 illustrates the comparison between the two conditions (SJ versus MJ) for both the Error Bias (A) and the Matching Error (B): two main different behaviours were found between the SJ and MJ tests. All subjects showed a tendency to overshoot the Proprioceptive Target when requested to perform the matching task in SJ condition with the elbow FE\({}_{\text{Elbow}}\). Contrarily, the same joint (FE\({}_{\text{Elbow}}\)) undershot when the MJ condition was presented for both left and right arms. Furthermore, a significant deterioration of proprioceptive acuity was also inferred in multiarticular complex movements (MJ) rather than in single joint (SJ): this was true only for the distal joint of the arm FE\({}_{\text{Elbow}}\), while the proximal anatomical district AA/FE shoulder, provided similar results independently on the testing modality (SJ vs. MJ). The aforementioned differences were confirmed by rANOVA test, highlighting a significant condition (SJ vs. MJ) effect (\"condition\": Error Bias: \(F\)(1,18) = 33.5, \(p\) < 0.001; Matching Error: \(F\)(1,18) = 30.5, \(p\) < 0.001). Ultimately, we statistically inferred across the two conditions, by a paired \(t\)-test post-hoc analysis, different behaviour of each tested DoF, and it has been found that only FE\({}_{\text{Elbow}}\) DoF presents statistically significant differences (see Tables 1 and 2). Contrarily the other tested limb's joint, the shoulder, maintains statistically similar performance independently on the condition. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Body Side**} & \multirow{2}{*}{**Condition**} & \multicolumn{4}{c}{**Error Bias**} & \multicolumn{2}{c}{**Matching Error**} \\ \cline{3-8}  & & **FE\({}_{\text{Elbow}}\)** & **FE\({}_{\text{Shoulder}}\)** & **AA\({}_{\text{Shoulder}}\)** & **FE\({}_{\text{Elbow}}\)** & **FE\({}_{\text{Shoulder}}\)** & **AA\({}_{\text{Shoulder}}\)** \\ \hline Right & SJ & & & & & \\  & MJ & 0.002 * & 0.029 & 0.825 & \textless{0.001 *} & 0.379 & 0.335 \\ \hline Left & SJ & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Statistical \(p\)-values for the Error Bias and Matching Error between conditions. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Body Side**} & \multirow{2}{*}{**DoF**} & \multicolumn{2}{c}{**Error Bias**} & \multicolumn{2}{c}{**Matching Error**} \\ \cline{3-8}  & & **SJ** & **MJ** & **SJ** & **MJ** \\ \hline \multirow{4}{*}{Right} & FE\({}_{\text{Elbow}}\) & 3.97 \(\pm\) 2.75 & \(-\)16.89 \(\pm\) 6.26 & 13.24 \(\pm\) 0.93 & 26.80 \(\pm\) 2.49 \\  & FE\({}_{\text{Shoulder}}\) & 0.37 \(\pm\) 1.31 & 3.54 \(\pm\) 1.42 & 6.12 \(\pm\) 0.66 & 6.95 \(\pm\) 3.12 \\  & AA\({}_{\text{Shoulder}}\) & 7.53 \(\pm\) 1.82 & 7.13 \(\pm\) 2.28 & 11.21 \(\pm\) 1.03 & 12.10 \(\pm\) 1.40 \\  & FE\({}_{\text{Elbow}}\) & 8.21\(\pm\) 2.67 & \(-\)21.96 \(\pm\) 4.67 & 14.01 \(\pm\) 1.29 & 26.64 \(\pm\) 3.59 \\ Left & FE\({}_{\text{Shoulder}}\) & \(-\)0.47 \(\pm\) 1.29 & 2.31 \(\pm\) 1.91 & 6.04 \(\pm\) 0.66 & 8.08 \(\pm\) 0.87 \\  & AA\({}_{\text{Shoulder}}\) & 8.73 \(\pm\) 2.32 & \(-\)3.76 \(\pm\) 3.26 & 12.94 \(\pm\) 1.43 & 15.56 \(\pm\) 1.63 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Mean values and standard errors (%) for the Error Bias and Matching Error. Figure 2: Outcome measures relative to the Error Bias and the Matching Error. In each graph, the orange color represents the left body side, while the green color represents the right one. The single-joint condition (SJ), which could be: AA\({}_{\text{Shoulder}}\) or FE\({}_{\text{Shoulder}}\) or FE\({}_{\text{Elbow}}\)) is represented by a round marker, while a triangular marker represents the multi-joint condition (MJ).