Obstructive Sleep Apnea (OSA) is one of the most common sleep disorders characterized by recurrent upper airway collapse during sleep. While Mandibular Advancement Devices (MADs) represent the standard non-invasive treatment, unmonitored titration can generate excessive biomechanical loads on the stomatognathic system. Current clinical protocols rely primarily on static morphological assessments or manual geometric registrations, leaving a significant "blind spot" regarding the dynamic biomechanical interactions within the Temporomandibular Joint (TMJ). The present work aims to overcome these limitations by developing a novel in vivo sensing architecture for the real-time biomechanical characterization of mandibular protrusion. Unlike existing state-of-the-art methods, the proposed system transitions from static measurements to a dynamic force-displacement characterization, providing clinicians with an objective tool for TMD diagnosis and personalized MAD titration. Overall, the proposed prototype consists of an Arduino Nano 33 BLE microcontroller and two actuated sensors, a compression load cell and a linear slide potentiometer, housed inside a 3D-printed ABS shell, optimized for clinical ergonomics. A key methodological innovation is the establishment of the "Incisal Edge-to-Edge" alignment as a standardized metrological origin, which effectively eliminates anatomical bias and ensures inter-subject repeatability. Data acquisition and synchronized real-time visualization were managed through a dedicated MATLAB analytics engine. Experimental Proof of Concept validation trials demonstrated the system's capability to map synchronized force-displacement trajectories with high fidelity. Post-processing through linear regression analysis allowed for the extraction of the Joint Stiffness (k) parameter. The calculated stiffness values ranged from 1.07 to 1.25 N/mm, yielding a mean value of 1.14 N/mm, which shows a strong consistency with the established literature benchmark (approximately 1.18 N/mm). These results validate the metrological reliability and accuracy of the device, confirming its potential as a clinical decision-support tool to identify the optimal therapeutic window for each patient, ultimately preventing long-term joint complications.
L'Apnea Ostruttiva del Sonno (OSA) è un disturbo cronico comune e diffuso, caratterizzato dal collasso ricorrente delle vie aeree superiori durante il sonno. Sebbene i Dispositivi di Avanzamento Mandibolare (MAD) rappresentino il trattamento non invasivo standard, una titolazione non monitorata può portare a carichi biomeccanici eccessivi sul sistema stomatognatico. Gli attuali protocolli clinici si basano principalmente su valutazioni morfologiche statiche o registrazioni geometriche manuali, lasciando un significativo punto cieco riguardo alle interazioni biomeccaniche dinamiche all'interno dell'Articolazione Temporo-Mandibolare (ATM). Questa tesi mira a superare tali limitazioni sviluppando un’architettura innovativa di sensing in vivo per la caratterizzazione biomeccanica in tempo reale della protrusione mandibolare. A differenza dei metodi attuali, il sistema proposto passa da misurazioni statiche alla caratterizzazione della dinamica forza-spostamento, fornendo ai clinici uno strumento obiettivo per la diagnosi dei disordini temporo-mandibolari (TMD) e la titolazione personalizzata dei MAD. Il sistema è governato da un microcontrollore Arduino Nano 33 BLE, integrando una cella di carico a compressione di alta precisione e un potenziometro lineare. L'architettura strutturale consiste in un guscio scheletrico leggero stampato in 3D in ABS, ottimizzato per l'ergonomia clinica. Un'innovazione metodologica chiave è l'adozione dell'allineamento "Incisivi testa-testa" come origine metrologica standardizzata, che elimina efficacemente i bias anatomici e garantisce la ripetibilità tra diversi soggetti. L'acquisizione dei dati e la visualizzazione sincrona in tempo reale sono state governate da un’architettura software gestita in ambiente MATLAB, finalizzata alla sincronizzazione temporale e alla visualizzazione dinamica dei parametri biomeccanici. I test sperimentali di Proof of Concept hanno dimostrato la capacità del sistema di mappare traiettorie sincronizzate forza-spostamento con elevata fedeltà. Il post-processing tramite analisi di regressione lineare ha permesso di estrarre il parametro di rigidezza articolare (k). I valori di rigidezza calcolati sono risultati compresi tra 1.07 e 1.25 N/mm, con un valore medio di 1.14 N/mm che mostra una forte coerenza con il benchmark di riferimento in letteratura (circa 1.18 N/mm). Questi risultati validano l'affidabilità metrologica e l'accuratezza del dispositivo, confermando il suo potenziale come strumento di supporto alla decisione clinica per identificare la finestra terapeutica ottimale per ogni paziente, prevenendo complicazioni articolari a lungo termine.
Development of a novel system to measure the force and displacement to protrude a mandible for the characterization of the Temporo-Mandibular Joint
SABBATINI, SARA
2025/2026
Abstract
Obstructive Sleep Apnea (OSA) is one of the most common sleep disorders characterized by recurrent upper airway collapse during sleep. While Mandibular Advancement Devices (MADs) represent the standard non-invasive treatment, unmonitored titration can generate excessive biomechanical loads on the stomatognathic system. Current clinical protocols rely primarily on static morphological assessments or manual geometric registrations, leaving a significant "blind spot" regarding the dynamic biomechanical interactions within the Temporomandibular Joint (TMJ). The present work aims to overcome these limitations by developing a novel in vivo sensing architecture for the real-time biomechanical characterization of mandibular protrusion. Unlike existing state-of-the-art methods, the proposed system transitions from static measurements to a dynamic force-displacement characterization, providing clinicians with an objective tool for TMD diagnosis and personalized MAD titration. Overall, the proposed prototype consists of an Arduino Nano 33 BLE microcontroller and two actuated sensors, a compression load cell and a linear slide potentiometer, housed inside a 3D-printed ABS shell, optimized for clinical ergonomics. A key methodological innovation is the establishment of the "Incisal Edge-to-Edge" alignment as a standardized metrological origin, which effectively eliminates anatomical bias and ensures inter-subject repeatability. Data acquisition and synchronized real-time visualization were managed through a dedicated MATLAB analytics engine. Experimental Proof of Concept validation trials demonstrated the system's capability to map synchronized force-displacement trajectories with high fidelity. Post-processing through linear regression analysis allowed for the extraction of the Joint Stiffness (k) parameter. The calculated stiffness values ranged from 1.07 to 1.25 N/mm, yielding a mean value of 1.14 N/mm, which shows a strong consistency with the established literature benchmark (approximately 1.18 N/mm). These results validate the metrological reliability and accuracy of the device, confirming its potential as a clinical decision-support tool to identify the optimal therapeutic window for each patient, ultimately preventing long-term joint complications.| File | Dimensione | Formato | |
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Thesis_Sara_Sabbatini.pdf
embargo fino al 14/01/2028
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https://hdl.handle.net/20.500.12075/28034