**5. Discussion**

Besides the features typically extracted from sEMG signal (RMS, envelope peak, muscle activation timing, median frequency, etc.), some attempts have been recently proposed to consider sEMG- signal variability as a suitable parameter to deepen the interpretation of muscular recruitment by neuromotor system in pathophysiology [38]. Different approaches have been used to quantify this phenomenon [15,39,40]. Nevertheless, a gold standard has not been identified yet. The CV adopted in this work has been proved to be a suitable and easy-to-measure index to assess in different clinical and experimental environments [14–16]. Thus, the goal of the present study is to assess the variability of the sEMG signal acquired over ankle muscles during hemiplegic-children walking by means of CV-index computation. Tibialis anterior and gastrocnemius lateralis are chosen because a large within-cycle variability of sEMG activity in those muscles is reported during hemiplegic-children walking [4,6]. The size of sEMG variability in hemiplegic children is quantified by a direct comparison with CV-based results achieved in a population of age-matched control children and in a further population of able-bodied young adults.

Differently from able-bodied subjects, hemiplegic children are used to hitting the ground in different ways during the same walking, such as by heel, forefoot and flat foot. It has been reported that each one of these contacts would correspond to a different EMG pattern [4]. This is particularly true for those muscles mainly involved in ankle-joint movements, such as GL and TA. Thus, a certain variability of muscle activity is expected, also in mild forms of hemiplegia, such as Winters' type I and II. Results in the present group of hemiplegic children (H-group), indeed, report high (>0.70) mean CV values (±SD) for GL (0.71 ± 0.16) and for TA (0.72 ± 0.14), confirming the above-mentioned reports and previsions. This variability may likely be ascribed to the pathophysiological alternation between sub-phases of gait in which muscles are recruited and sub-phases of gait in which muscles are silent. It could be also observed that sEMG variability is comparable in GL vs. TA, since no significant difference (*p* > 0.05) was detected between mean CV values of the two muscles.

To reliably quantify sEMG variability in hemiplegic children, it is necessary to compare these findings with an age-matched control population, which is represented by C-group in the present study. Alteration of walking in mild hemiplegic children has been widely reported in the literature [2–4,6,8–10]. The classification of hemiplegia proposed by Winters is based only on these differences. Winters' type I children show smaller and less frequent dorsi-flexor recruitment of the ankle in hemiplegic leg, provoking drop foot during swing. This phenomenon is further stressed in Winters' type II, causing a persistence of equinism throughout the gait cycle, often related to a knee hyperextension during stance. This obviously reflects on myoelectric activity of GL and TA. The present study was designed to check if these acknowledged alterations are also associated with a modification of sEMG variability in hemiplegic walking. Results show a decrease of mean CV value in H-group for GL (15%, *p* < 0.05) and TA (7%, *p* > 0.05), compared to C-group (Figures 6 and 7). The CV's own definition indicates that higher values of this index correspond to a more elevated variability of the phenomenon observed. Thus, lower CVs indicate a reduction of intra-subject variability of ankle-muscle activity compared to controls, suggesting that hemiplegic children present a limited capability of adapting their muscle recruitment to the different stimuli met during the walking task, also in the mildest forms of the disease (Winters' type I and II). This consideration is supported by the statistical significance only for GL. Decrease of sEMG variability for TA, indeed, is not statistically significant. This leads to reflect on the meaning of the CV index. As mentioned above, the CV index is not computed directly on sEMG samples, but it is derived from the standard deviation of the signal (Table 1), which is by definition a direct measurement of signal variability. Consequently, it is more informative in the assessment of the differences among different populations than the typical approach based on the statistical comparison among mean values. Thus, in our opinion, the information suggested by the present study could be considered reliable, certainly for dorsi-flexor muscles such as GL, but probably also for plantar-flexor ones such as TA. Moreover, these findings pave the way to further studies which will try and figure out if different results achieved on GL and TA are due to the choice of the index or to the statistical analysis or if this is going to stress a real difference in dorsi-flexor vs. plantar-flexion behavior. A further interesting finding is that H-group presents a larger normalized (to the mean value) range of CV values for both GL (0.33–1.43) and TA (0.63–1.36), compared to C-group (0.61–1.53 for GL and 0.68–1.25 for TA), indicating an increased inter-subject variability of sEMG signals during walking. This result is in line with reported studies indicating that the disorder could a ffect di fferent patients in di fferent ways [2,4], considering also that the present H-group is composed of both Winters' type I and II children.

A previous research pointed out mean CV values higher than 0.86 for GL in an adult population [16], suggesting that older age could increase sEMG signal variability. Thus, a control group of adult subjects (A-group) was also included in the present analysis, to consider the possible influence of age on CV value. In accordance with the observation reported in [16], CV values in the A-group are significantly higher for GL compared to both C-group and H-group (1.10 ± 0.21 vs. 0.83 ± 0.19 and 0.71 ± 0.16, respectively, *p* < 0.05, Figure 6). This is true also for TA (0.85 ± 0.11 vs. 0.77 ± 0.12 and 0.72 ± 0.14, respectively, *p* < 0.05, Figure 7). Thus, an overall reduction of intra-subject variability is detected in children (hemiplegic and control), suggesting that children are used to adopting a more constant muscular recruitment during walking, with respect to adults. Physiological interpretation of this result may be ascribed to the incomplete maturation of the neuro-motor aspects of walking, acknowledged in school-age children [20]. The CV values reported here in A-group are considerably higher than those shown in [16] for adult people. This is probably due to the di fference of gait protocol between the two studies. In the present study, consecutive strides during continuous long-distance gait have been considered. It is reasonable to argue that sEMG patterns may di ffer and variability could increase, when comparing with signals acquired in single stride during short-distance walking. Moreover, it is acknowledged that a large number of samples are needed to suitably describe the phenomenon of variability of physiological signals [39]. Therefore, the reliability of the present results is strengthened by the numerous strides analyzed here, on average nearly 300 per subject, and 30,000 in total.

The present group of researchers has recently focused its attention on the variability of muscular recruitment in children by means of sEMG analysis, a field where, to our knowledge, only few attempts were carried out. To this aim, di fferent studies were produced, focusing on the assessment of sEMG variability in able-bodied subjects [14,35,36], proposing a new parameter for quantifying sEMG variability [39], looking for novel insights in the maturation of gait [14,36], trying to quantify the asymmetric behavior of muscle recruitment in hemiplegic-children walking [6] and attempting to find a predominant muscle activation pattern able to characterize the di fferent classes of children hemiplegia [8]. However, most of these studies used an advanced signal a processing technique, called statistical gait analysis (SGA), which describes human walking by averaging spatial-temporal and sEMG-based characteristics over numerous strides of the same walking trial. Despite being reliable and robust, SGA is a computationally expensive technique which produces a wide range of results. Thus, the first contribution of the present study is to propose an alternative approach for a suitable assessment of sEMG variability, based on an easy-to-compute and compact index. Table 2 shows the detailed contributions of the present work with respect to each of the abovementioned studies in tabular form. Studies are reported in chronological order. While other studies [5,8,10,11,20,41] investigated muscular recruitment of lower limbs of hemiplegic children during walking, no direct assessment of sEMG variability was reported. Thus, a further contribution of the present study consists in showing the reliability of the CV index in hemiplegic-children walking, in order to also provide information on sEMG variability, besides sEMG amplitude and timing, and all the other typical parameters. A final contribution of the study is the detection of an overall reduction of intra-subject variability of ankle-muscle activity in mild-hemiplegic children compared to controls (children and young adults), suggesting that hemiplegic children present a limited capability of adapting their muscle recruitment to the di fferent stimuli met during walking task. To our knowledge, this information is quantified here for the first time.


*Electronics* **2020**, *9*,

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**Table 2.** *Cont.*

### **6. Conclusions and Future Work**

Overall, the present findings provide evidence to support the hypothesis of a decreased intra-subject variability of surface electromyography signal of ankle muscle in hemiplegic children during walking, encouraging future studies to deepen the pathophysiological reasons and modalities associate to this phenomenon. This reduction has been detected compared to both control children and able-bodied adults. Thus, it could probably be ascribed to both young age and the specific disease. Concomitantly, an increased inter-subject variability of sEMG signals was detected during hemiplegic walking, confirming that the disorder could affect different patients in different ways. Furthermore, present findings indicate that CV is a reliable index to evaluate the variability of muscle recruitment in different experimental circumstances and with different clinical goals, such as in adult and pediatric populations, in neurological disorders and for both intra- and inter-subject studies. Including the results obtained from the different indices listed in Table 1, on the set of sEMG measurements collected from the three populations, will be an interesting aspect to investigate in a future development of this study.

It has been shown that the first foot–floor contact of each hemiplegic stride could occur in different ways (with heel, forefoot and flat foot) and that each one of these contacts would correspond to a different EMG pattern. Further research developments could be focused on computing and comparing sEMG variability associated with each one of the different foot–floor contacts, trying to identify which one is more involved in the process of variability decrease. Moreover, it is acknowledged that a single gait cycle can be split in two main gait phases, stance and swing: Stance identifies the full time when the foot is on the ground; swing quantifies the period when the same foot is in the air for limb progression. Assessing sEMG variability separately for stance and swing could be one of the future developments of the present study. Since the CV approach seems to succeed in the quantification of sEMG variability in hemiplegia, further studies could involve other populations affected by neuromuscular disorders, such as cerebrovascular accident, Parkinson's disease and multiple sclerosis.

**Author Contributions:** Conceptualization, F.D.N. and S.S.; methodology F.D.N. and S.S.; software A.S., A.P., C.P. and S.S.; investigation F.D.N. and S.S.; validation, A.S. and C.P.; resources, S.F., V.A. and M.K.; data curation, F.D.N., A.S. and C.P.; writing—original draft preparation, F.D.N. and S.S., writing—review and editing S.F., V.A., A.P. and M.K.; visualization, F.D.N. and S.S. supervision, S.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.
