Exploring the Modification of a Foot-Insole Pressure Sensor as a Real-Time Training Tool for Dancers

An estimated 11.1 million people participate in dance in the US alone, and it was found that 26% of consumers reported it as their chosen form of physical activity (Bronner & Worthen-Chaudhari, 1999; Statista, 2025). However, up to 90% of dancers experience serious injury at some point (Callahan & Mangum, 2025). These injuries stem from many problems, one of which is improper technique (Lei et al., 2025). Sickling, also known as supination, is a common technical error that occurs when a dancer’s foot curves inward when pointed, most commonly in demi-pointe or relevè positions (Imura et al., 2022). Supination in dancers can cause severe and repetitive strain injuries, reducing shock absorption and leading to added stress on the outer foot, ankle, and leg structures (Lowe & Chaitow, 2009; Werber, 2011). Therefore, the purpose of this study was to create a proof-of-concept model that, when programmed into the connected sensor’s Arduino, could accurately detect unsafe weight distribution in dancers and provide real-time feedback to dancers to reduce the risk of injury. This was achieved by quantifying proportions of pressure that were characterized as sickling to utilize as possible thresholds for the device. A second verification test was followed by this to test the accuracy of the quantified thresholds. The results showed that these thresholds had an accuracy of 93.33% on the left foot and 81.67% on the right foot. A chi-square goodness of fit test was conducted, revealing that the results were statistically significant on the left foot [χ²(1, 120) = 90.133, p =