## 4 Discussion
In low-load configurations (Yellow, Blue, and Red), HandyGym tends to underestimate generated power, while in high-load configurations (BlueWP and RedWP), the device significantly overestimates power (Table 3). This pattern highlights a limitation in HandyGym's ability to provide accurate power measurements across the load spectrum, especially in high-resistance conditions, where overestimations could lead to misinterpretations of user performance. This is crucial in professional practice, where incremental load protocols are often used to determine the load that elicits peak concentric power [23; 54]. If relying solely on the integrated encoder, one might mistakenly conclude that the load eliciting the highest concentric power was the highest moment of inertia (RedWP), whereas the reference system shows it was a low-intermediate load (Blue). The power results from the reference system align more closely with previous studies using similar moments of inertia in flywheel squats with trained subjects [43; 44]. In some loading conditions, power bias is negative, while in others, it is positive, resulting in a small average bias in the pooled data. However, the correlation for power measurements is lower than for force (0.6), and the TEE is very large (1.32). The high random error, combined with varying bias dynamics across load conditions, makes it challenging to compare data from different loading configurations, especially between those using a load-multiplying pulley and those without. Notably, the Red condition presents the lowest bias, although TEE values remain large. Conversely, despite a very large positive bias in high-load conditions (BlueWP and RedWP), the random error (TEE) was moderate and lower than in other load conditions. Therefore, while power values differ significantly from the reference system, evaluating the trend of exercise series in load-multiplying pulley conditions (BlueWP and RedWP) is more accurate than in non-pulley conditions, provided corrections are applied using a regression equation (Figure 4) [48]. We did not observe a clear pattern in measurement validity between phases. However, in the eccentric phase (Table 3), a very large TEE and small correlation were observed, indicating low measurement accuracy. This may not be evident when analyzing each load condition separately but could be due to an E/C ratio of less than 1 (Table 1), as different submaximal braking techniques during the eccentric phase, with varying peak joint angular velocities of the knee, trunk, and hip, may affect the mechanical impulse required to stop the flywheel within the range of motion, increasing technique variability (i.e., progressive or delayed braking) [27; 44]. Additionally, during the concentric phase, the rope tension is generally constant, while during braking, slack in the rope can cause execution velocity (a key parameter for calculating power) to decouple from the rotational speed of the axis, where the rotary encoder is located [25]. Moreover, a tight initial rope setting may facilitate smoother transitions between eccentric and concentric phases at higher inertia, but it can hinder fluid transitions at lower inertia and higher velocities [29]. The presence of significant bias in both force and power measurements, whether negative or positive, raises questions about HandyGym's applicability in contexts where measurement accuracy is critical, such as elite athlete performance monitoring, rehabilitation protocols, scientific research, or power testing with progressive loads [27]. Although the device generally shows a strong correlation with a well-established reference system,the observed underestimations and overestimations may limit its practical utility. HandyGym consistently provides lower force values than the reference system across various loading conditions, with a very large correlation in the pooled data.