A Wireless Monitoring System Using a Tunneling Sensor Array in a Smart Oral Appliance for Sleep Apnea Treatment

Smart mandibular advancement devices for obstructive sleep apnea: a systematic literature review

PURPOSE

The goal of this review is to provide sleep physicians, dentists, and researchers with an evidence-based overview of the literature on smart mandibular advancement devices (MADs) for the treatment of obstructive sleep apnea.

METHODS

A systematic literature search was conducted by two blinded reviewers and an information specialist. A smart MAD was defined as any MAD with additional functionality besides mandibular protrusion. The bibliographic databases Medline, Embase, and Scopus were used to identify relevant publications. Studies were included if they described any stage of development of smart MADs. A total of 3162 titles and abstracts were screened for their relevance. In total, 58 articles were selected for full-text screening, 26 of which were included in this review.

RESULTS

The overall quality of the available literature was low. Most of the studies were observational, clinical or applied-research articles. The authors classified MADs into two main groups: passive and active. Passive MADs measured patient data, most commonly patient compliance. Active MADs adjusted protrusion of the mandible in response to patient data and were found in various phases of technological readiness (in development, demonstration, or deployment).

CONCLUSION

Innovations in smart mandibular advancement devices most frequently track patient compliance. Devices measuring other health parameters and active, feedback-controlled, devices are increasingly reported on. However, studies demonstrating their added benefit over traditional methods remain sparse. With further study, smart mandibular advancement devices have the potential to improve the efficiency of obstructive sleep apnea treatment and provide new treatment possibilities.

Precision medicine approaches in obstructive sleep apnoea: The role of dentist-sleep physician partnerships

Obstructive Sleep Apnoea (OSA) is a common heterogenous sleep disorder that is associated with a wide range of comorbidities and consequences, including the development of neurocognitive and cardiometabolic disorders. The heterogeneity of OSA necessitates a precision medicine approach to accurately diagnose this condition and to effectively manage patients. One of the primary models of precision medicine is described by the P4 approach of predicting those who are susceptible to disease, preventing the occurrence of disease, personalizing treatment, and encouraging patients to participate in their individual healthcare journey. Recent advances in oral appliance therapy and OSA monitoring techniques have fostered an exciting opportunity for enhanced collaboration between dentists and sleep physicians to optimize OSA precision medicine care. This review aims to discuss the sources of heterogeneity among OSA patients, provide an overview of the growing applications of oral appliance therapy and tailored monitoring programs for OSA that are shifting treatment to a more personalized and participatory model of care, and outline the pivotal role of dentists in managing patients with OSA.

Resolution enhancement of tongue tactile image based on deconvolution neural network

To reproduce the tactile perception of multiple contacts on the human tongue surface, it is necessary to use a pressure measurement device with high spatial resolution. However, reducing the size of the array sensing unit and optimizing the lead arrangement still pose challenges. This article describes a deconvolution neural network (DNN) for improving the resolution of tongue surface tactile imaging, which alleviates this tradeoff between tactile sensing performance and hardware simplicity. The model can work without high-resolution tactile imaging data of tongue surface: First, in the compression test using artificial tongues, the tactile image matrix (7 × 7) with low resolution can be acquired by sensor array with a sparse electrode arrangement. Then, through finite element analysis modeling, combined with the distribution rule of additional stress on the two-dimensional plane, the pressure data around the existing detection points are calculated, further expanding the tactile image matrix data amount. Finally, the DNN, based on its efficient nonlinear reconstruction attributes, uses the low-resolution and high-resolution tactile imaging matrix generated by compression test and finite element simulation, respectively, to train, and outputs high-resolution tactile imaging information (13 × 13) closer to the tactile perception of the tongue surface. The results show that the overall accuracy of the tactile image matrix calculated by this model is above 88%. Then, we deduced the spatial difference graph of the resilience index of the three kinds of ham sausages through the high-resolution tactile imaging matrix.

The Biomechanical Mechanism of Upper Airway Collapse in OSAHS Patients Using Clinical Monitoring Data during Natural Sleep

Obstructive sleep apnea hypopnea syndrome (OSAHS) is a common sleep disorder characterized by repeated pharyngeal collapse with partial or complete obstruction of the upper airway. This study investigates the biomechanics of upper airway collapse of OSASH patients during natural sleep. Computerized tomography (CT) scans and data obtained from a device installed on OSASH patients, which is comprised of micro pressure sensors and temperature sensors, are used to develop a pseudo three-dimensional (3D) finite element (FE) model of the upper airway. With consideration of the gravity effect on the soft palate while patients are in a supine position, a fluid–solid coupling analysis is performed using the FE model for the two respiratory modes, eupnea and apnea. The results of this study show that the FE simulations can provide a satisfactory representation of a patient’s actual respiratory physiological processes during natural sleep. The one-way valve effect of the soft palate is one of the important mechanical factors causing upper airway collapse. The monitoring data and FE simulation results obtained in this study provide a comprehensive understanding of the occurrence of OSAHS and a theoretical basis for the individualized treatment of patients. The study demonstrates that biomechanical simulation is a powerful supplementation to clinical monitoring and evaluation.