## 1 Introduction  
Postural control (PC) is a complex system involving continuous and dynamic interactions between the sensorimotor system and environmental stimuli [1]. It underpins two key components: postural stability, the capacity to maintain the centre of mass (COM) within the base of support, and postural orientation, which ensures appropriate alignment between body segments and the environment with respect to gravity for optimal task performance [2; 3]. Together, these mechanisms form the basis of an individual's control, enabling the maintenance, achievement, or restoration of postural stability across various postures, activities, and functional tasks [4; 5]. This ability, which strictly relies on the recruitment of postural adjustments, enables the selective managing of degrees of freedom involved in voluntary movement [6] and is intrinsically linked to feedforward mechanisms. These mechanisms play a pivotal role in preparing the body for movement and ensuring stability [7; 8]. Early postural adjustments (EPAs), which occur between 600 to \(-450\) ms before self-initiated movements, activate postural muscles to stabilize the body irrespective of disturbance direction [9; 10]. Closer to movement onset, anticipatory postural adjustments (APAs), occurring within \(-150\) ms to \(+50\) ms, generate forces to counteract destabilizing effects to ensure movement safety and efficiency [9; 11]. In addition to their functional importance, these mechanisms exhibit complexity and variability, highlighting the adaptability of the sensorimotor system to maintain postural stability and responding to environmental challenges [12; 13]. Dysfunction in these feedforward mechanisms has well-documented repercussions on PC, particularly in conditions such as stroke [14; 15; 16; 17]. PC dysfunction is among the most common consequences of stroke [17; 18; 19], significantly impairing functional tasks like gait or sit-to-stand [20; 21]. This, in turn, compromises independence, reduces activity levels, and increases the risk of falls [18; 22; 23]. Addressing these challenges is crucial for effective rehabilitation, emphasizing the need for precise assessment tools that can capture the complexities of PC dynamics. Traditional available approaches to understanding PC biomechanical parameters often emphasize linear measures [22; 24; 25; 26; 27]. While valuable, these measures fail to account the temporal dynamics, complexity, and adaptability required for real-life functional tasks [28; 29]. This limitation arises from the reliance of conventional methods on averaging the CoP over time, overlooking its dynamic properties, which could provide more detailed insights into post-stroke postural stability control [30; 31]. From a non-linear perspective, a system's dynamic variability is seen as a marker of adaptability, contrasting with linear approaches that often interpret variability as error (26). Analyzing the complexity and variability of these adjustments offers a deeper understanding of the complexity, stability, and adaptability of this dynamic system [32; 33]. Therefore, it is crucial to understanding how the body dynamically stabilizes itself across different temporal scales, particularly in the context of functional tasks [30]. These approaches enable researchers to investigate how biological systems maintain stability across multiple temporal scales, uncovering the intricate mechanisms underlying PC [34]. One of the key challenges in studying PC is effectively linking its various components [3]. Addressing this complexity requires approaches capable of capturing the non-linear and stochastic behaviours of the PC system [19; 20; 35]. Despite their potential, non-linear analyses remain underutilized in the study of PC in functional tasks, particularly in individuals with post-stroke impairments. A recent scoping review revealed that, to date, research has predominantly focused on upper limb (UL) tasks, focused on isolated components of task execution, such as muscular strength, muscle activity, or range of motion [36].