A portable skin deformation measurement platform for user-specific wearable interface design (U-WEAR)
Lead Research Organisation:
Imperial College London
Department Name: Bioengineering
Abstract
Human skin stretches and compresses during movements. Knowing the skin deformation as a function of limb kinematics is strictly necessary for the large-scale deployment of wearable systems, such as textiles with embedded electrodes or sockets for prostheses. However, predicting these skin deformations accurately is currently not possible. U-WEAR ("A portable skin deformation measurement platform for user-specific wearable interface design") aims to develop a user-specific measurement platform to inform the design of biomechanically seamless interfaces with the skin that become a natural extension of the wearer. The project has been developed as an extension to the research conducted under the ERC Synergy Grant Natural BionicS that aims to control and sense soft-robotic prosthetic limbs. Crucial for prostheses to truly become a natural extension of the wearer is the interface between the wearer and the bionic system, i.e. the prosthetic socket. The design of this interface is critical for the acceptability and efficacy of bionic limbs. U-WEAR will address this gap in prosthetics, as well as in several other wearable robots such as soft exoskeletons, by developing an affordable, fast and accurate motion capture-based platform with machine-learning-based dynamics modelling, enabling physics/mathematics analyses of skin deformation during movement. U-WEAR will provide a subject-specific quantitative understanding of skin biomechanics, and how limb surface and volume change during limb movements. The successful realisation of this framework will open opportunities in applications ranging from wearable robots to skin flaps planning in reconstructive surgery, and clothing and footwear. The developed technology will be translated into a market product by a spin-off company which will progressively, in three stages, address the markets of the scientific research community and of large corporates.
Organisations
| Description | State-of-the-art research that aims to understand movement of the human body is restricted by sparse information from the very few sensors or markers that are applied on the body. This limits the quantity and quality of information that can be obtained to just broad movement of the limbs. However, for the design of individual-specific assistive technologies or wearables, whether it be in prosthetics and orthotics or any other product or technology interfacing with the body, there is a need to capture a high-density of information. Capturing the body's surface shape, especially, how surface shape changes with limb movements and even other physiological function such as muscle activity or even breathing would allow optimal design of body-interfacing products and services. To this end, we have developed a motion-capture platform that comprises of a compression-fit garment with a high-density of unique markers that can be easily identified by camera-based computer algorithms. These markers are not rigid but deform along with the body and by capturing the shape of every marker and how the shape changes, together the entire surface (such as a body surface) is measured. This would allow for the automatic designing of products that are currently very difficult to design with traditional CAD and 3D modelling products. |
| Exploitation Route | We are actively working on building on this technology. Currently, we are extending the developed technology which was originally built to work with a multi-camera static rig to work with a handheld scanning platform. We are also aiming to generalise it to capture full-body scans from a large number of individuals. |
| Sectors | Aerospace Defence and Marine Creative Economy Digital/Communication/Information Technologies (including Software) Education Healthcare Manufacturing including Industrial Biotechology |
| Description | Our findings validated our hypothesis to realise a 4D scanning (high-density motion-capture) platform with a compression-fit garment. We are currently working on a general purpose framework for scanning and modelling. We are envisioning potential applications ranging from prosthetics and orthotics to wearable robotics, reconstructive surgery, wearables and even metaverse, animation and entertainment industry. |
| First Year Of Impact | 2024 |
| Sector | Digital/Communication/Information Technologies (including Software),Healthcare |
| Impact Types | Economic |
| Title | A high-density motion-capture platform to capture deformable body surfaces |
| Description | Through U-WEAR's activities, we developed a high-density motion-capture platform aimed at measuring deformable surfaces such as the human body. This is based on a wearable compression-fit garment with a high density of fiducial tags, AprilTags, that is measured by a number of cameras mounted on a static rig. While motion-capture based on fiducial tags is currently based on rigid tags, with our developed framework we are now able to learn how tags on the compression-fit garment deform and capture these tags even when they are deformed. This is a learning-based framework that builds on existing AI frameworks such as the Segment Anything Model (SAM) and other foundational image recognition frameworks. The result is that the framework learns the layout of the unique tags on the garment and are able to detect them even when they are partially occluded or heavily deformed. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | Through this method we have started capturing deformable surfaces such as the limb surface - especially the wrist. As the wrist moves, the skin surface changes/deforms and this is captured by the developed motion-capture platform. |