Optimal Sensor Placement for Estimation of Center of Plantar Pressure Based on the Improved Genetic Algorithms

Abstract

Plantar pressure analysis can be used for clinical diagnosis, exercise guidance and daily monitoring. In actual use, the CoP trajectory is an important parameter for dynamic analysis, which is generally obtained with an in-shoe system in outdoor and daily monitoring. Therefore, it is a critical issue to design the sensor placement to obtain accurate CoP estimation in a low-cost sensing insole. In this paper, a new sensor placement method, an improved genetic algorithm, was proposed, driven by a large amount of plantar pressure distribution data, with the objectives of reducing the trajectory estimation error and increasing the amount of information, and abstract the placement problem as a combinatorial optimization problem under multiple objectives. Through optimization iterations, a set of optimized sensor placements are determined and applied to practical use. Six subjects wore the optimal placement insoles and the mean absolute error was 3.81 mm (medial-lateral direction) and 8.61 mm (anterior-posterior direction) for comparison with the CoP trajectory provided by the measurement platform. Compared with previous results, the method proposed in this paper provides a more accurate CoP estimation with a 9.7% improvement. This study provides new guidelines for the selection of plantar pressure sensor placements and incorporates intelligent optimization algorithms into new ways to improve the accuracy of wearable device analysis.