Biomechanical Models of Human Upper and Tracheal Airway Functionality

The respiratory tract, in other words, the airway, is the primary airflow path for several physiological activities such as coughing, breathing, and sneezing. Diseases can impact airway functionality through various means including cancer of the head and neck, Neurological disorders such as Parkinson\u27s disease, and sleep disorders and all of which are considered in this study. In this dissertation, numerical modeling techniques were used to simulate three distinct airway diseases: a weak cough leading to aspiration, upper airway patency in obstructive sleep apnea, and tongue cancer in swallow disorders. The work described in this dissertation, therefore, divided into three biomechanical models, of which fluid and particulate dynamics model of cough is the first. Cough is an airway protective mechanism, which results from a coordinated series of respiratory, laryngeal, and pharyngeal muscle activity. Patients with diminished upper airway protection often exhibit cough impairment resulting in aspiration pneumonia. Computational Fluid Dynamics (CFD) technique was used to simulate airflow and penetrant behavior in the airway geometry reconstructed from Computed Tomography (CT) images acquired from participants. The second study describes Obstructive Sleep Apnea (OSA) and the effects of dilator muscular activation on the human retro-lingual airway in OSA. Computations were performed for the inspiration stage of the breathing cycle, utilizing a fluid-structure interaction (FSI) method to couple structural deformation with airflow dynamics. The spatiotemporal deformation of the structures surrounding the airway wall was predicted and found to be in general agreement with observed changes in luminal opening and the distribution of airflow from upright to supine posture. The third study describes the effects of cancer of the tongue base on tongue motion during swallow. A three-dimensional biomechanical model was developed and used to calculate the spatiotemporal deformation of the tongue under a sequence of movements which simulate the oral stage of swallow

Applications of EMG in Clinical and Sports Medicine

This second of two volumes on EMG (Electromyography) covers a wide range of clinical applications, as a complement to the methods discussed in volume 1. Topics range from gait and vibration analysis, through posture and falls prevention, to biofeedback in the treatment of neurologic swallowing impairment. The volume includes sections on back care, sports and performance medicine, gynecology/urology and orofacial function. Authors describe the procedures for their experimental studies with detailed and clear illustrations and references to the literature. The limitations of SEMG measures and methods for careful analysis are discussed. This broad compilation of articles discussing the use of EMG in both clinical and research applications demonstrates the utility of the method as a tool in a wide variety of disciplines and clinical fields

Biomechanical modeling of deglutition

Swallowing is a physiological process whose malfunction a effects the human quality of life, e.g. malnutrition, dehydration or asphyxia, and has been studied using in vivo approaches. However, advances in computational capacity have encouraged the production of more accurate computational models of offering advantages such as flexibility and reduced experimental costs. Hence, this work proposed the numerical solution of a 2D sagittal swallowing model with physiological accurate tongue's dorsum dynamics based on real time magnetic resonance imaging (RT-MRI) of a healthy young adult. The work designed a full factorial set of simulations and with a second order Box Behnken' surface response design, dimensional relationships were established between food bolus' rheology, swallowing speed, output flow rate, force and shear force over the tongue. Moreover, a dimensionless model was also proposed and exponential behaviors of pressure and friction coefficients as a function of Reynolds numbers were found with an exponential relationship. Such results are intended to predict swallowing flow conditions based on bolus' rheology and the speed of the swallowing event, and also serve as a first validation for more complex models that use other representation techniques. As validation approaches, the work addressed three indirect validations.MaestríaMAGISTER EN INGENIERÍA ÉNFASIS EN INGENIERÍA MECÁNIC

Musculoskeletal Models in a Clinical Perspective

This book includes a selection of papers showing the potential of the dynamic modelling approach to treat problems related to the musculoskeletal system. The state-of-the-art is presented in a review article and in a perspective paper, and several examples of application in different clinical problems are provided

Soft Electronics Enabled Ergonomic Human-Computer Interaction for Swallowing Training

We introduce a skin-friendly electronic system that enables human-computer interaction (HCI) for swallowing training in dysphagia rehabilitation. For an ergonomic HCI, we utilize a soft, highly compliant (“skin-like”) electrode, which addresses critical issues of an existing rigid and planar electrode combined with a problematic conductive electrolyte and adhesive pad. The skin-like electrode offers a highly conformal, user-comfortable interaction with the skin for long-term wearable, high-fidelity recording of swallowing electromyograms on the chin. Mechanics modeling and experimental quantification captures the ultra-elastic mechanical characteristics of an open mesh microstructured sensor, conjugated with an elastomeric membrane. Systematic in vivo studies investigate the functionality of the soft electronics for HCI-enabled swallowing training, which includes the application of a biofeedback system to detect swallowing behavior. The collection of results demonstrates clinical feasibility of the ergonomic electronics in HCI-driven rehabilitation for patients with swallowing disorders

Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview

A quantitative evaluation of kinetic parameters, the joint’s range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device’s positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user’s vital signs directly from the body in an accurate and non–invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach’s subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post–operative rehabilitation and athletes’ training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user’s health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties

Noninvasive Dynamic Characterization of Swallowing Kinematics and Impairments in High Resolution Cervical Auscultation via Deep Learning

Swallowing is a complex sensorimotor activity by which food and liquids are transferred from the oral cavity to the stomach. Swallowing requires the coordination between multiple subsystems which makes it subject to impairment secondary to a variety of medical or surgically related conditions. Dysphagia refers to any swallowing disorder and is common in patients with head and neck cancer and neurological conditions such as stroke. Dysphagia affects nearly 9 million adults and causes death for more than 60,000 yearly in the US. In this research, we utilize advanced signal processing techniques with sensor technology and deep learning methods to develop a noninvasive and widely available tool for the evaluation and diagnosis of swallowing problems. We investigate the use of modern spectral estimation methods in addition to convolutional recurrent neural networks to demarcate and localize the important swallowing physiological events that contribute to airway protection solely based on signals collected from non-invasive sensors attached to the anterior neck. These events include the full swallowing activity, upper esophageal sphincter opening duration and maximal opening diameter, and aspiration. We believe that combining sensor technology and state of the art deep learning architectures specialized in time series analysis, will help achieve great advances for dysphagia detection and management in terms of non-invasiveness, portability, and availability. Like never before, such advances will enable patients to get continuous feedback about their swallowing out of standard clinical care setting which will extremely facilitate their daily activities and enhance the quality of their lives