While public awareness of sleep related disorders is growing, sleep apnea syndrome (SAS) remains a public health and economic challenge. Over the last two decades, extensive controlled epidemiologic research has clarified the incidence, risk factors including the obesity epidemic, and global prevalence of obstructive sleep apnea (OSA), as well as establishing a growing body of literature linking OSA with cardiovascular morbidity, mortality, metabolic dysregulation, and neurocognitive impairment. The US Institute of Medicine Committee on Sleep Medicine estimates that 50-70 million US adults have sleep or wakefulness disorders. Furthermore, the American Academy of Sleep Medicine (AASM) estimates that more than 29 million US adults suffer from moderate to severe OSA, with an estimated 80% of those individuals living unaware and undiagnosed, contributing to more than $149.6 billion in healthcare and other costs in 2015. Although various devices have been used to measure physiological signals, detect apneic events, and help treat sleep apnea, significant opportunities remain to improve the quality, efficiency, and affordability of sleep apnea care. As our understanding of respiratory and neurophysiological signals and sleep apnea physiological mechanisms continues to grow, and our ability to detect and process biomedical signals improves, novel diagnostic and treatment modalities emerge. Objective: This article reviews the current engineering approaches for the detection and treatment of sleep apnea. Approach: It discusses signal acquisition and processing, highlights the current nonsurgical and nonpharmacological treatments, and discusses potential new therapeutic approaches. Main results: This work has led to an array of validated signal and sensor modalities for acquiring, storing and viewing sleep data; a broad class of computational and signal processing approaches to detect and classify SAS disease patterns; and a set of distinctive therapeutic technologies whose use cases span the continuum of disease severity. Significance: This review provides a current perspective of the classes of tools at hand, along with a sense of their relative strengths and areas for further improvement.

We present the device design, simulation, and measurement results of a therapy device that potentially prevents sleep apnea by slightly increasing inspired CO2 through added dead space (DS). The rationale for treatment of sleep apnea with CO2 manipulation is based on two recently reported premises: (i) preventing transient reductions in PaCO2 will prevent the patient from reaching their apneic threshold, thereby preventing “central” apnea and instabilities in respiratory motor output; and (ii) raising PaCO2 and end-tidal CO2, even by a minimal amount, provides a strong recruitment of upper airway dilator muscles, thereby preventing airway obstruction. We have also provided the simulation results, obtained from solving the Navier–Stokes (NS) equations within the device volume. Therein, the NS equations are coupled with a convection–diffusion equation that represents the transport of CO2 in the device, thus enabling the transient simulation of CO2 propagation. Using this procedure, a prototype of variable volume dead space reservoir device was designed. Volumetric factors influencing carbon dioxide increases in the added reservoir (open-ended DS) were investigated. The maximum/minimum amount of CO2 concentration were obtained for the maximum/minimum device volume; 3.4 and 2.4 mol/m3 for the DS volumes of 1.2 and 0.5 × 10−3 m3, respectively. In all case studies, the CO2 buildup reached a plateau after approximately 20 breathing cycles. The experimental measurement results are in agreement with the simulation and numerical results obtained using the proposed simplified modeling technique, with a maximum relative error of 3.5%.

Biomedical Engineering (BME) students at our University participate in a unique design curriculum consisting of team-based design courses for seven semesters. Starting freshman year where students work in interdisciplinary teams to solve community-based design challenges to sophomore through senior year where they design, build and test their innovative solutions for clients in the healthcare profession, local industry, community and university. Within our design curriculum sophomores work on teams with juniors forming mentored relationships and seniors participate in outreach as well as prepare their work for publication. Historically, students would develop technical skills as needed based on their project as well as through workshops offered through the department. Through engagement with our advisory board, alumni and our BME Student Advisory Committee (BSAC), it became evident that more formal and direct training on essential engineering tools was needed early in the curriculum. As a result, in 2012, we transformed our required second semester sophomore opened ended design course into a two-credit lecture and laboratory course with a guided design project: BME 201, “Biomedical Engineering Fundamentals and Design.” Over the last five offerings of BME 201 since 2012, the course has evolved to cohesively combine all three components (lecture, lab, and a design project) into modulus throughout the course that represent the field of BME both from a curricular and industry standpoint. The modules include: electronics, programing (LabVIEW and Arduino), mechanics (SOLIDWORKS, machine shop use and mechanical testing), biomaterials and tissue engineering (literature research, biosafety, aseptic technique, optics and material interactions). To effectively reach the students in the course and update course content, we utilize a three tiered instructional approach: instructors, three teaching assistants, and 20 undergraduate student assistants, all bringing their educational and industry experiences to the course. The student instructors rotate throughout the course depending on their expertise. We have assessed the effectiveness of this course with pre- and post- course surveys showing the influence of the course on their curriculum and career choices and the influence of the peer learning model. Additionally, our department’s Assessment Committee has noted an improvement in student outcome performance of both the sophomore student population as well as our seniors pre- and post- BME 201. Finally, employer surveys have shown that our students are well prepared for industry in a variety of positions.