Can Blood Flow Restricted Exercise Improve Ham:Quad Ratios Better Than Traditional Training?

Muscular deficiencies between the quadriceps and hamstrings are prevalent among women and often lead to knee injury and ACL tears. The purpose of this study was to examine whether short term resistance training with or without blood flow restriction (BFR) could improve hamstring:quadricep ratios (H:Q) and reduce the chance for injury. Women (n = 14; 18-25 yrs) were randomly assigned to either a traditional resistance training (RT: n = 8) or BFR resistance training in combination with traditional RT (RT+BFR: n = 6) group. Subjects trained 3 days/week for 6 weeks. The RT group completed 3 sets of 10 reps at 70% of their one-repetition maximum (1RM) with 1-minute rest between sets. The RT+BFR group completed the first 5 exercises similar to the RT group but performed the two-leg hamstring curl under blood flow restriction at 50% of occlusive pressure and 30% 1RM, completing 4 sets (30, 15, 15, 15) with 30 seconds rest between sets. Training effects were assessed using a two-way repeated measures ANOVA. Statistical significance was set at p≤0.05. There were significant (p < 0.05) main effects for time, with all muscle groups increasing strength but no significant main effects or interaction for the H:Q ratios at four testing speeds (60°/s, 180°/s, 240°/s, and 300°/s). This study found that hamstring strength with low load (30% 1RM) BFR training was improved to a similar extent as the hamstrings trained with the traditional high load (75% 1RM) program even though less external weight was used during training. H:Q ratios showed small non-significant increases post-training for both groups.

Statistical detection and imaging of objects hidden in turbid media using ballistic photons.

We exploit recent advances in active high-resolution imaging through scattering media with ballistic photons. We derive the fundamental limits on the accuracy of the estimated parameters of a mathematical model that describes such an imaging scenario and compare the performance of ballistic and conventional imaging systems. This model is later used to derive optimal single-pixel statistical tests for detecting objects hidden in turbid media. To improve the detection rate of the aforementioned single-pixel detectors, we develop a multiscale algorithm based on the generalized likelihood ratio test framework. Moreover, considering the effect of diffraction, we derive a lower bound on the achievable spatial resolution of the proposed imaging systems. Furthermore, we present the first experimental ballistic scanner that directly takes advantage of novel adaptive sampling and reconstruction techniques.