BackgroundMagnetic resonance imaging (MRI) is commonly used to diagnosing and monitoring the progress of brain tumours.However, it is costly, not easily accessible, and requires frequent visits to specialised health centres. Method: This study explores the use of passively assessed gait initiation signal data (GISD) as a potential alternative to MRI. We evaluated three hypotheses: (1) Certain features extracted from GISD are more sensitive in identifying brain tumours; (2) Changes in GISD patterns are correlated with brain tumour progression; and (3) The locations of brain tumours are correlated with GISD features. Data from healthy individualsin the UK Biobank (N=240 x 7 days) were used to establish a baseline for signal analysis. Then, we assessed the sensitivity of 28 features extracted from GISD to differentiate this healthy population and brain tumours patients (BrainWear project, N=49 x 9 months). Results: Statistical tests revealed significant differences (p < 0.05) in subsets of GISD-extracted features between healthy individuals and cancer patients. Classification models achieved a maximum accuracy of 77 % in distinguishing between these two groups. However, the identification of tumour location was less accurate (33 % − 65 %), particularly for certain regions (e.g., right temporal). We also found evidence of correlation between GISD patterns and tumours progression and treatments. Conclusions: Passive GISD analysis shows promise as a complementary tool to MRI in diagnosing brain tumours. However, our small patient cohort and limited evaluation period highlight the need for larger studies to generalise these findings and derive more reliable clinical implications.