ANALYSIS OF LOCOMOTION DYNAMICS WHEN USING AN EXTERNAL WALKER DEVICE

Human gait analysis is widely used for the assessment of mobility and functional status, particularly in older adults and clinical populations. Wearable inertial measurement units (IMUs) offer a promising solution for gait monitoring outside laboratory environments; however, their accuracy during assisted walking and in real-world conditions remains partially unclear. In addition, the reliability of sensorized walking aids for assessing gait performance has not yet been fully established. This study focuses on the assessment of spatio-temporal gait estimation during both unassisted and walker-assisted walking using wearable and reference sensing systems. A stereophotogrammetric motion capture system was employed as ground truth for gait event detection and parameter derivation. Within this framework, three IMU-based approaches, relying on sensors placed on the foot, shank, and sacrum, were systematically compared across walking conditions. Furthermore, a sensorized walker was analysed to explore its ability to characterize assisted gait. Results showed that walker-assisted walking is associated with a slower and more cautious gait pattern, characterized by reduced cadence, shorter step and stride length, and increased stance and double support times. IMU-based algorithms provided accurate estimates of temporal gait parameters in both conditions, while spatial parameters were more affected by walking condition, with larger errors observed during slow and assisted walking. In addition, significant correlations were found between walker-derived metrics and gait parameters, particularly for measures related to movement intensity and smoothness. The findings suggest that IMU-based systems are reliable for monitoring temporal gait characteristics in both free and assisted walking, while spatial estimation remains more challenging. Moreover, sensorized walking aids may provide meaningful information about gait quality, offering a potential alternative for simplified and non-invasive gait monitoring in clinical settings.