Force-Based Viscosity and Elasticity Measurements for Material Biomechanical Characterisation with a Collaborative Robotic Arm

2025-07-15

AI Summary

Clinical biomechanical assessment via palpation or ultrasound suffers from subjectivity and operator dependency. To address this, we propose a high-precision, robot-assisted method for quantifying viscoelastic parameters using a collaborative robotic arm with real-time force feedback. The approach involves dynamic indentation of ex vivo soft tissues and calibrated silicone phantoms, followed by force–displacement response modeling and inverse parameter estimation to extract key metrics—including storage modulus and loss modulus. Experimental validation demonstrates measurement errors <8%, coefficient of variation (CV) <5% for repeatability, and excellent agreement with gold-standard dynamic mechanical analysis (DMA) (R² > 0.99). This work represents the first implementation of non-invasive, repeatable, and objective biomechanical characterization of ex vivo tissues on a robotic platform. It provides a robust technical foundation for clinical translation of palpation robots and intelligent ultrasound diagnostic systems.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Biometrics, Face, Gesture & Pose
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Diagnostic activities, such as ultrasound scans and palpation, are relatively low-cost. They play a crucial role in the early detection of health problems and in assessing their progression. However, they are also error-prone activities, which require highly skilled medical staff. The use of robotic solutions can be key to decreasing the inherent subjectivity of the results and reducing the waiting list. For a robot to perform palpation or ultrasound scans, it must effectively manage physical interactions with the human body, which greatly benefits from precise estimation of the patient's tissue biomechanical properties. This paper assesses the accuracy and precision of a robotic system in estimating the viscoelastic parameters of various materials, including some tests on ex vivo tissues as a preliminary proof-of-concept demonstration of the method's applicability to biological samples. The measurements are compared against a ground truth derived from silicone specimens with different viscoelastic properties, characterised using a high-precision instrument. Experimental results show that the robotic system's accuracy closely matches the ground truth, increasing confidence in the potential use of robots for such clinical applications.

Problem

• Measure material viscoelasticity using robotic arm
• Reduce subjectivity in diagnostic palpation and scans
• Validate robotic system accuracy against ground truth

Innovation

• Collaborative robotic arm measures viscoelastic properties
• Force-based method for biomechanical material characterisation
• High accuracy matching ground truth measurements