## 1 Introduction  
According to the World Health Organization, falling is one of major health challenges of old age, raising extensive discussions among gerontologists and physical therapists [1]. [PERSON] et al. [2] noted that about one-third of adults aged 65 years and 50% of adults older than 80 falls at least once a year, and 6% of such falls cause fractures. Falling among older adults can lead to severe consequences such as hip and wrist fractures, permanent disability, fear of falling, reduced quality of life, and even death [3, 4]. The economic burden of falling among older adults is considerable, with annual direct medical costs about 5754 million for the fatal falls, and about $50 billion is related to non-fatal fall [5]. However,researchers suggested that two-third of falls in older persons can be prevented [6]. To prevent falling among the elderly, identifying the biomechanical differences in gait patterns between fallers and non-fallers can be helpful. More specifically, the identification of lower extremity joints coupling and its variability during gait in fallers compared to non-fallers can help to develop rehabilitation exercises to reduce these differences and decrease the probability of falling induced injuries. Gait disorder is the main reason for falls among older adults and not only it can occur during normal aging, but it can be due to neurological brain diseases or cervical spine and biomechanical diseases [7; 8]. More than 70% of falls in older adults take place during gait [9]. For a normal gait, many systems are required, such as sensation and coordination, lower limb and core muscle strength, balance, and function in an integrated fashion [10; 11]. A decrease in gait speed with an increase in age can be viewed as an adaptation to compensate for declining sensory-motor function in order to prevent the occurrence of falls. Biomechanical researchers have examined the spatiotemporal gait parameters and their variability among older adults as predictors of the risk of falling, as well as for differentiating between fallers and non-fallers [12; 13]. Researchers suggested that the temporal variability and mean spatial parameters of gait have the highest efficacy in predicting the fall risk in clinical measurements [14; 15], and that fallers walk with a considerably more irregular gait rhythm (shorter steps) than non-fallers [16]. Furthermore, increased variability of walking speed for defined and self-selected walking speeds and increased step width variability for fast walking speeds in fallers have been reported [12]. However, previous studies used linear measures of variability such as coefficient of variation in spatiotemporal gait parameters. Since the human movement is dynamic, the use of non-linear dynamic measures, such as coordination variability (CoordV), can provide additional insights into the interaction between two joints or segments [17; 18; 19; 20]. Coordination can be viewed as a process in which movements components are sequentially organized over time, producing a functional and synergistic movement pattern [21; 22]. The coordination between body segments and joints is coded in a subtle way to accommodate variations imposed by different task demands. Coordination patterns provide information about both the timing and the magnitude of movements, and they represent the organization of multiple degrees of freedom into a simple control strategy [23; 24; 25; 26]. The CoordV measure quantifies the variety of movement patterns that an individual uses during a task and can provide a measure of the flexibility/adaptability of the individual's motor system [22; 27]. A reduction in the CoordV measure could place older adults at a high risk of falling, because a decreased variety of movement patterns could limit the solutions to perturbations, e.g., obstacles or tripping [28]. As such, a greater variability in knee-ankle inter-joint coordination during the stance phase of gait in fallers than in non-fallers has been reported [29].