Abstract

Minimally invasive surgical operations encompass various surgical tasks ranging from conventional endoscopic/laparoscopic methods to recent sophisticated minimally invasive surgical techniques. In such sophisticated techniques, surgeons use equipment varying from robotic-assisted surgical platforms for abdominal surgery to computer-controlled catheters for catheter-based cardiovascular surgery. Presently, the countless advantages that minimally invasive surgery offers for both patients and surgeons have made the use of such surgical operations routine and reliable. However, in such operations, unlike conventional surgical operations, surgeons still suffer from the lack of tactile perception while interacting with the biological tissues using surgical instruments. To address this issue, it is necessary to develop a tactile sensor that can mimic the fingertip tactile perceptions of surgeons. In doing so and to satisfy the needs of surgeons, a number of considerations should be implemented in the design of the tactile sensors.
First, the sensor should be magnetic resonance compatible to perform measurements even in the presence of magnetic resonance imaging (MRI) devices. Currently, such devices are in wide-spread use in surgical operation rooms. Second, the sensor should be electrically-passive because introducing electrical current into the patients’ body is not desirable in various surgical operations such as cardiovascular operations. Third, the sensor should perform measurements under both static and dynamic loading conditions during the sensor-tissue interactions. Such a capability of the sensor ensures that surgeons receive tactile feedback even when there is continuous static contact between surgical tools and tissues. Essentially, surgeons need such feedback to make surgical tasks safer. In addition, the size of the sensor should be miniaturized to address the size restrictions. In fact, the combination of intensity-based optical fiber sensing principles and micro-systems technology is one of the limited choices that address all the required considerations to develop such tactile sensors in a variety of ways.
The present thesis deals with the design, modeling, manufacturing, testing, and characterizing of different tactile sensor configurations based on detection and integration methods. The various stages of design progress and principles are developed into different design configurations and presented in different chapters. The main sensing principle applied is based on the intensity modulation principle of optical fibers using micro-systems technology. In addition, a hybrid sensing principle is also studied by integrating both optical and non-optical detection methods. The micromachined sensors are categorized into five different generations. Each generation has advantages by comparison with its counterpart from the previous generation. The initial development of micromachined sensors is based on optical fiber coupling loss. In the second phase, a hybrid optical-piezoresistive sensing principle is studied. The success of these phases was instrumental in realizing a micromachined sensor that has the advantage of being fully optical. This sensor measures the magnitude of concentrated and distributed force, the position of a concentrated force, the variations in the force distribution along its length, the relative hardness of soft contact objects, and the local discontinuities in the hardness of the contact objects along the length of the contact area. Unlike most electrical-based commercially-available sensors, it performs all of these measurements under both static and dynamic loading conditions. Moreover, it is electrically passive and potentially MRI-compatible. The performances of the sensors were experimentally characterized for specific conditions presented in this thesis. However, these performances are easily tunable and adjustable depending upon the requirements of specific surgical tasks. Although the sensors were initially designed for surgical applications, they can have numerous other applications in the areas of robotics, automation, tele-display, and material testing.