Description |
Computing and data acquisition have become an integral part of everyday life. From reading emails on a cell phone, to kids playing with motion sensing game consoles, we are surrounded with sensors and mobile devices. As the availability of powerful mobile computing devices expands, the road is paved for applications in previously limited environments. Rehabilitative devices are emerging that embrace these mobile advances. Research has explored the use of smartphones in rehabilitation as a means to process data and provide feedback in conjunction with established rehabilitative methods. Smartphones, combined with sensor embedded insoles, provide a powerful tool for the clinician in gathering data and may act as a standalone training technique. This thesis presents continuing research of a sensor integrated insole system that provides real-time feedback through a mobile platform, the Adaptive Real-Time Instrumentation System for Tread Imbalance Correction (ARTISTIC). The system interfaces a wireless instrumented insole with an Android smartphone application to receive gait data and provide sensory feedback to modify gait patterns. Revisions to the system hardware, software, and feedback modes brought about the introduction of the ARTISTIC 2.0. The number of sensors in the insole was increased from two to 10. The microprocessor and a vibrotactile motor were embedded in the insole and the communications box was reduced in size and weight by more than 50%. Stance time iv measurements were validated against force plate equipment and found to be within 13.5 ± 3.3% error of force plate time measurements. Human subjects were tested using each of the feedback modes to alter gait symmetry. Results from the testing showed that more than one mode of feedback caused a statistically significant change in gait symmetry ratios (p < 0.05). Preference of feedback modes varied among subjects, with the majority agreeing that several feedback modes made a difference in their gait. Further improvements will prepare the ARTISTIC 2.0 for testing in a home environment for extended periods of time and improve data capture techniques, such as including a database in the smartphone application. |