Laboratory rats play a critical role in research because they provide a biological model that can be used for evaluating the affectation of diseases and injuries, and for the evaluation of the effectiveness of new drugs and treatments. The analysis of locomotion in laboratory rats facilitates the understanding of motor defects in many diseases, as well as the damage and recovery after peripheral and central nervous system injuries. However, locomotion analysis of rats remains a great challenge due to the necessity of labor intensive manual annotations of video data required to obtain quantitative measurements of the kinematics of the rodent extremities. In this work, we present a method that is based on the use of a bio-inspired algorithm that fits a kinematic model of the hind limbs of rats to binary images corresponding to the segmented marker of images corresponding to the rat’s gait. The bio-inspired algorithm combines a genetic algorithm for a group of the optimization variables with a local search for a second group of the optimization variables. Our results indicate the feasibility of employing the proposed approach for the automatic annotation and analysis of the locomotion patterns of the posterior extremities of laboratory rats. The adjustment of the hind limb kinematic model to markers of the video frames corresponding to rat’s gait sequences could then be used to analyze the motion patterns during the steps, which, in turn, can be useful for performing quantitative evaluations of the effect of lesions and treatments on rats models.

In this work, the twin-grating fiber optic sensor has been applied on wavelength-division multiplexing. A quasi-distributed sensor formed by three local twin-grating sensors, is numerically simulated. The wavelength channels were 1531.5, 1535.5, and 1539.5 nm. The numerical simulation shows the resolution vs. signal-to-noise rate. Three local twin-grating sensors have approximately the same resolution because all local sensors have the same cavity length and the wavelength channels are very close. All local sensors have two numerical resolutions because the Fourier domain phase analysis algorithm makes two evaluations of the Bragg wavelength shift. The transition between both resolutions can be calculated with the parameters: cavity length, Bragg wavelength channel, refraction index, and enveloped resolution. This transition depends on the noise system, demodulation algorithm, instrumentation, and local sensor properties. A very important point is, a theoretical analysis will permit to know the exact resolution for each local twin-grating sensor.