## 1 Introduction  
Stroke is the leading cause of acquired long-term disability [1]. Among stroke survivors, 25% to 75% require help or are fully dependent in activities of daily living [2]. The acute phase following the event requires prompt and specialized care to minimize the impairment to both the somatosensory and motor areas. Nevertheless, the chronic phase may benefit from rehabilitation as well [3; 4; 5]. The rehabilitation after stroke is not guided by an established standard protocol; therefore, treatment programs vary in duration, intensity, and frequency [6]. A key factor in the rehabilitation process is the evaluation of the improvements gained during the therapy. The most widely used methods of assessment are clinical scales (physical/cognitive tests or self-reported questionnaires). Some of the most exploited and reliable clinical scales in stroke are the Fugl-Meyer Assessment (FMA, [7]), the Wolf Motor Function Test (WMFT, [8]), and the Motor Activity Log-30 (MAL, [9]). Despite requiring little effort, in terms of operators and time, and providing a wide range of measures, they have some limitations, including lack of sensitivity and specificity along with their operator-dependency [10]. Thus, clinical scales can be integrated with specific neurological assessments, in order to provide an even more detailed portrait of the clinical status of patients [11]. Many instrumental approaches can be employed for this purpose, including kinematics, electromyography (EMG), and brain activity analysis. Each of them investigates a different domain of the hierarchical organization of the neuro-musculoskeletal system. The effects of rehabilitation on the kinematics of the patient is usually evaluated in terms of articular range of motion, and motor control features such as movement smoothness for the upper limb, or gait biomechanics for the lower limb [12]. These kinematics parameters can be assessed by means of motion tracking systems, such as marker-based optoelectronic devices. Recent works employed kinematics for the assessment of the effects of rehabilitative therapies. [PERSON] et al. [12; 13] related kinematics parameters to clinical scales to observe correlations between the two assessments in neurological patients. The effects of robotic therapies were observed as well, in terms of smoothness, accuracy, and velocity of motor performance, suggesting the possibility of promoting neuroplasticity at both shoulder and elbow level [14]. In a recent study [15] combined constrained induced therapy and robotic therapy demonstrating therapeutic effects on proximal and distal kinematics on children. Kinematics is also used to evaluate motor control capability and smoothness, often coupled with standard clinical tests [16]. As to the quantitative assessment of the muscle activity, a valuable approach for the analysis of EMG signals is the muscle synergy framework. It relies on the hypothesis that the Central Nervous System (CNS) solves the motor control problem by exploiting a limited number of muscle modules (synergies), i.e., coordinated activation patterns of groups of muscles that share a common control signal [17]. Thus, according to this analysis, the CNS uses a limited set of spatial synergies, modulated by a signal identifying their activation level along time while performing a specific task or group of tasks [18]. According to previous studies, in mild-impaired stroke survivors, an altered recruitment pattern can be found, while synergies composition is preserved [19]. In more compromised patients, synergies appear to modify their spatial components, by splitting or merging different motor modules [20]. In a recent study [21], it was found that spatial synergies may be partially related to the patient motor functionality, in a small population of post-stroke patients. Regarding the activation of the cerebral areas deputed to movement, these can be investigated by means of several methods.