The article titled “Ultrasound Imaging of Artificial Tongues During Compression and Shearing of Food Gels on a Biomimetic Testing Bench” by Glumac et al. [1] presents a novel methodology to analyze tongue–food interactions using ultrasound (US) imaging. The primary aim of the study is to better understand the mechanical processes that occur during oral food processing, particularly how deformation at the interface between the tongue and food contributes to the perception of texture.
To simulate oral conditions, the researchers developed four artificial tongue models made from polyvinyl alcohol (PVA) cryogels. These phantoms differed in surface roughness and stiffness to emulate various human tongue properties. Complementing these were model food gels made from agar, each with distinct concentrations to represent different textures. The experimental setup involved placing these gels between the tongue phantom and a simulated hard palate within a biomimetic testing bench. A multi-axis force sensor recorded the applied mechanical loads, while an ultrasound transducer array captured real-time images of the tongue surface during both compression and shear tests.
Ultrasound contour tracking allowed precise monitoring of deformation distribution along the contact surface. During shear tests, image-based particle tracking methods, including Particle Image Velocimetry (PIV), enabled the visualization of horizontal velocity gradients within the tongue model. These data revealed how deformation was not uniformly distributed but varied across the contact region, providing insight into how tactile stimuli are generated during oral manipulation of food.
One of the notable findings from the study was the ability to distinguish between static and dynamic friction phases during shearing motions, a feature that significantly influences how textures are perceived in the mouth. The technique also highlighted how different tongue stiffness levels affected force transmission and deformation patterns, reinforcing the critical role of oral biomechanics in food sensory evaluation.
Importantly, the study’s innovation lies in integrating high-resolution US imaging with a biomimetic mechanical platform, providing both spatial and temporal resolution of oral interactions that were previously inaccessible. These insights have broad implications for the fields of sensory science, food texture engineering, and even oral drug delivery.
MCC Spheres enhancing the reproducibility and standardization
In this context of ultrasound imaging of artificial tongues, CELLETS® 90 (60 – 100 µm) represent an important avenue for enhancing the reproducibility and standardization of such experiments. As highly uniform microcrystalline cellulose spheres, CELLETS® offer consistent mechanical properties and geometric features that make them ideal as model substrates in oral-processing research. Their controlled size and mechanical resilience could serve to benchmark system sensitivity or be incorporated as reference particles within gel matrices to better interpret deformation dynamics. Furthermore, the use of CELLETS® aligns with pharmaceutical interests in simulating the oral disintegration behavior of solid dosage forms. Their integration into the described US-based methodology would therefore contribute to expanding the translational relevance of this platform across both food and pharmaceutical domains.
Scientific Significance
This work pioneers the combination of biomimetic tongue models and advanced ultrasound imaging to quantitatively dissect oral texture mechanics. The ability to resolve friction phases, spatial deformation patterns, and velocity gradients during tongue–food interaction enriches our understanding of mechanosensory stimulation pathways. Such insights are invaluable for rational design of food products—especially for populations with altered oral processing (e.g., elderly, dysphagia)—as well as for development of orally disintegrating drug formulations. The proposed integration of CELLETS® further strengthens methodological robustness, offering a bridge between food science and pharmaceutical applications, and encouraging cross-disciplinary collaboration.
References
[1] M. Glumac, J.-L. Gennisson, V. Mathieu, Journal of Texture Studies, 2025; 56:e70030; doi:10.1111/jtxs.70030
Disclaimer: this text was partly composed with ChatGPT-4.
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