Does digital device software lead to exclusion? Investigating a portable metabolic analysis system and the input of sex data on physiological parameters.

Abstract

Background: Digital health devices have enhanced healthcare accessibility, but their design may unintentionally exclude gender diverse people. This study examines whether the input of binary sex data in a portable metabolic analysis system (COSMED K5) impacts the accuracy of physiological measurements during self-paced exercise.

Methods: Twenty adult participants (10 females, 10 males) completed two identical self-paced walking and running protocols with sex data alternately input as female or male in the device software. Key metabolic and pulmonary variables, including VO₂, VCO₂, ventilation, respiratory exchange ratio (RER), respiratory rate, and energy expenditure, were measured. Statistical comparisons evaluated differences between conditions.

Results: No differences were observed in any measured variables between the female and male conditions during walking or running (p > 0.05). Correlations between conditions were strong (r = 0.73-0.98).

Conclusion: The COSMED K5 device does not utilize binary sex input to alter physiological outputs, confirming that these data remain unaffected by this demographic variable. However, the limitation of binary sex options in the device software represents a barrier to inclusivity for gender diverse people. Device manufacturers are encouraged to update software with more inclusive options, aligning with recommendations for equitable research practices and addressing existing knowledge gaps in sport and exercise science.