# A Novel Wearable Foot and Ankle Monitoring System for the Assessment of Gait Biomechanics
## 2 Materials and Methods
### Correlation of the Plantar Pressure with Muscular Activity  
In this work, gait assessment is twofold. On one hand we performed the assessment of the plantar pressure along the COP progression line. On the other hand, we performed EMG assessment of the tibialis anterior and the gastrocnemius via the extracted features. The target of this paper is to correlate the FSR readings with the lower-limb EMG in order to perform gait assessment. Indeed, physiological gait assumes a very clear correlation of the plantar pressures with the lower-limb muscles. As such, we are able to assess physiological gait based on FSR and EMG correlation for the heel strike and toe-off phases. The time-domain plots in Figure 13 illustrates the clear interdependency of the FSR\({}_{5}\) and tibialis anterior EMG signals for heel strike, as well as the interdependency of the FSR\({}_{0}\) and gastrocnemius EMG signals respectively for toe-off. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Title 1** & **MAV** & **ZC** & **SSC** & **RMS** \\ \hline Walking & 0.1–0.2 & 5–10 & 10–20 & 0.1–0.3 \\ Running & 0.2–0.4 & 10–30 & 10–20 & 0.2–0.5 \\ Jumping & 0.5–1 & 10–20 & 15–25 & 0.3–0.6 \\ Rest & \textless{}0.1 & \textgreater{}15 & \textgreater{}25 & \textless{}0.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: EMG feature range for the discrimination of walking from rest [44]. As illustrated in Figure 13a for heel strike, a direct dependency can be formulated between the plantar pressure executed on \(\text{FSR}_{5}\) and muscular activity of the tibialis anterior. Similarly, as illustrated in Figure 13b for toe-off, a direct dependency can be formulated between the plantar pressure executed on \(\text{FSR}_{0}\) and muscular activity of the gastrocnemius. However, it should be noticed that gastrocnemius activation and \(\text{FSR}_{0}\) activation exhibit a certain delay for toe-off, rather than simultaneity which is the case for \(\text{FSR}_{5}\) and tibialis anterior at heel strike. As such, this delay must be accounted for when correlating \(\text{FSR}_{0}\) with the EMG of the gastrocnemius. The procedure followed to correlate FSR activation with muscular activity is performed as follows. Both FSR readings and the muscular activity have been binarized. The FSR signal was binarized by comparison to a threshold level, determined empirically in laboratory environment during extensive testing of the pressure sensors deployed onto the shoe insole. Muscular activity on the other hand was determined from the SSC-indicating the onset of movement, and the MAV-indicating muscular intensity. The EMG features were binarized by comparison to a threshold level, determined for the MAV and  
Figure 12: The lower-limb electromyogram (EMG) of a walking segment with the corresponding extracted features. Figure 13: Time-domain plots of the force sensor resistors (FSR) and EMG signals illustrating a clear interdependency during the gait phases: (**a**) \(\text{FSR}_{3}\) and tibialis anterior at heel strike, (**b**) \(\text{FSR}_{0}\) and gastrocnemius at toe-off. SSC as follows. The MAV threshold value was considered 0.05, that is half of the lower limit of the feature variation range in Table 4. The SSC threshold was considered 25, that is half of the lower limit of the feature variation range in Table 4 added to the upper limit. Additionally, considering that muscular activity is accounted for by low SSC values, SSC binarization is complementary, i.e., binarized SSC is logical 1 provided the SSC is lower than the threshold. Then, muscular activity was determined as the logical AND functional between the binarized EMG features. Finally, correlation of the FSR reading with the EMG is evaluated as the cross-correlation of the binarized FSR signal and muscular activity respectively, expressed as  
\[R_{FSR,EMG}(m)=\left\{ \begin{array}{c}\sum\limits_{n=0}^{n-m+1}FSR(n+m)\cdot EMG (n),\ m\geq 0\\ \begin{array}{c}R_{EMG,FSR}(-m),\ m<0\end{array}\end{array} \right., \tag{6}\]  
where \(m\) is the cross-correlation function index [52].