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Foot modeling and smart plantar pressure reconstruction from three sensors.

Ghaida HA, Mottet S, Goujon JM - Open Biomed Eng J (2014)

Bottom Line: In a second part, we show that just 3 discrete pressure sensors per foot are enough to generate real time plantar pressure cartographies in the standing position or during walking.Finally, the generated cartographies are compared with pressure cartographies issued from the F-SCAN system.The results show 0.01 daN (2% of full scale) average error, in the standing position.

View Article: PubMed Central - PubMed

Affiliation: CNRS-Foton, UMR 6082, Lannion, France.

ABSTRACT
In order to monitor pressure under feet, this study presents a biomechanical model of the human foot. The main elements of the foot that induce the plantar pressure distribution are described. Then the link between the forces applied at the ankle and the distribution of the plantar pressure is established. Assumptions are made by defining the concepts of a 3D internal foot shape, which can be extracted from the plantar pressure measurements, and a uniform elastic medium, which describes the soft tissues behaviour. In a second part, we show that just 3 discrete pressure sensors per foot are enough to generate real time plantar pressure cartographies in the standing position or during walking. Finally, the generated cartographies are compared with pressure cartographies issued from the F-SCAN system. The results show 0.01 daN (2% of full scale) average error, in the standing position.

No MeSH data available.


Related in: MedlinePlus

Approximation of a multi exponential problem using a single exponential function.
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Figure 9: Approximation of a multi exponential problem using a single exponential function.

Mentions: In this case, we show in Fig. (9) that a single exponential satisfies the description of a multilayer system for the domain of pressure between 0.15 and 1 daN/pixel, which corresponds to the pressure of greater numerical weight in the linear regression method. It is impossible to determine the zero value of the functions, which implies that the compression can be defined with an additive constant. For example, Fig. (9) shows the summation, in circular forms, of two 5 mm layers with respective stiffness of 0.1 daN/pixel and 0.4 daN/pixel. The continuous black curve is the fitting exponential of the sum for a thickness of 7.6 mm and a stiffness of 0.25 daN/pixel.


Foot modeling and smart plantar pressure reconstruction from three sensors.

Ghaida HA, Mottet S, Goujon JM - Open Biomed Eng J (2014)

Approximation of a multi exponential problem using a single exponential function.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4231377&req=5

Figure 9: Approximation of a multi exponential problem using a single exponential function.
Mentions: In this case, we show in Fig. (9) that a single exponential satisfies the description of a multilayer system for the domain of pressure between 0.15 and 1 daN/pixel, which corresponds to the pressure of greater numerical weight in the linear regression method. It is impossible to determine the zero value of the functions, which implies that the compression can be defined with an additive constant. For example, Fig. (9) shows the summation, in circular forms, of two 5 mm layers with respective stiffness of 0.1 daN/pixel and 0.4 daN/pixel. The continuous black curve is the fitting exponential of the sum for a thickness of 7.6 mm and a stiffness of 0.25 daN/pixel.

Bottom Line: In a second part, we show that just 3 discrete pressure sensors per foot are enough to generate real time plantar pressure cartographies in the standing position or during walking.Finally, the generated cartographies are compared with pressure cartographies issued from the F-SCAN system.The results show 0.01 daN (2% of full scale) average error, in the standing position.

View Article: PubMed Central - PubMed

Affiliation: CNRS-Foton, UMR 6082, Lannion, France.

ABSTRACT
In order to monitor pressure under feet, this study presents a biomechanical model of the human foot. The main elements of the foot that induce the plantar pressure distribution are described. Then the link between the forces applied at the ankle and the distribution of the plantar pressure is established. Assumptions are made by defining the concepts of a 3D internal foot shape, which can be extracted from the plantar pressure measurements, and a uniform elastic medium, which describes the soft tissues behaviour. In a second part, we show that just 3 discrete pressure sensors per foot are enough to generate real time plantar pressure cartographies in the standing position or during walking. Finally, the generated cartographies are compared with pressure cartographies issued from the F-SCAN system. The results show 0.01 daN (2% of full scale) average error, in the standing position.

No MeSH data available.


Related in: MedlinePlus