## 1 Introduction  
Muscle strength is a key determinant of current and prospective health, mobility, and independent living in aging [1, 2]. The loss in muscle function (i.e., strength, power, and endurance) is associated with increased adverse outcomes, including cardiometabolic diseases, falls, functional decline, frailty, and mortality [3]. Among the components of muscle function, muscle power, defined as the product of the force or torque of a muscular contraction and its velocity [4], seems to be the strongest predictor of functional limitations in aging [5, 6, 7]. Indeed, the tasks of real life require some amount of muscle power to guarantee independent living and to overcome gravity [8]. Moreover, muscle power declines with a faster dynamic [9] compared to strength, making it an ideal sentinel index for detecting individuals at higher risks and monitoring aging trajectory [10].  
The gold standard quantitative analysis of muscle power is typically performed in a laboratory setting with the use of instruments such as the Motion Capture System (MoCap), force platform, or isokinetic dynamometer [6]. However, the high costs and the limited accessibility of such equipment, the need for highly specialized personnel, and the complexity of the set-up make these measures not applicable on a large scale and/or in clinical settings [6, 11]. To overcome these limitations, some field methods have been developed to evaluate muscle power in a time- and cost-efficient way [5]. Among them,the 5-Sit-To-Stand test (SSTS) has been preferred over other methods (e.g., vertical leaps, long jumps, stair climb, force-velocity profiling) [12; 13; 14; 15] for testing elderly populations in clinical settings thanks to its low-risk profile and relationship with functionally relevant movements [2; 14].This test requires five sit-to-stand movements to be performed from a box of a standardized height as fast as possible. The estimation of mean concentric lower limb muscle power is performed using the formula proposed by [PERSON] et al. [6]. This formula relies on basic physics principles and on the following assumptions: (i) the duration of the concentric phase is approximated as one-tenth of the total time trial; (ii) the vertical displacement is calculated as the difference between the lower limb length (assumed to be equal to 50% of the subject's stature) and the height of the box; (iii) the force expressed during the concentric phase of standing is equal to 90% of the subject's body mass multiplied by g (9.81 m \(\times\) s\({}^{-1}\)) (for the formula and a more detailed description of the parameters, please see the Section 2.5).  
This approach has increasingly been used in clinical settings [1]. However, the assumptions on which it is based have only been partially scrutinized [16]; therefore, a verification against a fully objective, gold standard approach is lacking. Finally, the replication of the validation process of the lower limb muscle power estimates outside the laboratory settings in which the method was developed is warranted.  
By comparison with a fully automated gold standard method (motion capture system and force platform), the aim of this study was to: (1) verify the accuracy of the assumptions of [PERSON]'s method (Duration, Position, and Force); (2) verify the accuracy of the estimates of muscle power with [PERSON] method; (3) develop and validate an optimized estimation of muscle power that are based on optimized assumptions.