TOWARDS DYNAMIC CHARACTERIZTION OF FULLY 3D PRINTED CAPACITIVE SENSORS FOR FOOTBED PRESSURE SENSING APPLICATIONS

被引:0
|
作者
Gothard, Andrew T. [1 ]
Anton, Steven R. [1 ]
机构
[1] Tennessee Technol Univ, Cookeville, TN 38505 USA
关键词
3D printing; capacitive sensor; footbed pressure; GAIT ANALYSIS;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Currently, the analysis of an individual's gait and foot pressure distribution is a valuable tool in orthopedics to assist in the diagnosis and treatment of gait disorders. Thanks to the development of pressure sensing insoles, gait and foot pressure distribution analysis has become more common in research focused on human locomotion. Typically, however, insoles containing pressure sensor arrays have limited customizability or are expensive to customize. The lack of affordable, patient-specific solutions can be problematic for patients with foot deformities. Past work has been done to mitigate the lack of customizability of pressure sensing insoles through the use of 3D printing to create insoles with embedded commercial capacitive pressure sensors. The use of 3D printing to fabricate insoles gives rise to the potential to create customized insoles rapidly and at low cost. However, at present, there are no wholly developed methods for integrating fully printed embedded capacitive sensors within pressure sensing insoles. This work focuses on the development and dynamic characterization of fully 3D printed capacitive sensors using flexible thermoplastic polyurethane (TPU) filament and conductive polylactic acid (PLA) filament. Sinusoidal compressive tests are performed at 1, 3, 5, and 7 Hz for pressure levels of 25, 35, 55, and 75 N/cm(2) in order to evaluate the sensitivity of the sensor over a range of cyclic pressures typical of the . footbed environment. From the results of the experiments, the use ofa fully 3D printed capacitive sensor to track dynamic changes in pressure is shown to be feasible. Representative calibration curves calculated for each load and frequency combination show that the sensor exhibits maximum hysteresis and linearity error of 68.9% and 34.9%, respectively. Due to the significant nonlinearity and hysteresis in the sensor output, a nonlinear model must be developed to accurately characterize the dynamic behavior of the sensor.
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页数:8
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