ASSESSING THE IMPACT OF POSITIONAL RELEASE TECHNIQUE AND MUSCLE ENERGY TECHNIQUE ON LOW BACK PAIN-A RANDOMIZED CONTROLLED TRIAL

Aims of Study: The purpose of this study is to ascertain the impact of positional release technique and muscular energy technique on low back pain. Methodology: It was a single blinded randomized controlled trial. Participants were enrolled using envelop method of simple random sampling technique. A total n=30 clinically diagnosed LBP patients with between 26 to 40 y/o were recruited and randomly divided into two groups. Group-A MET (n=15) patients receiving muscle energy technique and Group-B PRT (n=15) patients receiving Positional Release Technique for two weeks. Results: Between groups analysis was performed using independent t test as the data was normally distributed. The results revealed statically significant results in both the groups. However, group A show more significant results with mean value of 2.0±0.53, 10.73±1.79, and 2.80±0.14 for NPRS, ODI, and Modified Schober’s Test Score respectively as shown in table 3. Limitations and Future Implications: The study may have had a limited number of participants, which could affect the generalizability of the results. Secondly, the study might have focused on short-term outcomes, assessing the immediate effects of the interventions. Originality: The study has used and compared new technique and have identified the efficacy between the two physical therapy intervention based study. Conclusions According to the findings of this study, both therapy options are successful in treating low back pain. The effectiveness of the patients in the muscle energy technique group, however, showed a substantial difference.

Robust/Optimal Control of Minimum-Phase Nolinear Systems

This thesis proposes a framework that provides suboptimal control laws for a class of minimum-phase nonlinear systems. This class includes systems whose state dynamics are an algebraic sum of their linear and nonlinear sub-dynamics. We propose a systematic method of designing a robust and optimal control law which essentially consists of two components a linear and a nonlinear. It is shown that the proposed control scheme achieves stabilization while providing suboptimality for the class of systems under consideration. Furthermore, the framework provides for a mechanism which is suitable for handling tracking and regulation problems for the class of minimum-phase nonlinear systems by using the Internal Model Principle. Astrikingfeatureoftheproposedframeworkistheflexibilityofstartingwithsynthesizing a Linear-Quadratic-Regulator for linear sub-dynamics of the system and then including a nonlinear control component that stabilizes the nonlinear sub-dynamics of the system. The flexibility offered by the proposed framework is applied firstly to a general class of linear parameter-varying and linear time-varying systems. We extend the flexibility obtained for these two systems to the class of minimum-phase nonlinear systems which are decomposable through existence of an appropriate transformation into their linear and nonlinear sub dynamics. Moreover, we also propose a simplified approach to obtain an approximate yet practical solution to the nonlinear optimal control problem by replacing the requirement of solving Hamilton-Jacobi-Bellman equations with that of the Riccati partial differential equations,andthensynthesizingthenonlinearcomponentofthecontrollawtoachieverobust and suboptimal stabilization