<![CDATA[This study evaluates the accuracy of height estimation on a sensor-based smart wheelchair system, focusing on user posture and mobility variables. Precise height measurement is crucial in medical applications, particularly for pharmacological dose determination and nutritional status evaluation, where non-standard posture or user movement poses a high risk of causing data bias. Testing was conducted using the Chumlea method as a validation standard for the ultrasonic sensors integrated into the wheelchair. The experiment involved four specific conditions: normal/static, non-normal/static, normal/dynamic, and non-normal/dynamic postures, involving 20 subjects (10 men, 10 women). Data analysis utilized Mean Absolute Error (MAE) and ANOVA tests to assess the significance of accuracy differences between conditions. The results indicate that testing conditions significantly affect height estimation accuracy. In the normal/static condition, the average MAE was 0.65 cm for men and 1.12 cm for women. In contrast, in the non-normal/dynamic condition, MAE increased sharply to 2.93 cm for men and 2.88 cm for women, indicating a significant decrease in accuracy. The ANOVA statistical test confirmed a significant difference (p < 0.001) in sensor accuracy among the different testing conditions . These findings conclude that non-ideal posture and dynamic mobility simultaneously exacerbate sensor inaccuracies. This research contributes to the development of smart wheelchair technology by providing insights into how external factors influence sensor performance for more accurate medical decision-making.]]>
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