CE
C.L.J. Eijck
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Dynamic Footprints
Redesigning 4D Scanning Hardware to Facilitate Natural Walking
The prescription of custom foot orthotics traditionally relies on static fitting methods, such as foam-box impressions or static 3D scanning. While these methods capture the foot's geometry in a single posture, they fail to account for the complex, dynamic deformations that occur during a human's natural gait cycle. Four-dimensional (4D) dynamic foot scanning addresses this by capturing the continuous 3D shape of the foot over time. This dynamic data has the potential to significantly improve the design and comfort of personalized footwear and orthotics.
To make this technology accessible, pioneering research at TU Delft previously developed a low-cost 4D foot scanner prototype (Vidmar, 2020; Kwa, 2021). However, an independent design evaluation of this prototype revealed critical mechanical and practical limitations that prevent routine clinical deployment. Most notably, mounting depth cameras directly onto the walkway frame left the sensors highly vulnerable to footstep-induced cadence vibrations. Furthermore, the system suffered from suboptimal sensor placement, camera resolution constraints, and a bulky, fixed structure that made it impossible to transport in a standard compact car, such as a Volkswagen Polo.
To overcome these barriers, this thesis focuses on the redesign of the 4D foot scanner to drastically enhance its technical reliability, clinical usability, and structural mobility. The proposed conceptual prototype features a modular, low-profile walkway design to improve patient accessibility and eliminate the fear of heights. To isolate the optical sensors from structural vibrations, a decoupled camera mounting system was engineered. Additionally, the bottom scanner was upgraded to Active Stereo Vision technology (Intel RealSense D405) with a shorter focal length to eliminate multipath interference from the glass plate and further lower the walkway height.
The physical dimensions of the redesign were rigorously evaluated through physical gait experiments and Virtual Reality (VR) simulation studies. The findings demonstrated that a 5-meter-long walkway is required to facilitate a truly natural gait pattern without the patient adjusting their stride, and that the combined effects of platform height and width significantly influence perceived patient discomfort.
Finally, optimal camera positioning was calculated to maximize view overlap, which successfully reduced the mean absolute scanning error from 3 mm to 2.25 mm. With a total component cost of €6.048,89, the physical prototype comfortably meets the financial requirements for low-cost clinical implementation. By solving the critical hardware and ergonomic challenges of previous iterations, this redesign provides a robust, mobile, and highly accurate foundation for the commercial adoption of 4D foot scanning in podiatry.
...
To make this technology accessible, pioneering research at TU Delft previously developed a low-cost 4D foot scanner prototype (Vidmar, 2020; Kwa, 2021). However, an independent design evaluation of this prototype revealed critical mechanical and practical limitations that prevent routine clinical deployment. Most notably, mounting depth cameras directly onto the walkway frame left the sensors highly vulnerable to footstep-induced cadence vibrations. Furthermore, the system suffered from suboptimal sensor placement, camera resolution constraints, and a bulky, fixed structure that made it impossible to transport in a standard compact car, such as a Volkswagen Polo.
To overcome these barriers, this thesis focuses on the redesign of the 4D foot scanner to drastically enhance its technical reliability, clinical usability, and structural mobility. The proposed conceptual prototype features a modular, low-profile walkway design to improve patient accessibility and eliminate the fear of heights. To isolate the optical sensors from structural vibrations, a decoupled camera mounting system was engineered. Additionally, the bottom scanner was upgraded to Active Stereo Vision technology (Intel RealSense D405) with a shorter focal length to eliminate multipath interference from the glass plate and further lower the walkway height.
The physical dimensions of the redesign were rigorously evaluated through physical gait experiments and Virtual Reality (VR) simulation studies. The findings demonstrated that a 5-meter-long walkway is required to facilitate a truly natural gait pattern without the patient adjusting their stride, and that the combined effects of platform height and width significantly influence perceived patient discomfort.
Finally, optimal camera positioning was calculated to maximize view overlap, which successfully reduced the mean absolute scanning error from 3 mm to 2.25 mm. With a total component cost of €6.048,89, the physical prototype comfortably meets the financial requirements for low-cost clinical implementation. By solving the critical hardware and ergonomic challenges of previous iterations, this redesign provides a robust, mobile, and highly accurate foundation for the commercial adoption of 4D foot scanning in podiatry.
...
The prescription of custom foot orthotics traditionally relies on static fitting methods, such as foam-box impressions or static 3D scanning. While these methods capture the foot's geometry in a single posture, they fail to account for the complex, dynamic deformations that occur during a human's natural gait cycle. Four-dimensional (4D) dynamic foot scanning addresses this by capturing the continuous 3D shape of the foot over time. This dynamic data has the potential to significantly improve the design and comfort of personalized footwear and orthotics.
To make this technology accessible, pioneering research at TU Delft previously developed a low-cost 4D foot scanner prototype (Vidmar, 2020; Kwa, 2021). However, an independent design evaluation of this prototype revealed critical mechanical and practical limitations that prevent routine clinical deployment. Most notably, mounting depth cameras directly onto the walkway frame left the sensors highly vulnerable to footstep-induced cadence vibrations. Furthermore, the system suffered from suboptimal sensor placement, camera resolution constraints, and a bulky, fixed structure that made it impossible to transport in a standard compact car, such as a Volkswagen Polo.
To overcome these barriers, this thesis focuses on the redesign of the 4D foot scanner to drastically enhance its technical reliability, clinical usability, and structural mobility. The proposed conceptual prototype features a modular, low-profile walkway design to improve patient accessibility and eliminate the fear of heights. To isolate the optical sensors from structural vibrations, a decoupled camera mounting system was engineered. Additionally, the bottom scanner was upgraded to Active Stereo Vision technology (Intel RealSense D405) with a shorter focal length to eliminate multipath interference from the glass plate and further lower the walkway height.
The physical dimensions of the redesign were rigorously evaluated through physical gait experiments and Virtual Reality (VR) simulation studies. The findings demonstrated that a 5-meter-long walkway is required to facilitate a truly natural gait pattern without the patient adjusting their stride, and that the combined effects of platform height and width significantly influence perceived patient discomfort.
Finally, optimal camera positioning was calculated to maximize view overlap, which successfully reduced the mean absolute scanning error from 3 mm to 2.25 mm. With a total component cost of €6.048,89, the physical prototype comfortably meets the financial requirements for low-cost clinical implementation. By solving the critical hardware and ergonomic challenges of previous iterations, this redesign provides a robust, mobile, and highly accurate foundation for the commercial adoption of 4D foot scanning in podiatry.
To make this technology accessible, pioneering research at TU Delft previously developed a low-cost 4D foot scanner prototype (Vidmar, 2020; Kwa, 2021). However, an independent design evaluation of this prototype revealed critical mechanical and practical limitations that prevent routine clinical deployment. Most notably, mounting depth cameras directly onto the walkway frame left the sensors highly vulnerable to footstep-induced cadence vibrations. Furthermore, the system suffered from suboptimal sensor placement, camera resolution constraints, and a bulky, fixed structure that made it impossible to transport in a standard compact car, such as a Volkswagen Polo.
To overcome these barriers, this thesis focuses on the redesign of the 4D foot scanner to drastically enhance its technical reliability, clinical usability, and structural mobility. The proposed conceptual prototype features a modular, low-profile walkway design to improve patient accessibility and eliminate the fear of heights. To isolate the optical sensors from structural vibrations, a decoupled camera mounting system was engineered. Additionally, the bottom scanner was upgraded to Active Stereo Vision technology (Intel RealSense D405) with a shorter focal length to eliminate multipath interference from the glass plate and further lower the walkway height.
The physical dimensions of the redesign were rigorously evaluated through physical gait experiments and Virtual Reality (VR) simulation studies. The findings demonstrated that a 5-meter-long walkway is required to facilitate a truly natural gait pattern without the patient adjusting their stride, and that the combined effects of platform height and width significantly influence perceived patient discomfort.
Finally, optimal camera positioning was calculated to maximize view overlap, which successfully reduced the mean absolute scanning error from 3 mm to 2.25 mm. With a total component cost of €6.048,89, the physical prototype comfortably meets the financial requirements for low-cost clinical implementation. By solving the critical hardware and ergonomic challenges of previous iterations, this redesign provides a robust, mobile, and highly accurate foundation for the commercial adoption of 4D foot scanning in podiatry.
Conference paper
(2022)
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Farzam Tajdari, Christiaan Eijck, Felix Kwa, Christiaan Versteegh, Toon Huysmans, Yu Song
Optical motion capturing explains the three-Dimensional (3D) position estimation of points through triangulation employing several depth cameras. Prosperous performance relies on level of visibility of points from different cameras and the overlap of captured meshes in-between. Generally, the accuracy of the estimation is practically based on the camera parameters e.g., location and orientations. Accordingly, the camera network configurations play a key role in the quality of the estimated mesh. This paper proposes an optimal approach for camera placement based on characteristics of a depth camera D435i - Intel RealSense. The optimal problem includes a cost function that contains several minimisation and maximisation terms. The minimisation terms are distance of the cameras to the center of the scanning object, resolution error, and sparsity. And the maximisation terms are distance between each two pair of cameras, percent of captured point from an object, and the level of overlap between cameras. The object is designed based on practical experiments of human walking and is a bounding box around one step of dynamic foot work-space from heel strike posture to toe-off posture. The accuracy and robustness of the algorithms are assessed via experiment measurement, and sensitivity to the number of cameras is investigated. Accordingly, the experiment results determined that the scanning accuracy can be as high as 2.5 % based on a reference scan with a high-end scanner (Artec Eva).
...
Optical motion capturing explains the three-Dimensional (3D) position estimation of points through triangulation employing several depth cameras. Prosperous performance relies on level of visibility of points from different cameras and the overlap of captured meshes in-between. Generally, the accuracy of the estimation is practically based on the camera parameters e.g., location and orientations. Accordingly, the camera network configurations play a key role in the quality of the estimated mesh. This paper proposes an optimal approach for camera placement based on characteristics of a depth camera D435i - Intel RealSense. The optimal problem includes a cost function that contains several minimisation and maximisation terms. The minimisation terms are distance of the cameras to the center of the scanning object, resolution error, and sparsity. And the maximisation terms are distance between each two pair of cameras, percent of captured point from an object, and the level of overlap between cameras. The object is designed based on practical experiments of human walking and is a bounding box around one step of dynamic foot work-space from heel strike posture to toe-off posture. The accuracy and robustness of the algorithms are assessed via experiment measurement, and sensitivity to the number of cameras is investigated. Accordingly, the experiment results determined that the scanning accuracy can be as high as 2.5 % based on a reference scan with a high-end scanner (Artec Eva).