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313 results for “locomotion”
Related with: Long-short term memory prediction of user's locomotion in Virtual Reality publication (Dataset)
<p>Dataset: Captured motion data from 44 users.</p> <p>Scenes:</p> <p>SL -> Scene Lab.</p> <p>SR -> Escape Room.</p> <p>MF -> Shooter forest.</p> <p>Since it is recorded inside a game engine and all records take place inside their processing, the timestamp is written down for each register (Time_sice_startup field). Additionally, the anonymized identification of the user is recorded (User field).</p> <p>The dataset includes the following characteristics for Oculus Quest 2 HMD and each controller.</p> <ul> <li> DevicePosition (x, y, z): Position recorded.</li> <li> DeviceRotation (w, x, y, z): Rotation expressed with a quaternion.</li> <li> Forward (x, y, z): The unit vector that points to the specific device in the forward direction used in our new model. It can also be obtained by rotating $(0,0,1)$ with the quaternion.</li> <li> DeviceVelocity (x, y, z): Linear velocity of that device in that frame. It represents the rate of change in position.</li> <li> DeviceAcceleration (x, y, z): Linear acceleration of that device in that frame.</li> <li> DeviceAngularVelocity (x, y, z): The angular velocity vector in that frame of the device is measured in radians per second.</li> <li> DeviceAngularAcceleration (x, y, z): The angular acceleration at that frame. </li> </ul> <p>Also for each goal in the scene:</p> <ul> <li> GoalName (x, y, z): Position of that goal. If the element is static, the same position will always be recorded.</li> <li> GoalName_Quat (w, x, y, z): As in the previously defined fields, a rotation is expressed as a quaternion.</li> <li> GoalName_LocalScale (x, y, z): Scale of that element locally related to its parent in the hierarchy. They have no relatives in their hierarchy, so it is the real scale.</li> </ul>
Data from: Frog limbs in deep time: is jumping locomotion at the roots of the anuran Bauplan?
<p><span>The unique body plan of frogs (Lissamphibia: Anura) has been largely conserved from at least 200 Myr and its evolution from a more generalized tetrapod condition is still poorly understood, in part due to the scarce early fossil record of Salientia, the anuran total-group. The origin of the anuran Bauplan has been classically explained as an adaptation to jumping, but recent studies incorporating new data in a phylogenetic context have challenged the popular jumping hypothesis. Here we revisit and test this hypothesis from a palaeobiological perspective by integrating limb data from a wide range of extant and fossil frogs. We first explored the evolution of limb proportions from the Jurassic to the Paleogene to understand when the present limb diversity originated and whether, and to what extent, limb proportions have been conserved over the last 200 Myr. We then inferred the locomotor capabilities of extinct species by phylogenetic flexible discriminant analysis and, from these inferences, we studied the locomotor diversity of frogs over geological time and reconstructed the ancestral state for frog-like salientians. The evolution of limb proportions is characterized by an early diversification that was underway in the Jurassic, followed by a repeated convergence over a limited area of the morphospace that was already explored by the Early Cretaceous. In agreement with this early limb diversity, the Jurassic stem species were also locomotory diverse and their inferred locomotor modes do not support the jumping hypothesis. We propose that the patterns found herein of repeated convergent evolution of both limb proportions and locomotor capabilities over geological time hamper any attempt to confidently infer the ancestral locomotion mode and, therefore, it might be time to start focusing on other hypotheses on the origin of the anuran Bauplan that are not related to locomotion.</span></p>
Fig. 5 in The origin of ammonoid locomotion
Fig. 5. Changes in the orientation of the aperture of the adult conchs of ten representative Early and Middle Devonian ammonoids and Recent Nautilus through phylogeny (Erbenoceras, Mimosphinctes, Convoluticeras, Mimagoniatites, Agoniatites, Ponticeras, Cabrieroceras, Holzapfeloceras, Pharciceras). The two graphs on the left are based on diagrams figured by Saunders and Shapiro (1985) and Okamoto (1996). Comments on the modifications of these graphs are given in Klug (2001) and Korn and Klug (2003). Shell thickness is impossible to determine in most Early and Middle Devonian ammonoids and thus the lines of correlation between WER, BCL, and OA are printed as broad lines in the graphs. Note the shift of the orientation of the aperture from oblique to more or less horizontal in the agoniatitid, anarcestid, and tornoceratid lineages. In the agoniatitid lineage (E, F), the horizontal position was achieved by an increase in whorl expansion rate (relatively short body chambers) compared to A and B. In the anarcestid lineage (G, I, K), the body chamber lengths first increased in the progress of evolution and subsequently decreased again, leading to moderate body chamber lengths (K, H) and consequently more or less horizontal apertures. The positions of Erbenoceras (A) and Mimosphinctes (B) are shown in grey because in their cases, the orientation of the aperture does not correlate with the body chamber length and thus whorl expansion rate, as it is the case for advolute, evolute, and involute species.
Fig. 2 in The origin of ammonoid locomotion
Fig. 2. Phylogenetic change in orientation of the conchs and swimming velocity of Bactritida and primitive Ammonoidea. Outlines of the conchs of one bactritid and nine ammonoids from the Early and Middle Devonian with body chamber lengths (BCL), orientation of the aperture (OA), and relative swimming speed. Centre of gravity is indicated by a cross and the centre of buoyancy by a circle (for further explanations see Fig. 1).
Fig. 1 in The origin of ammonoid locomotion
Fig. 1. Forces operating on ammonoids during swimming, parameters, and terminology. A. Forces operating on ammonoids during swimming (modified from Jacobs and Chamberlain 1996). The thrust force produced by the jet which is expelled by the hyponome acts on the centre of gravity. This causes an oblique downward momentum which is opposed by the restorative moment (resulting from buoyancy and gravity) and the drag. At relatively high velocities, this might result in a fairly stable horizontal movement in some derived ammonoids. B. Angles of the body chamber length and of the orientation of the aperture. C. Terminology.
Data from: Arm waving in stylophoran echinoderms: three-dimensional mobility analysis illuminates cornute locomotion
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Data for: Mobility of the human foot's medial arch helps enables upright bipedal locomotion
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Kinematic data and mathematical modeling of sea star locomotion
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Foothold selection during locomotion in uneven terrain: Results from the integration of eye tracking, motion capture, and photogrammetry
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Data from: Frog limbs in deep time: is jumping locomotion at the roots of the anuran Bauplan?
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Comparative analysis of a geometric and an adhesive righting strategy against toppling in inclined hexapedal locomotion
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Mantis shrimp locomotion: coordination and variation of hybrid metachronal swimming
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Data from: Immune challenge affects risk sensitivity and locomotion in mosquitofish (Gambusia holbrooki)
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Data from: Behavior shapes retinal motion statistics during natural locomotion
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Locomotion and paleoclimate explain the re-evolution of quadrupedal body form in Brachymeles lizards
<p>Evolutionary reversals, including re-evolution of lost structures, are commonly found in phylogenetic studies. However, we lack an understanding of how these reversals happen mechanistically. A snake-like body form has evolved many times in vertebrates, and occasionally, a quadrupedal form has re-evolved, including in <i>Brachymeles</i> lizards. We use body form and locomotion data for species ranging from snake-like to quadrupedal to address how a quadrupedal form could re-evolve. We show that large, quadrupedal species are faster at burying and surface locomotion than snake-like species, indicating a lack of expected performance trade-off. Species with limbs use them while burying, suggesting that limbs are useful for burying in wet, packed substrates. Paleoclimatological data suggest that <i>Brachymeles</i> originally evolved a snake-like form under a drier climate likely with soil<strike> </strike>in which it was easier to dig. The quadrupedal clade evolved as the climate became humid, where limbs and large size facilitated fossorial locomotion in packed soils.</p>
Raw data accompanying: Ground reaction forces in monitor lizards (Varanidae) and the scaling of locomotion in sprawling tetrapods
<p>Geometric scaling predicts a major challenge for legged, terrestrial locomotion.<b> </b>Locomotor support requirements scale identically with body mass (α M<sup>1</sup>), while force generation capacity should scale α M<sup>2/3</sup> as it depends on muscle cross-sectional area. Mammals compensate with more upright limb postures at larger sizes, but it remains unknown how sprawling tetrapods deal with this challenge. Varanid lizards are an ideal group to address this question because they cover an enormous body size range while maintaining a similar bent-limb posture and body proportions. This study reports the scaling of ground reaction forces and duty factor for varanid lizards ranging from 7 g 37 kg. Impulses (force x time) scaled roughly as predicted by the inverted pendulum model (α M<sup>0.99-1.34</sup>) while peak forces (α M<sup>0.73-1.00</sup>) scaled higher than expected. Duty factor scaled α M<sup>0.04 </sup>and was higher for the hindlimb than the forelimb. The proportion of vertical impulse to total impulse increased with body size, and impulses decreased while peak forces increased with speed. These results provide valuable data into how locomotor forces vary with body size and suggest how other, extinct, sprawling tetrapods may have dealt with the biomechanical challenges associated with generating sufficient locomotor forces at larger body sizes.</p>
Human locomotion dataset
<p>The zip file contains 128 npy files. Each npy file is a python numpy array file that contains one dictionary with the following keys: ['info', 'emg_r', 'kinematic_r', 'kinematic_l', 'emg_l'].</p> <p><strong>info</strong>: Is a pandas dataframe with the following columns.</p> <p>file_name ⟶ refers to subject ID</p> <p>fs_emg (Hz) ⟶ refers to sample frequency of EMG data</p> <p>fs_kin (Hz) ⟶ refers to sample frequency of kinematic data</p> <p>mass (kg) ⟶ subject mass in kg</p> <p>trailing_leg ⟶ leg used as trailing leg during unilateral skipping. right (<em>r</em>) or left (<em>l</em>)</p> <p>vel (km/h) ⟶ speed on km/h</p> <p><strong>emg_r</strong>: List of <em>n</em> elements. <em>n </em>is equivalent to the number of strides registered. Each element of the list present a DataFrame containig 14 EMG signals of right and left legs corresponding to a one stride segmented using the heel strike of the right leg.</p> <p><strong>emg_l</strong>: List of <em>n</em> elements. <em>n </em>is equivalent to the number of strides registered. Each element of the list present a DataFrame containig 14 EMG signals of right and left legs corresponding to a one stride segmented using the heel strike of the left leg.</p> <p><strong>kinematic_r</strong>: List of <em>n</em> elements. <em>n </em>is equivalent to the number of strides registered. Each element of the list present a DataFrame containig <em>x</em>, <em>y </em>and <em>z</em> coordinates of 18 reflective markers used in a MOCAP system during one stride identified using the heel strike of the right leg.</p> <p><strong>kinematic_l</strong>: List of <em>n</em> elements. <em>n </em>is equivalent to the number of strides registered. Each element of the list present a DataFrame containig <em>x</em>, <em>y </em>and <em>z</em> coordinates of 18 reflective markers used in a MOCAP system during one stride identified using the heel strike of the left leg.</p> <p> </p> <pre><code class="language-python">#example of use data = np.load('IT_R_110.npy',allow_pickle=True,encoding='latin1').item() #load a file emg5r = data['emg_r'][5] #Load all emg data of the 5th stride defined from right leg heel strike kinematic5l = data['kinematic_l'][5] #Load all kinematic data of the 5th stride defined from right leg heel strike</code></pre> <p> </p>
STM, locomotion and survival raw data for: A neural m6A/Ythdf pathway is required for learning and memory in Drosophila
<p>The files contain raw and summarized data files for the STM, locomotion and survival experiments published in the manuscript entitled " A neural m6A/Ythdf pathway is required for learning and memory in Drosophila". Instructions on how to process data and further information is found in the "summary" file.<br> </p>
Optimal searching behaviour generated intrinsically by the central pattern generator for locomotion
<p>Efficient searching for resources such as food by animals is key to their survival. It has been proposed that diverse animals from insects to sharks and humans adopt searching patterns that resemble a simple Lévy random walk, which is theoretically optimal for 'blind foragers' to locate sparse, patchy resources. To test if such patterns are generated intrinsically, or arise via environmental interactions, we tracked free-moving <i>Drosophila</i> larvae with (and without) blocked synaptic activity in the brain, suboesophageal ganglion (SOG) and sensory neurons. In brain-blocked larvae we found that extended substrate exploration emerges as multi-scale movement paths similar to truncated Lévy walks. Strikingly, power-law exponents of brain/SOG/sensory-blocked larvae averaged 1.96, close to a theoretical optimum (µ = 2.0) for locating sparse resources. Thus, efficient spatial exploration can emerge from autonomous patterns in neural activity. Our results provide the strongest evidence so far for the intrinsic generation of Lévy-like movement patterns.</p>
The interplay between habitat use, morphology and locomotion in subterranean crustaceans of the genus Niphargus
<p>Locomotion is an important, fitness-related functional trait. Environment selects for type of locomotion and shapes the morphology of locomotion-related traits such as body size and appendages. In subterranean aquatic arthropods, these traits are subjected to multiple, at times opposing selection pressures. Darkness selects for enhanced mechano- and chemosensory systems and hence elongation of appendages. Conversely, water currents have been shown to favor short appendages. However, no study has addressed the variation in locomotion of invertebrates inhabiting cave streams and cave lakes, or questioned the relationship between species' morphology and locomotion. To fill this knowledge gap, we studied the interplay between habitat use, morphology and locomotion in amphipods of the subterranean genus Niphargus. Previous studies showed that lake and stream species differ in morphology. Namely, lake species are large, stout and long-legged, whereas stream species are small, slender and short-legged. We here compared locomotion mode and speed between three lake and five stream species. In addition, we tested whether morphology predicts locomotion. We found that the stream species lie on their body sides and move using slow crawling or tail-flipping. The species inhabiting lakes move comparably faster, and use a variety of locomotion modes. Noteworthy, one of the lake species almost exclusively moves in an upright or semi-upright position that resembles walking. Body size and relative length of appendages predict locomotion mode and speed in all species. We propose that integrating locomotion in the studies of subterranean species might improve our understanding of their morphological evolution. </p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.