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. 2021 Jun 28;21(13):4437.
doi: 10.3390/s21134437.

Optical-Based Foot Plantar Pressure Measurement System for Potential Application in Human Postural Control Measurement and Person Identification

Tanapon Keatsamarn  1 , Sarinporn Visitsattapongse  1 , Hisayuki Aoyama  2 , Chuchart Pintavirooj  1
Affiliations

Optical-Based Foot Plantar Pressure Measurement System for Potential Application in Human Postural Control Measurement and Person Identification

Tanapon Keatsamarn et al. Sensors (Basel). .

Abstract

Plantar pressure, the pressure exerted between the sole and the supporting surface, has great potentialities in various research fields, including footwear design, biometrics, gait analysis and the assessment of patients with diabetes. This research designs an optical-based foot plantar pressure measurement system aimed for human postural control and person identification. The proposed system consists of digital cameras installed underneath an acrylic plate covered by glossy white paper and mounted with LED strips along the side of the plate. When the light is emitted from the LED stripes, it deflects the digital cameras due to the pressure exerted between the glossy white paper and the acrylic plate. In this way, the cameras generate color-coded plantar pressure images of the subject standing on the acrylic-top platform. Our proposed system performs personal identification and postural control by extracting static and dynamic features from the generated plantar pressure images. Plantar pressure images were collected from 90 individuals (40 males, 50 females) to develop and evaluate the proposed system. In posture balance evaluation, we propose the use of a posture balance index that contains both magnitude and directional information about human posture balance control. For person identification, the experimental results show that our proposed system can achieve promising results, showing an area under the receiver operating characteristic (ROC) curve of 0.98515 (98.515%), an equal error rate (EER) of 5.8687%, and efficiency of 98.515%.

Keywords: biometrics; foot pressure; gait analysis; human postural balance.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The designed optical-based plantar pressure measurement platform.
Figure 2
Figure 2
The four images captured from four cameras, which are denoted as UL, UR, LL, and LR.
Figure 3
Figure 3
Weighted function for the smoothing of the transition region.
Figure 4
Figure 4
(a) A set of known weights and the associated computed forces and pressures; (b) plot of average intensity and pressure.
Figure 5
Figure 5
Series of captured images of gaiting foot plantar pressure acquisition. The left side is the plantar pressure when the subject starts to step onto the platform. The middle is the plantar pressure when the subject completely steps on. The right side is the plantar pressure when the subject steps away from the platform.
Figure 6
Figure 6
(a) COP trajectory is plotted superimposed with a foot pressure image. (b) COP trajectory is plotted in the 2D coordinate axis.
Figure 7
Figure 7
Trajectory of the COP of three subjects. (a) Trajectory of subject with weakest human posture balance; (b) trajectory of subject with medium human posture balance; (c) trajectory of subject with strongest human posture balance.
Figure 8
Figure 8
Ellipsoidal fit of COP trajectory labeled with posture balance index of two subjects.
Figure 9
Figure 9
Posture balance index of a subject under the influence of alcohol (blue) compared with a normal subject (red).
Figure 10
Figure 10
Normal foot with arch index of 0.23. Solid line is the principal axis of a normal foot. Dashed line divides the principal axis into equal distances. The ratio of the middle portion to the total foot area defines the arch index.
Figure 11
Figure 11
Flat foot with arch index of 0.31.
Figure 12
Figure 12
High arch foot with arch index of 0.16.
Figure 13
Figure 13
Graph of pressure variation over a period of time for two subjects (a,b) (left and right graph). Two acquisitions per subject (upper and lower graph).
Figure 14
Figure 14
Illustration of the static (a) and dynamic feature (b). In (a), blue vectors are the two-principal axis, the red is the ellipsoidal fit; in (b), step angle (III–IV) is the angle between the principal axes of the left and the right foot. Step width (I–II) is defined to be the distance between each step of the subject.
Figure 15
Figure 15
Distribution of genuine and imposter matching score. Genuine distribution is shown in blue whereas imposter distribution is shown in red. The intersection of genuine distribution and imposter distribution is the equal error rate (ERR).
Figure 16
Figure 16
ROC curves showing area under the ROC curve of 0.98396.
See this image and copyright information in PMC

References

    1. Guoand Y., Lanmei W. Recent advance in plantar pressure measurement system. Sens. Transducers. 2012;145:96–105.
    1. Racic V., Pavic A., Brownjohn J.M.W. Modern facilities for experimental measurement of dynamic loads induced by humans: A literature review. Shock Vib. 2013;20:53–67. doi: 10.1155/2013/975956. - DOI
    1. Wafai L., Zayegh A., Woulfe J., Aziz S.M., Begg R. Identification of foot pathologies based on plantar pressure asymmetry. Sensors. 2015;15:20392–20408. doi: 10.3390/s150820392. - DOI - PMC - PubMed
    1. Hernandez M.E., Snider J., Stevenson C., Cauwenberghs G., Poizner H. A Correlation-Based Framework for Evaluating Postural Control Stochastic Dynamics. IEEE Trans. Neural Syst. Rehabil. Eng. 2016;24:551–561. doi: 10.1109/TNSRE.2015.2436344. - DOI - PMC - PubMed
    1. Ma R., Hu F. An Intelligent Thermal Sensing System for Automatic, Quantitative Assessment of Motion Training in Lower-Limb Rehabilitation. IEEE Trans. Syst. ManCybern. Syst. 2018;48:661–669. doi: 10.1109/TSMC.2016.2636660. - DOI