Flexible Sensors for Pressure Therapy: Effect of Substrate Curvature and Stiffness on Sensor Performance

Flexible pressure sensors are increasingly being used in medical and non-medical applications, and particularly in innovative health monitoring. Their efficacy in medical applications such as compression therapy depends on the accuracy and repeatability of their output, which in turn depend on factors such as sensor type, shape, pressure range, and conformability of the sensor to the body surface. Numerous researchers have examined the effects of sensor type and shape, but little information is available on the effect of human body parameters such as support surfaces’ curvature and the stiffness of soft tissues on pressure sensing performance. We investigated the effects of body parameters on the performance of pressure sensors using a custom-made human-leg-like test setup. Pressure sensing parameters such as accuracy, drift and repeatability were determined in both static (eight hours continuous pressure) and dynamic (10 cycles of pressure application of 30 s duration) testing conditions. The testing was performed with a focus on compression therapy application for venous leg ulcer treatments, and was conducted in a low-pressure range of 20–70 mmHg. Commercially available sensors manufactured by Peratech and Sensitronics were used under various loading conditions to determine the influence of stiffness and curvature. Flat rigid, flat soft silicone and three cylindrical silicone surfaces of radii of curvature of 3.5 cm, 5.5 cm and 6.5 cm were used as substrates under the sensors. The Peratech sensor averaged 94% accuracy for both static and dynamic measurements on all substrates; the Sensitronics sensor averaged 88% accuracy. The Peratech sensor displayed moderate variations and the Sensitronics sensor large variations in output pressure readings depending on the underlying test surface, both of which were reduced markedly by individual pressure calibration for surface type. Sensor choice and need for calibration to surface type are important considerations for their application in healthcare monitoring.