# Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)?
## 2 Materials and Methods
### Data Processing  
The data recording and processing approach used in this study was the same as the one described in our recently published paper on rectus femoris EMG clustering [10].  
All subjects walked barefoot at a self-selected speed along a lane 15 m in length during data acquisition. Kinematics and kinetics were recorded using a twelve-camera 3D motion analysis system (VICON, Oxford Metrics Limited, Yarrton, UK) operating at 120 Hz and using three force plates (Kistler Instruments Co., Vienna, Austria), respectively. The skin-mounted markers were applied according to the protocol of [PERSON] et al. [25], and the plug-in-gait model was chosen to calculate the kinematics, kinetics, and spatiotemporal parameters of participants' gait. Subsequently, the parameters were determined for at least seven strides.  
The EMG data were recorded from seven major lower-extremity muscles: rectus femoris, vastus lateralis, tibialis anterior, semimembranosus, biceps femoris, lateral gastrocnemius, and the lateralis anterior. The muscles were recorded using a 120 Hz and  
nemius, and soleus, on both right and left legs, using myon 320 (Myon AG, Schwarzenberg, Switzerland). Bipolar surface adhesive electrodes (Blue Sensor, Ambu Inc., Glen Burnie, MD, USA) were placed on the targeted muscles, following the guidelines provided by SENIAM [26]. The distance between the electrodes was set at 2 cm [27]. To amplify the EMG signal, the Biovision EMG apparatus (Biovision Inc., Wehrheim, Germany) was utilized before 2013/2014 and via Delsys (Delsys Inc., Natick, MA, USA) after 2013/14, with a preamplification factor of \(\times\)5000.  
The raw EMG data were then band-pass filtered (Butterworth filter with a cutoff frequency of 20-350 Hz), rectified, and the signal smoothed (Butterworth low-pass filter with a cutoff frequency of 9 Hz), amplitude-normalized to the mean of signal, time-normalized within one gait cycle (101 datapoints), and eventually averaged across valid strides in Matlab (2018b, The MathWorks, Inc., Natick, MA, USA) [5]. The calculated envelopes were used for subsequent analysis.  
To quantify the extent of deviation in a patient's EMG envelopes and gait parameters relative to a reference group, we calculated the norm-distance (ND) according to [5]. ND was defined as the absolute difference between a muscle's EMG envelope at the i_th data point belonging to the patient \(p\) (\(F_{pi}\)) and the mean value of the corresponding data point within that muscle for the reference group (\(\overline{F}_{ni}\)), divided by the respective standard deviation within the reference group (\(SD_{ni}\)), as expressed in Equation (1). The ND values for all 101 data points were averaged over a gait cycle for further analysis. Changes in the average ND (\(\overline{ND}\)) from the initial examination (E1) to the subsequent examination (E2) were regarded as indicative of the surgery's impact on the patient's EMG. A reduction in \(\overline{ND}\) following the intervention suggested an improvement towards a pattern more similar to the reference group.  
\[\text{NDi}=\frac{\left|\text{F}_{\text{pi}}-\overline{\text{F}}_{\text{ni}} \right|}{\text{SD}_{\text{ni}}} \tag{1}\]  
The same procedure was also employed to assess gait patterns in sagittal plane, including angles, moments, and power at the hip, knee, and ankle joints.