Spine disorders are one of the most prevalent and costly problems facing modem medicine, with an estimated annual cost of over S80 billion. Improved understanding of the biomechanical properties of the normal and pathological spine is essential for treatment of traumatic injury, degeneration, or other ailments. To measure these properties, highly specialized testing machines and devices have been developed; providing valuable data such as the load-displacement behavior or stiffness of a specimen. However, the complex structure of the spine makes experimental testing difficult to control using standardized load or displacement control methods, which were established for typical (linear) engineering materials such as plastics or steel. Hence, new control methods for testing of these biological systems are needed.
The primary objective of this research was to apply robotics technology and control methods to the measurement of lumbar spine structural properties, and to develop an analytical simulation of both the robot and the specimen. An existing robotic/UFS (universal force sensor) testing system using a hybrid (stiffness-based) control method was adapted to measurement of flexion/extension kinetics of 15 lumbar functional spinal units (FSUs). Results demonstrated characteristic kinetic features of the lumbar spine — including typical neutral and elastic zones as described in previous studies. It was found that hybrid control methods combining both load and displacement feedback provided improved delineation and control of the specimen within the neutral zone. For each specimen, sequential sectioning of the ligaments, facets, and disc was performed. In-situ loads carried by each of the FSU component structures during flexion/extension was measured. These studies provided valuable data necessary for the development of analytical specimen models.
Analytical models of both the specimen and the robotic/UFS testing system were developed using kinetic theory derived from classical robotics literature. These models were combined into a simulation, or “virtual testing system,” enabling a wide variety of control algorithms, testing procedures, and specimen variables to be developed and visualized. Further developments of hybrid and other control theories could help to elucidate the interactions that occur among the passive, active, and neural control subsystems of the spine.
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