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Movement

Movement refers to the physical displacement of a body or its parts through space.
It encompasses a wide range of activities, including locomotion, exercise, and rehabilitation.
Movement research focuses on understanding the underlying physiological, biomechanical, and neurological processes that govern human and animal motion.
This area of study has broad applications in fields such as sports science, physical therapy, and robotics, aiming to optimize performance, prevent injuries, and enhance quality of life.
Researchers in this domain leverge advanced tehnologies, like the AI-powered PubCompare.ai platform, to streamline their work and drive breakthroughs in movement science.

Most cited protocols related to «Movement»

Functional MRI Preprocessing Workflow

Cited 1506 times

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Publication 2011

bis(tri-n-hexylsiloxy)(2,3-naphthalocyaninato)silicon Brain fMRI Head Movements Movement Radionuclide Imaging Rage

Optimizing Eddy Current Correction for Diffusion MRI Data

Cited 566 times

For several of the data sets, the diffusion gradients are duplicated for opposing PE-directions. This offers a way to assess the performance of eddy and also to compare it to a commonly used existing method (eddy_correct in FSL) that uses FLIRT (Jenkinson and Smith, 2001 (link)), a 12-dof affine transformation and correlation ratio as a cost-function to register the diffusion weighted images to a b = 0 image. Two images acquired with the same diffusion gradient will have the same contrast and any difference between them should be due to differences in distortions and/or measurement error (noise). We therefore ran eddy separately on the data with the two different PE-directions and then calculated the sum-of-squared differences for paired diffusion weighted images.
Data acquired with different PE-directions also differ with respect to different susceptibility-induced distortions and if not corrected these would dominate any comparison between the images. We therefore used RGM and pairs of b = 0 (where there will be no eddy current-induced distortions) with different PE-directions to estimate the susceptibility-induced off-resonance field and applied that to the images using spline-interpolation and Jacobian modulation (see section Resampling the images). These “susceptibility-only corrected” pairs were the baseline against which the eddy and eddy_correct methods were compared. The eddy_correct method was modified to use spline interpolation and also to be able to incorporate the susceptibility-field from RGM so as to allow for a single resampling into a space corrected for susceptibility, eddy currents and subject movement in the same way that eddy does.
A series of tests was run on the FMRIB (data sets

A

and

B

) and the early HCP data (

C

) to evaluate different settings for the options in eddy. As described above these tests were performed by running eddy separately on the A → P and the P → A (or L → R and R → L in the case of the HCP 3 T data (

C

)) data and then compared pairwise to assess how well the correction worked. These settings were
Estimation of GP hyperparameters There are several different options for determining the hyperparameters for the Gaussian process that model the diffusion signal. These are maximum marginal likelihood (MML), leave-one-out cross validation (CV) and Geissers's surrogate predictive probability (GPP). For each method data was extracted from 1000 random brain voxels and used for the estimation. Note that this random voxel selection potentially introduces a run-to-run variability to the eddy results, but which can be turned off by specifying a seed at the command level.
Q-space smoothing The GP can be seen as a smoothing operation in Q-space. We tested different levels of increased smoothing by multiplying the error-variance estimates (hyperparameter of the GP) by values ranging from 1 (no additional smoothing) to 10.
Spatial smoothing Data and predictions were smoothed with a Gaussian filter with FWHM ranging from 0 to 5 mm. N.B. that the filtering is applied only during the estimation phase and not to the final resampled results.
EC model Different models for the EC-induced fields corresponding to first (four parameters), second (ten parameters) and third (20 parameters) order polynomials were tested. See Appendix A for a complete description of the different models.
Second level modeling The EC-parameters were fitted to a first or second order polynomial at the end of each iteration.
Joint modeling of multi-shell data When having multi-shell data one can either correct each shell independently or one can model (and correct) them all simultaneously. The latter option is potentially better because the Gaussian process is able to use data from one shell when making predictions about another shell (Andersson and Sotiropoulos, 2015 ). To test that, we corrected the HCP 3 T data (

C

) for each shell individually and also jointly for all four shells.

Andersson J.L, & Sotiropoulos S.N. (2016). An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage, 125, 1063-1078.

Publication 2016

Brain Diffusion Joints Movement Susceptibility, Disease Vibration

CryoEM Movie-Frame Defocus Refinement

Cited 564 times

One of the biggest advances in cryoEM recently is the invention of direct electron detectors which allow movie recording. Beam induced movement correction using movies has greatly improved the resolution of the final reconstruction (Bai et al., 2013 (link), Li et al., 2013 (link)). The movement in the X or Y direction of a micrograph is usually around several Ångstroms (e.g. 1–10 Å), while the Z-direction movement can be over a hundred Ångstroms (Russo and Passmore, 2014 (link)). Although the movement is dominantly in the Z-direction, the small movement in the XY plane severely affects the quality of cryoEM micrographs. Motion correction programs normally consider only the drift in the XY plane because the eucentric height of the object does not affect its ideal 2D projection. However, EM micrographs are modulated by CTF, which is sensitive to Z-height changes. Beam induced movement might change the CTF from frame to frame. A hundred Ångstrom movement is not a significant change even up to a 3 Å reconstruction, but Fig. 1 suggests it might help to improve a reconstruction close to 2 Å.
Accurate defocus refinement for movie frames is implemented in Gctf to deal with large movement in the Z-direction. Similar to local defocus refinement, movie defocus refinement is performed in two steps. First, global CTF parameters are determined for the averaged micrograph of motion-corrected movies. Then based on the global values, parameters for each frame are refined using an equally weighted average of adjacent frames (suggested 5–10) to reduce the noise. Two options are provided in Gctf: coherent averaging Eq. (8) or incoherent averaging Eq. (9).

| F_{i_{ca}} (\vec{s}) | = |\sum_{j = i - N / 2}^{i + N / 2} \frac{F_{j} (\vec{s})}{N}|

| F_{i_{ica}} (\vec{s}) | = \sum_{j = i - N / 2}^{i + N / 2} \frac{| F_{j} (\vec{s}) |}{N}

where

| F_{i_{ca}} (\vec{s}) |

represents the coherent averaging of

i_{th}

frame and

i_{th}

the incoherent averaging;

N

is the number of frames to be averaged.

, & Zhang K. (2016). Gctf: Real-time CTF determination and correction. Journal of Structural Biology, 193(1), 1-12.

Publication 2016

Cryoelectron Microscopy Electrons Movement Reading Frames Reconstructive Surgical Procedures

Suction Blister Induction and Wound Healing

Cited 418 times

A negative pressure instrument (Electronic Diversities, Finksburg, MD, USA) constructed to produce standard suction blisters upon application of negative pressure, was used on healthy skin (ex vivo: abdominal skin; in vivo: lower forearm). Subcutaneous fat was partially removed from ex vivo skin using a scissor. Subsequently, skin (10 × 10 cm²) was placed (not fixed, not kept in medium) on a styrofoam lid that was covered with aluminium foil to provide (at least partial) backpressure. Suction chambers with 5 openings (Ø = 5 mm) on the orifice plate were attached to skin, topped with a styrofoam lid and pressed with 1 kg weight in order to avoid movement of the plate. A pressure of 200–250 millimeter (mm) mercury (Hg) (ex vivo) or 150–200 mm Hg (in vivo) caused the skin to be drawn through the openings creating typical suction blisters of different size within 6–8 h (ex vivo) and 1–2 h (in vivo). Suction blister fluid (~110 µl/5 blisters) was collected using a syringe with a needle. Cells within the fluid were counted and placed on adhesion slides for staining and analysis. Blister roof epidermis was cut with a scissor, fixed with ice-cold acetone (10 minutes) and used for staining. For comparison and control, epidermal sheets were prepared from unwounded skin biopsy punches (Ø = 6 mm; 3.8% ammonium thiocyanate (Carl Roth GmbH + Co. KG, Germany) in PBS (Gibco, Thermo Fisher, Waltham, MA, USA), 1 h, 37 °C). Removal of the blister roof created a wound area. Biopsies (Ø = 6 mm) from wounded and unwounded areas were cultivated for 12 days in either duplicates or triplicates in 12 well culture plates and Dulbecco’s modified Eagle’s medium (DMEM) (Gibco) supplemented with 10% fetal bovine serum (FBS) (Gibco) and 1% penicillin-streptomycin (Gibco) and were cultured at the air-liquid interphase. Medium was changed every second day.

Rakita A., Nikolić N., Mildner M., Matiasek J, & Elbe-Bürger A. (2020). Re-epithelialization and immune cell behaviour in an ex vivo human skin model. Scientific Reports, 10, 1.

Publication 2020

Abdomen Acetone Aluminum ammonium thiocyanate Biopsy Cells Cold Temperature Eagle Epidermis Fetal Bovine Serum Forearm Interphase Mercury-200 Movement Needles Penicillins Pressure Skin Streptomycin styrofoam Subcutaneous Fat Suction Drainage Syringes

Detailed Cortical Surface Reconstruction

Cited 408 times

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Publication 2010

Brain Cortex, Cerebral Hybrids Insula of Reil Magnetic Fields Mesencephalon Microtubule-Associated Proteins Movement Reconstructive Surgical Procedures Tissues White Matter

Most recents protocols related to «Movement»

Infrasound Detection using Fiber Flow Sensors

Not available on PMC !

Example 2

In some applications, an infrasonic sensor is desired, with a frequency response f_lthat extends to an arbitrarily low frequency, such as a tenth of hundredth of a Hertz. Such a sensor might be useful for detecting fluid flows associated with movement of objects, acoustic impulses, and the like. Such an application works according to the same principles as the sonic sensor applications, though the length of individual runs of fibers might have to be greater.

In addition, the voltage response of the electrode output to movements is proportional to the velocity of the fiber, and therefore one would typically expect that the velocity of movement of fluid particles at infrasonic frequencies would low, leading to low output voltages. However, in some applications, the fluid movement is macroscopic, and therefore velocities may be appreciable. For example, in wake detection applications, the amplitude may be quite robust.

Generally, low frequency sound is detected by sensors which are sensitive to pressure such as infrasound microphones and microbarometers. As pressure is a scaler, multiple sensors should be used to identify the source location. Meanwhile, due to the long wave length of low frequency sound, multiple sensors have to be aligned far away to distinguish the pressure difference so as to identify the source location. As velocity is a vector, sensing sound flow can be beneficial to source localization. There is no available flow sensor that can detect infrasound flow in a broad frequency range with a flat frequency response currently. However, as discussed above, thin fibers can follow the medium (air, water) movement with high velocity transfer ratio (approximate to 1 when the fiber diameter is in the range of nanoscale), from zero Hertz to tens of thousands Hertz. If a fiber is thin enough, it can follow the medium (air, water) movement nearly exactly. This provides an approach to detect low frequency sound flow directly and effectively, with flat frequency response in a broad frequency range. This provides an approach to detect low frequency sound flow directly. The fiber motion due to the medium flow can be transduced by various principles such as electrodynamic sensing of the movement of a conductive fiber within a magnetic field, capacitive sensing, optical sensing and so on. Application example based on electromagnetic transduction is given. It can detect sound flow with flat frequency response in a broad frequency range.

For the infrasound detection, this can be used to detect manmade and natural events such as nuclear explosion, volcanic explosion, severe storm, chemical explosion. For the source localization and identification, the fiber flow sensor can be applied to form a ranging system and noise control to find and identify the low frequency source. For the low frequency flow sensing, this can also be used to detect air flow distribution in buildings and transportations such as airplanes, land vehicles, and seafaring vessels.

The infrasound pressure sensors are sensitive to various environmental parameters such as pressure, temperature, moisture. Limited by the diaphragm of the pressure sensor, there is resonance. The fiber flow sensor avoids the key mentioned disadvantages above. The advantages include, for example: Sensing sound flow has inherent benefit to applications which require direction information, such as source localization. The fiber flow sensor is much cheaper to manufacture than the sound pressure sensor. Mechanically, the fiber can follow the medium movement exactly in a broad frequency range, from infrasound to ultrasound. If the fiber movement is transduced to the electric signal proportionally, for example using electromagnetic transduction, the flow sensor will have a flat frequency response in a broad frequency range. As the flow sensor is not sensitive to the pressure, it has a large dynamic range. As the fiber motion is not sensitive to temperature, the sensor is robust to temperature variation. The fiber flow sensor is not sensitive to moisture. The size of the flow sensor is small (though parallel arrays of fibers may consume volume). The fiber flow sensor can respond to the infrasound instantly.

Note that a flow sensor is, or would be, sensitive to wind. The sensor may also respond to inertial perturbances. For example, the pressure in the space will be responsive to acceleration of the frame. This will cause bulk fluid flows of a compressible fluid (e.g., a gas), resulting in signal output due to motion of the sensor, even without external waves. This can be advantages and disadvantages depends on the detailed applications. For example, it can be used to detect flow distribution in the buildings. If used to detect infrasound, the wind influence be overcome by using an effective wind noise reduction approach.

US11869476B2. Acoustic metamaterial (2024-01-09). The Research Foundation for The State University of New York [US]. Inventors: Steven M. Hoffberg [US].

Patent 2024

Acceleration Acoustics A Fibers Blast Injuries Blood Vessel Cloning Vectors Dietary Fiber Electric Conductivity Electricity Electromagnetics Fibrosis Magnetic Fields Movement Pressure Reading Frames Sound Sound Waves Toxic Epidermal Necrolysis Ultrasonics Vaginal Diaphragm Vibration Water Movements Wind

Detection of Respiratory Effort and Cerebral Activation from Mandibular Movements

Not available on PMC !

Example 15

In a 15^thexample, reference is made to FIGS. 12 and 13. FIG. 12 shows an example of the first measurement signal stream F1 and of the second measurement signal stream F2 in the situation where the subject suffers a temporary disappearance of all control of cerebral origin, which is characteristic of central hypopnoea. This disappearance is characterized by the mouth opening passively because it is no longer held up by the muscles. It is therefore seen in the streams F1 and F2 that between the peaks the signal does not indicate any activity. On the other hand at the moment of the peak there is observed a high amplitude of the movement of the mandible. Toward the end of the peaks there is seen a movement that corresponds to a non-respiratory frequency, which is the consequence of cerebral activation that will then result in a micro-arousal. The digit 1 indicates the period of hypopnoea where a reduction of the flow is clearly visible on the stream F5th from the thermistor. The digits 2 and 3 indicate the disappearance of mandibular movement in the streams F1 and F2 during the period of central hypopnoea. FIG. 13 shows an example of the first measurement signal stream F1 and of the second measurement signal stream F2 in the situation where the subject experiences a prolonged respiratory effort that will terminate in cerebral activation. It is seen that the signal from the accelerometer F1 indicates at the location indicated by H a large movement of the head and of the mandible. Thereafter the stream F2 remains virtually constant whereas in that F1 from the accelerometer the level drops, which shows that there is in any event a movement of the mandible, which is slowly lowered. There then follows a high peak I that is a consequence of a change in the position of the head during the activation that terminates the period of effort. The digit 1 indicates this long period of effort marked by snoring. It is seen, as indicated by the digit 2, that the effort is increasing with time. This effort terminates, as indicated by the digit 3, in cerebral activation that results in movements of the head and the mandible, indicated by the letter I.

The analysis unit holds in its memory models of these various signals that are the result of processing employing artificial intelligence as described hereinbefore. The analysis unit will process these streams using those results to produce a report on the analysis of those results.

It was found that the accelerometer is particularly suitable for measuring movements of the head whereas the gyroscope, which measures rotation movements, was found to be particularly suitable for measuring rotation movements of the mandible. Thus cerebral activation that leads to rotation of the mandible without the head changing position can be detected by the gyroscope. On the other hand, an IMM type movement will be detected by the accelerometer, in particular if the head moves on this occasion. An RMM type movement will be detected by the gyroscope, which is highly sensitive thereto.

US11864910B2. System comprising a sensing unit and a device for processing data relating to disturbances that may occur during the sleep of a subject (2024-01-09). Sunrise SA [BE]. Inventors: Pierre Martinot [BE].

Patent 2024

ARID1A protein, human Arousal Exhaling Fingers Gene Expression Regulation Head Head Movements Mandible Medical Devices Memory Movement Muscle Tissue Oral Cavity Respiratory Rate Sleep Thumb Vision

Mitochondrial Motility Regulation by Delta-2 Tubulin and Bortezomib

Not available on PMC !

EXAMPLE 4

To determine the effect bortezomib and delta-2 tubulin accumulation have on mitochondrial motility, DRG neurons were transduced with lentivirus to express wild-type tubulin or delta-2 tubulin. As shown in FIGS. 15A and B, DRG neurons that expressed delta-2 tubulin showed a significant reduction in the motility of the mitochondria in the neurons as compared to control neurons or neurons that expressed wild-type tubulin. Expression of delta-2 tubulin affected every state of mitochondrial movement analyzed except for the stationary state (STA) (FIG. 15C). The effect of CCP1 knockdown on mitochondrial movement in the presence of bortezomib was also analyzed. As shown in FIG. 15D, treatment with bortezomib greatly affected the movement of mitochondria in DRG neurons. However, the knockdown of CCP1 activity rescued the effects bortezomib had on the motility of the mitochondria (FIG. 15D-F).

US11874284B2. Delta-2-tubulin as a biomarker and therapeutic target for peripheral neuropathy (2024-01-16). THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK [US], UNIVERSITÀ DEGLI STUDI DI MILANO-BICOCCA [IT]. Inventors: Francesca Bartolini [US], Maria Elena Pero [US], Guido Cavaletti [IT].

Patent 2024

Bortezomib delta-Tubulin Lentivirus Mitochondria Mitochondrial Inheritance Motility, Cell Motor Neurons Movement Neurons Tubulin

Porous Material for Sample Separation and Ionization

Not available on PMC !

Example 5

Probes of the invention include a porous material, such as paper, that can function to both separate chemicals in biological fluids before in situ ionization by mass spectrometry. In this Example, the porous material for the probe was chromatography paper. As shown in FIG. 24, a mixture of two dyes was applied to the paper as a single spot. The dyes were first separated on the paper by TLC (thin layer chromatograph) and the separated dyes were examined using MS analysis by methods of the invention with the paper pieces cut from the paper media (FIG. 24). Data show the separate dyes were detected by MS analysis (FIG. 24).

The chromatography paper thus allowed for sample collection, analyte separation and analyte ionization. This represents a significant simplification of coupling chromatography with MS analysis. Chromatography paper is a good material for probes of the invention because such material has the advantage that solvent movement is driven by capillary action and there is no need for a syringe pump. Another advantage is that clogging, a serious problem for conventional nanoelectrospray sources, is unlikely due to its multi-porous characteristics. Therefore, chromatography paper, a multi-porous material, can be used as a microporous electrospray ionization source.

US11867684B2. Sample dispenser including an internal standard and methods of use thereof (2024-01-09). Purdue Research Foundation [US]. Inventors: Zheng Ouyang [US], He Wang [US], Nicholas E. Manicke [US], Robert Graham Cooks [US], Qian Yang [US], Jiangjiang Liu [US].

Patent 2024

Biopharmaceuticals Capillary Action Chromatography Dyes Mass Spectrometry Movement Solvents Specimen Collection Syringes Thin Layer Chromatography

Central Apnoea Respiratory Monitoring

Not available on PMC !

Example 14

In a 14^thexample, reference is made to FIG. 11. FIG. 11 shows an example of the first measurement signal stream F1 and of the second measurement signal stream F2 in the situation where the subject suffers a central apnoea. The peaks F show a movement of the head and of the mandible on resumption of respiration. It is also seen that between the peaks F there is so to speak no movement of the mandible. The digit 1 indicates an absence of respiratory flow that goes hand in hand with an absence of effort, indicated by the digit 2, and activation and resumption of the effort, indicated by the digit 3.

Patent 2024

Cell Respiration Fingers Head Movements Mandible Medical Devices Movement Respiratory Rate Sleep Sleep Apnea, Central Thumb Vision

Top products related to «Movement»

Matlab by MathWorks

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MATLAB is a high-performance programming language and numerical computing environment used for scientific and engineering calculations, data analysis, and visualization. It provides a comprehensive set of tools for solving complex mathematical and computational problems.

Ethovision xt by Noldus

Sourced in Netherlands, United States, China, Japan, United Kingdom

EthoVision XT is a video tracking system that automatically tracks and analyzes the movement and behavior of animals in real-time. It provides an objective and reliable way to measure various parameters, such as distance traveled, velocity, and time spent in different zones of the experimental setup.

Labview by National Instruments

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LabVIEW is a software development environment for creating and deploying measurement and control systems. It utilizes a graphical programming language to design, test, and deploy virtual instruments on a variety of hardware platforms.

Smart 3 by Harvard Apparatus

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The Smart 3.0 is a compact and versatile laboratory equipment designed for diverse experimental applications. It functions as a programmable syringe pump, capable of precisely delivering and withdrawing liquids in a controlled manner. The device features an intuitive user interface and a range of connection options to integrate with various experimental setups.

Ethovision software by Noldus

Sourced in Netherlands, United States, United Kingdom

Ethovision is a video tracking software developed by Noldus. It is used to automatically track and analyze the movement and behavior of animals in a variety of experimental settings.

Ethovision 3 by Noldus

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Ethovision 3.0 is a video-based tracking system designed for automated behavioral analysis. It captures and tracks the movement and position of animals in a controlled environment, providing detailed data on their behavior.

Ethovision xt software by Noldus

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EthoVision XT is a video tracking software that automatically tracks and analyzes the movement and behavior of animals. It captures and records the position and movement of animals in real-time and generates quantitative data for research purposes.

Optojump by Microgate

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Optojump is a laboratory equipment product used for measuring various physical parameters. It utilizes optical sensors to capture data related to human movement and performance. The core function of Optojump is to provide accurate and reliable measurements without interpretation or extrapolation.

Ethovision by Noldus

Sourced in Netherlands, United States

EthoVision XT is a video tracking software that can automatically track and analyze the behavior of animals in real-time or from recorded videos. It provides detailed data on various parameters such as distance moved, velocity, and position of the tracked animal within the experimental arena.

Ethovision xt 8 by Noldus

Sourced in Netherlands, United States

EthoVision XT 8.5 is a video tracking system that automatically tracks and analyzes the movement and behavior of animals in a variety of experimental settings. It provides precise and reliable data on parameters such as distance traveled, velocity, and time spent in different zones of the test arena.

What are the different types or variations of movement that researchers study?

Researchers study a wide range of movement types, including locomotion (such as walking, running, and swimming), fine motor skills (like dexterity and coordination), and whole-body movements (such as exercise and rehabilitation exercises). The specific type of movement under investigation often depends on the research goals, whether that's optimizing athletic performance, understanding neurological processes, or developing assistive technologies.

How can movement research help improve quality of life?

Movement research has many practical applications that can enhance quality of life. For example, studies on movement and rehabilitation can help develop more effective physical therapy treatments to restore function for individuals with disabilities or recovering from injuries. Additionally, movement analysis in sports science can lead to injury prevention strategies and training methods to help athletes perform at their best and avoid setbacks. Even in the field of robotics, movement research aims to create assistive devices that can improve mobility and independence for those with limited physical capabilities.

What are some common challenges researchers face when studying movement?

One of the key challenges in movement research is the complexity of the physiological, biomechanical, and neurological processes involved. Accurately measuring and analyzing the nuances of human or animal motion requires sophisticated equipment and techniques. Researchers must also consider individual variations, environmental factors, and the interplay of multiple bodily systems. Adressing these complexities can slow down the research process and make it difficult to draw definitive conclusions.

How can PubCompare.ai help movement researchers optimize their work?

PubCompare.ai is an AI-powered platform that can streamline movement research by helping researchers more efficiently screen protocol literature and identify critical insights. The platform's advanced analysis capabilities allow researchers to pinpoint the most effective movement protocols related to their specific research goals, enabling them to choose the best options for reproducibility and accuracy. This can save valuable time and resources, allowing researchers to focus on driving breakthroughs in movement science and improving quality of life.

What are some key applications of movement research?

Movement research has a wide range of applications across fields such as sports science, physical therapy, and robotics. In sports, movement analysis can be used to optimize training regimens, prevent injuries, and enhance athletic performance. In physical therapy, a deeper understanding of movement mechanics can lead to more effective rehabilitation treatments for patients recovering from injuries or living with disabilities. And in robotics, movement research is essential for developing assistive devices and prosthetics that can mimic natural human motion and improve mobility for those with limited physical capabilities. Therse applications highligt the broad impact of movement science on improving quality of life.

More about "Movement"

Motion, Locomotion, Displacement, Biomechanics, Neuroscience, Rehabilitation, Sports Science, Physical Therapy, Robotics, Movement Analysis, Kinematics, Kinetics, Posture, Gait, Balance, Coordination, MATLAB, EthoVision XT, LabVIEW, Smart 3.0, Ethovision software, Ethovision 3.0, EthoVision XT software, Optojump, Ethovision, EthoVision XT 8.5.
Movement refers to the physical displacement of a body or its parts through space.
It encompasses a wide range of activities, including locomotion, exercise, and rehabilitation.
Movement research focuses on understanding the underlying physiological, biomechanical, and neurological processes that govern human and animal motion.
This area of study has broad applications in fields such as sports science, physical therapy, and robotics, aiming to optimize performance, prevent injuries, and enhance quality of life.
Researchers in this domain leverge advanced tehcnologies, like the AI-powered PubCompare.ai platform, to streamline their work and drive breakthroughs in movement science.
PubCompare.ai is a powerful tool that empowers movement researchers to effortlessly locate and compare protocols from literature, pre-prints, and patents.
Leveraging advanced AI technology, PubCompare.ai provides data-driven insights to help identify the most optimal movement protocols and products, streamlining the research process and driving breakthroughs in the field.
Experiance the power of this platform and take your movement research to new heights.