Traumatic brain injury has been the leading cause of mortality and morbidity in human beings. One of the most susceptible structures to this damage is the hippocampus due to cellular and synaptic loss and impaired hippocampal connectivity to the brain, brain stem, and spinal cord. Thus, hippocampal damage in rodents using a stereotaxic device could be an adequate method to study a precise lesion from CA1 to the dentate gyrus structures. We studied male and female rats and mice, analyzing hindlimb locomotion kinematics changes to compare the locomotion kinematics using the same methodology in rodents. We measure (1) the vertical hindlimb metatarsus, ankle, and knee joint vertical displacements (VD) and (2) the factor of dissimilarity (DF). The VD in intact rats in metatarsus, ankle, and knee joints differs from that in intact mice in similar joints. In rats, the vertical displacement through the step cycle changed in the left and right metatarsus, ankle, and knee joints compared to the intact group versus the lesioned group. More subtle changes were also observed in mice. DF demonstrates contrasting results when studying locomotion kinematics of mice or rats and sex-dependent differences. Thus, a precise lesion in a rodent's hippocampal structure discloses some hindlimb locomotion changes related to species and sex. Thus, we only have a qualitative comparison between murine species. In order to make a comparison with other species, we should standardize the model.
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http://dx.doi.org/10.3390/brainsci13111545 | DOI Listing |
Sensors (Basel)
January 2025
Centre for Automation and Robotics (CAR UPM-CSIC), Escuela Técnica Superior de Ingeniería y Diseño Industrial (ETSIDI), Universidad Politécnica de Madrid, Ronda de Valencia 3, 28012 Madrid, Spain.
Analysis of the human gait represents a fundamental area of investigation within the broader domains of biomechanics, clinical research, and numerous other interdisciplinary fields. The progression of visual sensor technology and machine learning algorithms has enabled substantial developments in the creation of human gait analysis systems. This paper presents a comprehensive review of the advancements and recent findings in the field of vision-based human gait analysis systems over the past five years, with a special emphasis on the role of vision sensors, machine learning algorithms, and technological innovations.
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January 2025
College of Sport and Health Science, Ritsumeikan University, Kusatsu 525-8577, Shiga, Japan.
This study aimed to assess the intraday reliability of markerless gait analysis using an RGB-D camera versus a traditional three-dimensional motion analysis (3DMA) system with and without a simulated walking assistant. Gait assessments were conducted on 20 healthy adults walking on a treadmill with a focus on spatiotemporal parameters gathered using the RGB-D camera and 3DMA system. The intraday reliability of the RGB-D camera was evaluated using intraclass correlation coefficients (ICC 1, 1), while its consistency with the 3DMA system was determined using ICC (2, 1).
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January 2025
Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico.
Portable monitoring devices based on Inertial Measurement Units (IMUs) have the potential to serve as quantitative assessments of human movement. This article proposes a new method to identify the optimal placements of the IMUs and quantify the smoothness of the gait. First, it identifies gait events: foot-strike (FS) and foot-off (FO).
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January 2025
Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.
Parkinson's disease (PD) is characterized by a slow, short-stepping, shuffling gait pattern caused by a combination of motor control limitations due to a reduction in dopaminergic neurons. Gait disorders are indicators of global health, cognitive status, and risk of falls and increase with disease progression. Therefore, the use of quantitative information on the gait mechanisms of PD patients is a promising approach, particularly for monitoring gait disorders and potentially informing therapeutic interventions, though it is not yet a well-established tool for early diagnosis or direct assessment of disease progression.
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January 2025
German Center for Vertigo and Balance Disorders (DSGZ), LMU University Hospital, LMU Munich, 81377 Munich, Germany.
Instrumented gait analysis is widely used in clinical settings for the early detection of neurological disorders, monitoring disease progression, and evaluating fall risk. However, the gold-standard marker-based 3D motion analysis is limited by high time and personnel demands. Advances in computer vision now enable markerless whole-body tracking with high accuracy.
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