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282 results for “Exoskeleton”
Ocean acidification alters properties of the exoskeleton in adult tanner crabs, Chionoecetes bairdi
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Surmounting the ceiling effect of motor expertise by novel sensory experience with a hand exoskeleton
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Estimating human joint moments unifies exoskeleton control and reduces user effort
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Large and exaggerated sexually selected weapons comprise high proportions of metabolically inexpensive exoskeleton
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Data from: Exoskeleton ageing and its relation to longevity and fecundity in female Australian Leaf Insects (Phyllium monteithi)
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A versatile knee exoskeleton mitigates quadriceps fatigue in lifting, lowering, and carrying tasks
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Amphibalanus amphitrite begins exoskeleton mineralization within 48-hours of metamorphosis
<p>Barnacles are ancient arthropods that, as adults, are surrounded by a hard, mineralized, outer shell that the organism produces for protection. While extensive research has been conducted on the glue-like cement that barnacles use to adhere to a surfaces, less is known about the barnacle exoskeleton, especially the process by which the barnacle exoskeleton is formed. Here we present data exploring the changes that occur as the barnacle cyprid undergoes metamorphosis to become a sessile juvenile with a mineralized exoskeleton. Scanning electron microscope (SEM) data show dramatic morphological changes in the barnacle exoskeleton following metamorphosis. Energy dispersive x-ray spectroscopy (EDS) indicates a small amount of calcium (8%) 1-hour post-metamorphosis that steadily increases to 28% by 2-days following metamorphosis. Raman spectroscopy indicates calcite in the exoskeleton of a barnacle 2-days following metamorphosis and no detectable calcium carbonate in exoskeletons up to 3-hours post-metamorphosis. Confocal microscopy indicates during this 2-day period, barnacle base plate area and height increases rapidly (0.001 mm<sup>2</sup>/hr and 0.30 µm/hr, respectively). These results provide critical information into the early life stages of the barnacle, which will be important for developing an understanding of how ocean acidification might impact the calcification process of the barnacle exoskeleton.</p>
Data from: Muscle-tendon mechanics explain unexpected effects of exoskeleton assistance on metabolic rate during walking
The goal of this study was to gain insight into how ankle exoskeletons affect the behavior of the plantarflexor muscles during walking. Using data from previous experiments, we performed electromyography-driven simulations of musculoskeletal dynamics to explore how changes in exoskeleton assistance affected plantarflexor muscle–tendon mechanics, particularly for the soleus. We used a model of muscle energy consumption to estimate individual muscle metabolic rate. As average exoskeleton torque was increased, while no net exoskeleton work was provided, a reduction in tendon recoil led to an increase in positive mechanical work performed by the soleus muscle fibers. As net exoskeleton work was increased, both soleus muscle fiber force and positive mechanical work decreased. Trends in the sum of the metabolic rates of the simulated muscles correlated well with trends in experimentally observed whole-body metabolic rate (R2=0.9), providing confidence in our model estimates. Our simulation results suggest that different exoskeleton behaviors can alter the functioning of the muscles and tendons acting at the assisted joint. Furthermore, our results support the idea that the series tendon helps reduce positive work done by the muscle fibers by storing and returning energy elastically. We expect the results from this study to promote the use of electromyography-driven simulations to gain insight into the operation of muscle–tendon units and to guide the design and control of assistive devices.
Figure 1. A in Evolution of cheaper workers in ants: comparative study of exoskeleton thickness
Figure 1. A, longitudinal section through prothorax of Proceratium japonicum, showing the plane of cross-sectioning (arrow); B, cross-section where thickness was measured (br: brain, lg: labial gland, mf: muscle fibres, ptg: prothoracic ganglion, sog: suboesophageal ganglion).
Figure 5 in Evolution of cheaper workers in ants: comparative study of exoskeleton thickness
Figure 5. Cross-sections through prothorax of smallest worker (head width 0.56 mm) of Dorylus orientalis (A) and of larger conspecific workers (B – E) with indication of head width (HW). Note increase of cuticle thickness with increasing worker size. All photographs at same magnification (oe: oesophagus, lg: labial gland, mf: muscle fibres, ptg: prothoracic ganglion).
Figure 4 in Evolution of cheaper workers in ants: comparative study of exoskeleton thickness
Figure 4. Cross-sections through pronotal cuticle in various species (formicoids on left, poneroids on right), comparing workers of similar head widths in each row (AB, CD, etc.). Head width (HW, in millimetres) increases from upper to lower rows. All photographs at same magnification.
Figure 3 in Evolution of cheaper workers in ants: comparative study of exoskeleton thickness
Figure 3. Ratio between cuticle thickness (prothorax) and head width in poneroids (black) and formicoids (grey). Medians, quartiles and ranges are shown.
Figure 2 in Evolution of cheaper workers in ants: comparative study of exoskeleton thickness
Figure 2. Allometry between cuticle thickness and head width across nine ant subfamilies. Poneroid (black) and formicoid (grey) subfamilies are shown.
Error Related Potential in motion to stop the gait with a lower limb exoskeleton
<h2>Description</h2> <p>This dataset contains EEG signals from experiments designed to evoke Error-Related Potentials (ErrP) in motion, during gait using a Brain-Computer Interface (BCI) to control a lower limb exoskeleton. The ErrP is elicited using Tactile stimuli that activates while walking and, once it deactivates, the exoskeleton stops.</p> <p>The experiment consists in a circuit with color marks on the floor, with 4 regions: 2 Gait Regions, where the subject has to keep walking, and 2 Stop Regions, where the subject tries to stop the exoskeleton using motor imagination. At the beginning of each repetition, the exoskeleton activates automatically and, while walking, they must perform two mental tasks: Relax (R), at Gair Regions to keep walking, and Motor Imagery (I) of stop, at Stop Regions to deactivate the exoskeleton and stop. These tasks can be executed correctly (RC, IC) or incorrectly (RE, IE). Since it is an open-loop experiment and the subject is never in control of the system, tasks are correctly performed 70% of the time (RC, IC), while the remaining 30% are incorrect (RE, IE). </p> <p>For instance, one the subject enters in the Gait Region and maintains an idle state while walking to continue with the gait. In RC (Relax Correct) they cross the region without any stop, but in RE (Relax Error) the feedback activates and the exoskeleton erroneously stops. Conversely, in IC (Imagination Correct, the subject imagines the sensation of stop walking in their muscles, and the feeedback activates and the exoskeleton stops the gait, but during IE (Imagination Error), they walk through the region and the exoskeleton does not stop despite the motor imagery. Therefore, ErrP is elicited by the stimuli in RE and can be compared with the absence of ErrP (NoErrP) in IC, where the stimulus activates but should not evoke an error.</p> <p>Each subject participates in three sessions, consisting of 20 trials. In each trial, 4 mental tasks are performed, 2 Relax and 2 Imagination, interleaved. Thus, in each session, a total of 12 ErrP and 28 NoErrP signals are recorded in the dataset. Except subject R06, who only participated in 2 sessions. </p> <p> </p> <h2>Data information</h2> <p>A trial consists of a Matlab structure that stores all information related to the trial experiment. </p> <ul> <li><em>data_EEG</em>: Original EEG signals recorded with a sampling rate of 250Hz, where each row is a channel (1-28 EEG, 29-32 EOG, 33-35 inertial electrodes).</li> <li><em>data_preprocessed_EEG</em>: Matrix that contains the preprocessed signals for each channel. Rows 1-35 are the original signals and then, the preprocessed signals in blocks of 35. Find the indexes of each filter in <em>session.conf.info.preprocessingSteps.ListPreprocessingSteps</em>.</li> <li><em>trigger_EEG</em>: Information related to signal quality and missing data while recording. </li> <li><em>data_EXO</em>: Exoskeleton recorded data with a sampling rate of 250Hz.</li> <li><em>data_preprocessed_EXO: </em>The same data recorded by the exoskeleton in <em>data_EXO</em>, since it does not require the application of any filter.</li> <li><em>trigger_EXO</em>: Empty vector. </li> <li><em>data_Actuators</em>: Arduino response when activates (1) and deactivates (-1) the feedback. </li> <li><em>data_preprocessed_Actuators: </em>The same Arduino resposes recorded in <em>data_Actuators</em>, because it does not require any filter application. </li> <li><em>trigger_Actuators</em>: Empty vector. </li> <li><em>task_EEG</em>: Vector that associates a task to each signal sample.</li> <li><em>task_index_EEG</em>: Zero vector with negative peaks at the samples indicating the start of a task. Each peak decrements by one unit with each task. </li> <li><em>task_order_EEG</em>: Vector that increments a unit with each task change. </li> <li><em>event_EEG</em>: Vector of commands to activate (1) and deactivate (-1) the feedback in Arduino. </li> <li><em>conf</em>: Configuration employed for data acquisition and preprocessing. <ul> <li><em>acquisition</em>: User and signals acquisition information. <ul> <li><em>user_code</em>: User code name.</li> <li><em>feedback</em>: Trial in openloop (User do not have control of the system).</li> <li><em>feedbackErrP</em>: Feedback type employed during the trial.</li> <li><em>readfile</em>: Path to read files after its acquisition.</li> <li><em>saveSession_Script</em>: Script used to save the recorded data.</li> <li><em>writeResults</em>: Path to save the recorded data.</li> <li><em>device</em>: List of connected devices during the trial and their related information, such as name, sampling rate, connection order, etc. </li> <li><em>task</em>: Information about tasks occurring during the trial. <ul> <li><em>task_list</em>: Decodes tasks numbers. The first number is the global task/mental activity, the second one is the physiological state of the user, and the third one indicates the task version (preparation or basic task).</li> <li><em>sequence_tasks</em>: List of tasks in order of execution.</li> <li><em>sequence_times</em>: List with the duration of each task in the sequence.</li> </ul> </li> <li><em>deviceOutput</em>: List of devices that receive commands to execute orders, such as the exoskeleton for walking and stopping and the VibroLed for turning feeedback on and off.</li> <li><em>eye_index</em>: Indexes of EOG electrodes.</li> <li><em>EEG_index</em>: Indexes of EEG electrodes.</li> <li><em>inertial_index</em>: Indexes of inertial electrodes.</li> <li><em>file_name</em>: Trial name.</li> <li><em>num_epochs</em>: Number of epochs within a trial. An epoch is the half of sampling rate (250Hz), this means that an epoch has a duration of 0.5s and 125 samples. </li> </ul> </li> <li><em>preadjustment</em>: Empty list. </li> <li><em>preprocessing</em>: Information of the preprocessing filters, parameters and order of application.</li> <li><em>processing</em>: Not necessary for this analysis. </li> <li><em>static</em>: Information used internally by the architecture for its correct operation.</li> <li><em>info</em>: Important information about filters, their order and indexes in <em>data_processed_EEG</em>.</li> </ul> </li> <li><em>times</em>: Struct with information of the devices synchronization and preprocessing times.</li> <li><em>times_processing</em>: Processing duration times. </li> </ul>
An Exoskeleton System using a 3-UPU Spherical Parallel Manipulator for Rehabilitation in Stroke Patients
<p>One of the important branches of medical robotics is rehabilitation robotics. A 3-UPU spherical parallel manipulator is designed and controlled to perform wrist extension, flexion, radial deviation and ulnar deviation motions in stroke-affected patients. This exoskeleton robot produces spherical motion about a fixed center. In order to produce the rotational motion, the robot is designed based on certain geometric and structural conditions. Using the inverse kinematics solution the 3-UPU robot is controlled to perform rehabilitation task. The robot parts are manufactured using additive manufacturing technology. The manufacturing tolerance in universal joints have been identified. There is always a mystery behind the singularity of this robot, which describes the manner in which it will collapse in its home position. Thus, the robot is designed and developed in such a way that it can be effectively used at home position for hand rehabilitation.</p>
Figure 2 in An evolutionary comparative analysis of the medusozoan (Cnidaria) exoskeleton
Figure 2. Schematic of the exoskeleton in fossil groups in Medusozoa. A, Conulatae: A1, hypothetical Conulatae, general morphology with main features (modified from Leme et al., 2004); A2, lamellar ornament details of the exoskeleton. B, Corumbella: B1, Corumbella werneri; B2, oral region; B3, cross-section of the exoskeleton with microlamellae; B4, lamellar detail showing pores (brown arrow) and papillae (red arrow); B5, underside view of two of the polygonal plates that comprise the lamellae with papillae (shown as red 'u'); B6, topside view of the same plates as in B5, showing pores (shown as brown oval) (modified from Pacheco et al., 2011). Colour-coded chemical composition and structure of the exoskeleton: yellow, calcium phosphate; orange, calcium carbonate.
Figure 1 in An evolutionary comparative analysis of the medusozoan (Cnidaria) exoskeleton
Figure 1. Model of the chitin-protein (corneous) exoskeleton and cell tissues in Medusozoa. Red line refers to the exoskeleton, yellow circles are carbon atoms, blue circles hydrogen, purple circles oxygen, and cyan circle N-acetyl group.
Figure 3 in An evolutionary comparative analysis of the medusozoan (Cnidaria) exoskeleton
Figure 3. Schematic view of the exoskeleton in extant groups of Medusozoa. A, Staurozoa, Stauromedusae, Haliclystus; B, C, Scyphozoa: B, Coronatae, C, Discomedusae; D, Cubozoa, Carybdeida; E–I, Hydrozoa: E, Leptothecata, F, 'Anthoathecata', G, Hydridae, Hydra vulgaris, H, Millepora sp., I, Bimeria vestita. Chemical composition and structures of the exoskeleton indicated in different colours: red, chitin-protein; cyan, glycosaminoglycans; orange, calcium carbonate; green, glycosaminoglycan, chondroitin sulphate, and putative peroxidase proteins; p, podocyst.
Figure 4 in An evolutionary comparative analysis of the medusozoan (Cnidaria) exoskeleton
Figure 4. Phylogenetic hypothesis of the exoskeleton in Cnidaria, with fossil Medusozoa, with optimization for different skeleton types: calcareous, corneous, coriaceous; bilayered;? unknown, without exoskeleton. Skeleton composition: chitin, calcium carbonate, calcium phosphate, glycosaminoglycans (GAGs) and putative peroxidase proteins, chitin-protein and GAGs. Lineages are by colour: yellow, Anthozoa; orange, Staurozoa; green Cubozoa; purple, Scyphozoa; blue, Trachylina; dark green, Capitata; grey, Siphonophora; brown, Aplanulata; red, 'Anthoathecata'; cyan, Leptothecata. Numbers in parentheses indicate the total number of extant species, based on Daly et al. (2007) and Collins (2009). Solid bars indicate fossils, open squares do not have fossil records. Red circles indicate groups with internal, chitinous skeletons. This hypothesis combines the phylogeny in Collins et al. (2006) with, for the position of the Conulatae, Van Iten et al. (2006, 2014) and Cartwright et al. (2008). Hypothetical relations for Hydroidolina are based on unpublished data (M. M. Maronna & A. C. Marques). Images of fossils: 1, Cubozoa and Narcomedusae (Cartwright et al., 2007); 2, Conulatae (Van Iten et al., 2013a); 3, Pseudodiscophylum windermerensis (Fryer & Stanley, 2004); 4, Lepidopora sp. (modified from Cairns & Grant-Mackie, 1993); 5, Sinobryon elongatum (Balinski et al., 2014).
Upper Limb Task-Oriented Rehabilitation With Robotic Exoskeleton for Hemiparetic Stroke Patients
ClinicalTrials.gov study NCT03319992. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
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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.