Engineering Vestibular System Using Polymeric Piezoresistive Hair Cell Sensors

Balance impairments afflict almost 30% of the population over the course of their lives and cause debilitating symptoms such as nystagmus, oscillopsia, and vertigo. Balance disorders are attributed to peripheral vestibular dysfunction, mainly caused by hair cell loss. Ageing, trauma, genetics, and ototoxicity are the main factors resulting in vestibular hair cell damage. Hair cells are positioned in the ampullae of three interconnected semicircular canals (SCCs), constituting the main part of the complicated vestibular organ, which is directly in charge of body balance. This thesis focuses on developing a biomimetic semicircular canal equipped with miniaturized sensors to mimic vestibular function. It begins with the introduction of objectives, physical problem, and a brief overview of the critical features of used materials for fabricating flow sensors in Chapter 1. Chapter 2 reviews the history and developments of bioelectronic devices, including bionic vestibular systems and artificial hair cell sensors to interface with the vestibular system. Moreover, this chapter presents the history of hair bundle analysis, and SCC modelling of SCCs is presented. In the first project, a microelectromechanical systems (MEMS) flow sensor is proposed to mimic the vestibular hair cell sensors by embedding the sensor into a three-dimensional (3D) printed lateral SCC (LSCC), as detailed in Chapter 3. Head movement is simulated by a rotary stage consisting of three servo motors, each of them responsible for mimicking the yaw, pitch, and roll rotations of the head. To achieve ultra-high sensitivity and linear response, we have fabricated a miniaturized hair cell sensor comprised of a mazelike structure of vertical graphene nanosheets (VGNs) with penetrated PDMS. As one of its applications, we characterized the sensor with an airflow generator and tested it as an airflow sensor for monitoring respiratory patterns. The results showed the sensor has outstanding performance as an airflow sensor. Then the proposed flow sensor was fully characterized under stationary and oscillatory flow conditions and tested in an LSCC at various frequencies and head rotation angles, as described in Chapter 4. Then, we utilized this sensor as an airflow sensor for monitoring human respiratory patterns, as presented in Chapter 5. The sensor was characterized in a wide range of airflow rates, and the obtained results indicated a linear response with high sensitivity and low response time (below 1 s). A finite-element analysis was conducted to evaluate the experimental results, particularly the sensor tip displacement measured by laser Doppler vibrometry (LDV) and sensor output as a function of flow rate. The biocompatibility of artificial hair cell sensors is a critical factor that should be addressed. Chapter 6 presents a biocompatible hair cell sensor based on polyvinyl alcohol (PVA) hydrogel nanocomposites with a mazelike network of VGNs. The main feature of the proposed flow sensor is the low-frequency detection of oscillatory flows down to 0.1 Hz, making the sensor ideal for simulating vestibular hair cells inside the SCCs. Chapter 7 proposes an artificial hair cell sensor made of platinum (Pt) thin films reinforced with carbon nanofibers (CNFs) sandwiched by two PDMS layers. The proposed sensor was characterized by various airflow rates for recording respiratory patterns. The results demonstrated the sensor has high sensitivity, low response time and a low-velocity threshold compared with previous studies. As the main application of the artificial hair cell sensor, the sensor was tested in LSCC at various physiological conditions of vestibular hair cells in Chapter 8. Finally, this thesis concludes with remarkable points for further improvements in Chapter 9.