Image-based haptic roughness estimation and rendering for haptic palpation from in vivo skin image

Area of Science:

• Biomedical Engineering
• Dermatology
• Human-Computer Interaction

Background:

• Diagnosing skin diseases often relies on manual palpation, which carries risks of infection and damage.
• Existing technologies lack precise tactile feedback for in vivo skin surface properties.
• A need exists for non-invasive methods to assess skin's tactile characteristics.

Purpose of the Study:

• To develop a multidimensional rendering system for multimodal (visual and haptic) rendering of in vivo skin.
• To create an infection- and damage-free method for skin palpation and roughness rendering.
• To introduce an image-based roughness estimation method for verifying haptic rendering accuracy.

Main Methods:

• A 2D and 3D rendering system was developed using a commercial 3 degrees of freedom (3DOF) haptic device.
• A force shading algorithm was implemented to enhance haptic roughness rendering by reducing force discontinuity.
• An image-based roughness estimation method was introduced and validated against haptic results.

Main Results:

• The system successfully rendered haptic skin roughness, enabling virtual palpation.
• The force shading algorithm improved the fidelity of haptic roughness rendering.
• The image-based roughness estimation method correlated well with haptic rendering, verifying system accuracy.

Conclusions:

• The developed haptic rendering system facilitates non-invasive diagnosis of skin abnormalities, particularly those involving roughness changes (e.g., psoriasis, atopic dermatitis, aging).
• The system serves as a valuable tool for evaluating skin condition changes before and after cosmetic product application.
• The proposed 2D roughness estimation method has potential for mobile applications, offering an accessible online skin roughness assessment tool.