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The latest advances in the molecular diagnostics associated with gastric cancer malignancy.
Walking and running, the two most basic and functional gait modes, have been often addressed through EMG, kinematics and biomechanical modelling, however, there is no consensus in the literature on which factors trigger the transition from walking to running. Ankle plantarflexors and dorsiflexor were found to play an important role in gait transition due to higher muscular activation to propel the body forward to run. We tested these muscles activation during walking and running at the same speeds, through a musculoskeletal model derived from subjects' kinematic and kinetic data. Compared to EMG data frequently reported in the literature, the results yielded similar activation patterns for all muscles analyzed. Besides, across speeds, dorsiflexor activation kept increasing in walking, especially after PTS (preferred transition speed), which may indicate its contribution to gait transition, as an effort to bring the foot forward to keep up with the unnatural condition of walking at high speeds.Pain in the lower back is frequent problem for most individuals with transfemoral amputation, which limits their overall mobility and quality of life. While the underlying root causes of back pain are multifactorial, a contributing factor is the mechanical loading environment within the lumbopelvic joint. Specifically, this study aims to explore the upstream effects amputation has on the mechanical loading environment of the lumbopelvic joint using a 3D musculoskeletal model of transfemoral amputation. A generic musculoskeletal model was altered to represent a transfemoral amputation. Muscle parameters were adjusted to represent a myodesis amputation surgery that preserved musculotendon tension in a neutral anatomical pose. The model contained a total of 28 degrees of freedom and 76 muscles spanning the lower-limb and torso. In forward dynamics simulations, generalized external forces were applied to the distal end of the residual limb at a series of directions. Axial, oblique and transverse 10 N end-limb loay, which intend to maintain anatomical alignment may have beneficial upstream effects for the patients during locomotion. Given the prevalence of lower back pain in individuals with transfemoral amputation, teasing out the causes of lower back pain could bring relief to a population that struggles with community independence.Motion capture systems are extensively used to track human movement to study healthy and pathological movements, allowing for objective diagnosis and effective therapy of conditions that affect our motor system. Current motion capture systems typically require marker placements which is cumbersome and can lead to contrived movements.Here, we describe and evaluate our developed markerless and modular multi-camera motion capture system to record human movements in 3D. The system consists of several interconnected single-board microcomputers, each coupled to a camera (i.e., the camera modules), and one additional microcomputer, which acts as the controller. The system allows for integration with upcoming machine-learning techniques, such as DeepLabCut and AniPose. These tools convert the video frames into virtual marker trajectories and provide input for further biomechanical analysis.The system obtains a frame rate of 40 Hz with a sub-millisecond synchronization between the camera modules. We evaluated the system by recording index finger movement using six camera modules. The recordings were converted via trajectories of the bony segments into finger joint angles. The retrieved finger joint angles were compared to a marker-based system resulting in a root-mean-square error of 7.5 degrees difference for a full range metacarpophalangeal joint motion.Our system allows for out-of-the-lab motion capture studies while eliminating the need for reflective markers. The setup is modular by design, enabling various configurations for both coarse and fine movement studies, allowing for machine learning integration to automatically label the data. Although we compared our system for a small movement, this method can also be extended to full-body experiments in larger volumes.The objective of the current investigation was to examine the presence, absence or alteration of fundamental postural control strategies in individuals post traumatic brain injury (TBI) in response to base of support perturbations in the anterior-posterior (AP) direction. Four age-matched healthy controls (age 46.50 ± 5.45 years) and four individuals diagnosed with TBI (age 48.50 ± 9.47 years, time since injury 6.02 ± 4.47 years) performed standing on instrumented balance platform with integrated force plates while 3D motion capture data was collected at 60 Hz. The platform was programmed to move in the AP direction, during a sequence of 5 perturbations delivered in a sinusoidal pattern at a frequency of 1 Hz, with decreasing amplitudes of 10, 8, 6, 4, and 2 mm respectively. The sagittal plane peak-to-peak range and root mean square (RMS) of the hip, knee, and ankle joint angles during the 5 seconds of perturbation were computed from optical motion capture data. The TBI group had a higher mean range (5.17 ± 1.91°) about the ankle compared to the HC group (4.17 ± 0.81°) for the 10mm perturbation, but their mean range was smaller than the HCs for the other 4 conditions. About the hip, the TBI group's mean range was larger than the HC's for all conditions. For both groups, the mean range decreased with perturbation amplitude for all conditions. The TBI group showed larger changes in mean range and RMS values as the amplitude of the perturbation changed, while the HC group showed smaller intertrial changes. The results suggest that the TBI group was substantially more reliant on the hip strategy to maintain balance during the perturbations and this reliance was well linked with perturbation amplitude.Clinical Relevance- Existing information regarding changes in postural control strategies in individuals post TBI is limited. The current work demonstrates lower limb kinematic differences between HC and TBI and some preliminary evidence on increased hip movement in the TBI group.The purpose of this study was to understand how the form (i.e., shape and presence of underlying soft tissue) of residual limb tissue influences limb function and comfort for individuals with transfemoral limb loss. Specifically, there exist surgical techniques that are frequently applied to the lower limbs of individuals to reduce an excessive soft tissue envelope. However, the clinical goals are frequently from a cosmetic perspective and are applied most commonly to individuals who are obese and not necessarily those with limb loss. For specific individuals with transfemoral limb loss, there likely exist limb shapes and distributions of underlying soft tissue that more optimally engage with lower-limb prostheses. Based on recent experimental findings, optimizing the limb and its physical connection to lower-limb prostheses, may have equivalent if not greater impact on user outcomes than selection of prosthetic components. This study develops and tests a method for informing optimal designs of the residual l.Clinical Relevance-Prosthetic technology advancement within the last decade has heightened the hopes of individuals with amputation. However, how these devices integrate to their human users is non-trivial and can curtail these advancements. click here Tools are needed to inform how residual limb itself can be optimized to better integrate with prostheses.Microinjection is a widely used technique employed by biologists with applications in transgenesis, cryopreservation, mutagenesis, labeling/dye injection and in-vitro fertilization. However, microinjection is an extremely laborious manual procedure, which makes it a critical bottleneck in the field and thus ripe for automation. Here, we present a computer-guided robot that automates the targeted microinjection of Drosophila melanogaster and zebrafish (Danio rerio) embryos, two important model organisms in biological research. The robot uses a series of cameras to image an agar plate containing embryos at multiple magnifications and perspectives. This imaging is combined with machine learning and computer vision algorithms to pinpoint a location on the embryo for targeted microinjection with microscale precision. We demonstrate the utility of this microinjection robot to successfully microinject Drosophila melanogaster and zebrafish embryos. Results obtained indicate that the robotic microinjection approach can significantly increase the throughput of microinjection as compared to manual microinjection while maintaining survival rates comparable to human operators. In the future, this robotic platform can be used to perform high throughput microinjection experiments and can be extended to automatically microinject a host of organisms such as roundworms (Caenorhabditis elegans), mosquito (Culicidae) embryos, sea urchins (Echinoidea) and frog (Xenopus) oocytes.The use of actuated exoskeletons in gait rehabilitation increased significantly in recent years. Although most of these exoskeletons are produced with a generic cuff, at the foot and ankle there are a lot of bony prominences and a limited amount of soft tissue, making it less comfortable . Furthermore, a proper alignment of the actuation systems is essential for the correct functioning of the exoskeleton. Therefore, we propose a digital workflow for the design of bespoke cuffs as interface parts of a powered ankle foot orthoses (PAFO). Moreover, this digital workflow permits the creation of axis and points of reference for the anatomical features which allows not only for the creation of custom-made cuffs but also for the integration and alignment of the PAFO mechanical components and actuation unit.Functional medical imaging systems can provide insights into brain activity during various tasks, but most current imaging systems are bulky devices that are not compatible with many human movements. Our motivating application is to perform Positron Emission Tomography (PET) imaging of subjects during sitting, upright standing and locomotion studies on a treadmill. The proposed long-term solution is to construct a robotic system that can support an imaging system surrounding the subject's head, and then move the system to accommodate natural motion. This paper presents the first steps toward this approach, which are to analyze human head motion, determine initial design parameters for the robotic system, and verify the concept in simulation.Previous studies have shown that athletic jump mechanics assessments are valuable tools for identifying indicators of an individual's anterior cruciate ligament injury risk. These assessments, such as the drop jump test, often relied on camera systems or sensors that are not always accessible nor practical for screening individuals in a sports setting. As human pose estimation deep learning models improve, we envision transitioning biometrical assessments to mobile devices. As such, here we have addressed two of the most preclusive hindrances of the current state-of-the-art models accuracy of the lower limb joint prediction and the slow run-time of in-the-wild inference. We tackle the issue of accuracy by adding a post-processing step that is compatible with all inference methods that outputs 3D key points. Additionally, to overcome the lengthy inference rate, we propose a depth estimation method that runs in real-time and can function with any 2D human pose estimation model that outputs COCO key points. Our solution, paired with a state-of-the-art model for 3D human pose estimation, significantly increased lower-limb positional accuracy.
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