**1. Introduction**

Surface electromyography (sEMG) is widely used in clinical gait analysis [1,2]: amplitude-, time-, frequency-based parameters, and conduction velocity of muscle fibers can be investigated to characterize muscle activity from sEMG [3,4]. In particular, temporal parameters, i.e., the on/off

timing of muscle activation, have become a de-facto standard for the clinical assessment of gait [5–7]. On/off timing of activation of each analyzed muscle is calculated from the raw sEMG signal through passband filtering, rectification, envelope computation, and thresholding [8–10], and used to identify the pattern of activation during the gait cycle. Then, the subject-specific pattern can be compared to that of healthy/reference populations for functional assessment [11]. Therefore, the approach used for the identification of such patterns plays a critical role in the resulting functional assessment.

In common practice, a single reference activation pattern is considered, resulting from the analysis of a limited number of strides (i.e., usually few units over a limited number of trials) acquired in laboratory conditions [11]. Recently, the statistical analysis of muscle activity over multiple decades of consecutive strides in ecological conditions highlighted that not only one, but several activation patterns can be identified with different statistical occurrence in the same walking trial, usually one prevalent pattern accompanied by few less frequent, but still statistically significant ones [4,12–16]. Studies performed on healthy adults [4,13,16] found for the rectus femoris a pattern of three activations per gait cycle (i.e., at the beginning of gait cycle, around foot-off, and in the terminal swing) in 53% of total strides, of two activations (i.e., as the previous but lacking activation around foot-off) in 26%, and of two (or three) small activations only around stance-to-swing transition in 17% [13].The identification of this variable behavior is crucial for characterizing motor function and control strategies in healthy subjects, and even more to better understand the modifications occurring in pathological conditions. Therefore, the statistical approach has also been applied in preliminary studies analyzing the muscle activation pattern of pathologic gait; in hemiplegic children, for instance, a reduced frequency in the activation of the tibialis anterior (TA) during terminal swing and a lack of activity of the same muscle at heel-strike compared to healthy controls were identified [17].

Besides the promising preliminary results, and the potential of a better insight in motor control mechanisms provided by the application of a statistical approach for the analysis of sEMG [18,19], some methodological aspects of its implementation still need to be better investigated, especially as referred to the analysis of pathological gait, where changes in the activation pattern can be related to other kinematic and/or kinetic modifications. Gait asymmetry [20,21], for instance, can appear in certain pathological conditions, and can significantly affect the implementation of a statistical approach for the analysis of sEMG, differentiating or not the specific behavior of muscles in the two limbs. Although it is relevant, a specific indication regarding how to take gait symmetry into account is still missing.

Among motor disorders that influence gait performance, Parkinson's Disease (PD) is one of the most investigated in clinical research [22–29]. Usually, authors assess muscle activation during gait of PD patients with amplitude-based parameters [23,24], focusing mainly on distal muscles of the lower limbs, i.e., gastrocnemius (GA) and TA [25–29]. Few recent studies analyzed the on/off timing of these muscles within the gait cycle without identifying a representative activation pattern in PD patients. Cioni et al. [25] observed the absence or extreme reduction in TA activations in early stance or during the early and late swing phases, while Dietz et al. [28] found well preserved timing in the activations of the GA and TA comparable to healthy reference values, and some other authors [27,29] observed the co-activation of the two antagonist muscles (i.e., overlapping periods of on/off timings): Ferrarin et al. [27] reported maintained reciprocity between antagonist muscles, while Dietz et al. [28] observed larger co-activations during the support phase in PD compared to the healthy elderly. These contradictory results can depend on differences in the analyzed PD populations, including different pharmacological treatments and severity of the pathology, but the most important limitation can be identified in the limited number of analyzed strides, preventing the actual identification of significant patterns. Given the intrinsic variability of the muscle activation pattern identified in healthy subjects [10,13], the application of a statistical approach over multiple decades of strides can help to properly take intra-subject variability into account and provide more reliable assessment [30,31] also in pathological gait [17,32].

The aim of the present study was to apply a statistical approach to the analysis of sEMG to identify gastrocnemius medialis (GM) and TA activation patterns in the gait of PD patients, taking potential stride asymmetries into account. More specifically, using data acquired during a 6-min walking test, first, temporal gait symmetry was verified, then occurrence of the di fferent activation patterns, in terms of number and timing within each stride per muscle, and the co-activation of antagonist muscles were quantified.

### **2. Materials and Methods**
