Representation Of Motion Research Articles

Phantom limb pain: actual concepts of pathophysiology and treatment methods from the standpoint of evidence-based medicine

Rationale. Despite a large number of studies on the effectiveness of various pharmacological and non- pharmacological therapies, PLP treatment tactics have not yet been developed, which is largely due to the complex mechanism of the formation of this pathology. Although PLP is classified as neuropathic pain, standard methods of neuropathic pain therapy are not always effective for this syndrome. To optimize the regimens of existing methods of PLP treatment, as well as the search and clinical trials of new therapeutic approaches, it is necessary to take into account the currently available evidence base.Material and methods. Our analysis included publications on phantom pain treatment methods with a high level of evidence (randomized controlled trials, systematic reviews and meta-analyses). Literature search was performed in Medline PubMed and eLIBRARY systems.Results. The review provides an evidence base for pharmacotherapy methods (opioids, NMDA-receptor antagonists, tricyclic antidepressants, anticonvulsants, local anesthetics), for methods based on the phantom illusion (mirror therapy, motion representation, virtual reality), for non-invasive (transcutaneous electrical neurostimulation, transcranial magnetic stimulation, transcranial electrical stimulation) and invasive (deep brain stimulation, motor cortex stimulation, spinal cord stimulation, dorsal root ganglion stimulation) neuromodulation. Data on the most studied dosing regimens of different methods of pharmacological and non-pharmacological therapy are presented.

Phantom limb pain: actual concepts of pathophysiology and therapeutic targets

In the review, we present the main pathogenetic mechanisms of the development of phantom limb pain (PLP) after limb amputation, the prevalence of which can reach 87%. The exact mechanism of PLP remains unknown. The involvement of peripheral and central mechanisms of the formation of PLP is assumed. Peripheral mechanisms include increased excitability and the formation of ectopic activity in the amputation neuromas and in the ganglion cells of the dorsal roots of the spinal cord. The central mechanisms are represented by central sensitization in the dorsal horns of the spinal cord with the development of the “wind up” phenomenon, reorganization processes in the thalamus and cortex with thalamic and cortical remapping, and proprioceptive memory. Also significant is the neuromatrix theory, the reduction of feedback from the visual and other sensory systems after deafferentation. PLP therapy methods focused on central mechanisms are: spinal cord stimulation, transcutaneous electrical neurostimulation, deep brain stimulation, non-invasive and invasive methods of cerebral cortex stimulation, mirror therapy, virtual and augmented reality technologies, movement representation and its modification “phantom exercises”. In addition, pharmacologic treatment options based on PLP mechanisms can be used: NMDA receptor antagonists, anticonvulsants, tricyclic antidepressants, opioids.

Influence of sport expertise in facilitating and inhibiting the recognition of the opponent's intentions in sailing.

Starting from the proposed role of the mirror neuron system in the recognition of the intention underlying the actions of others, an experimental paradigm was implemented to test the role of sailing motor expertise in predicting the outcome of a competitor's action. It was hypothesized that subjects with experience in sailing would correctly interpret the maneuver performed due to the activation of domain specific motor representations of the same movements and that subjects who practiced a sport different from sailing would perform worse because of the activation of irrelevant motor patterns. For doing so, a series of video clips, in which a professional sailor performed a tack or a feint, have been manipulated so that the video clips would stop at the moment of the dunkin, namely, when the boat acquires speed to tack or continue straight ahead. The task consisted in predicting whether the action following the dunkin was an actual tack or a feint. The performance of 87 subjects, divided into three subgroups (sailors, tennis players, sedentary), was evaluated in terms of accuracy in identifying the sailor's intentions and correlated to age, gender, manual dominance, education, job, hours spent weekly playing videogames, and experience in playing sports. Results showed that the percentage of correct identifications of the intention to do a tack or feint was the highest in the group of sailors and the lowest in tennis players. An inverse relation between tennis experience and ability in recognizing the sailor's intention was found in the group of tennis players. Gender, age, manual dominance, education, job, and experience with videogames were not found to be correlated with performance. Findings support the possible implication of the mirror neuron system in maneuver detection in sailing and may be a starting point for the development of psychological training in this sport.

Numerical Equivalence of Diabatic and Adiabatic Representations in Diatomic Molecules.

The (time-independent) Schrödinger equation for atomistic systems is solved by using the adiabatic potential energy curves (PECs) and the associated adiabatic approximation. In cases where interactions between electronic states become important, the associated nonadiabatic effects are taken into account via derivative couplings (DDRs), also known as nonadiabatic couplings (NACs). For diatomic molecules, the corresponding PECs in the adiabatic representation are characterized by avoided crossings. The alternative to the adiabatic approach is the diabatic representation obtained via a unitary transformation of the adiabatic states by minimizing the DDRs. For diatomics, the diabatic representation has zero DDR and nondiagonal diabatic couplings ensue. The two representations are fully equivalent and so should be the rovibronic energies and wave functions, which result from the solution of the corresponding Schrödinger equations. We demonstrate (for the first time) the numerical equivalence between the adiabatic and diabatic rovibronic calculations of diatomic molecules using the ab initio curves of yttrium oxide (YO) and carbon monohydride (CH) as examples of two-state systems, where YO is characterized by a strong NAC, while CH has a strong diabatic coupling. Rovibronic energies and wave functions are computed using a new diabatic module implemented in the variational rovibronic code Duo. We show that it is important to include both the diagonal Born-Oppenheimer correction and nondiagonal DDRs. We also show that the convergence of the vibronic energy calculations can strongly depend on the representation of nuclear motion used and that no one representation is best in all cases.

Exploring the impact of machine learning on dance performance: a systematic review

ABSTRACT In recent years, the intersection of machine learning and dance has garnered increasing attention as a means to enhance the aesthetics and creativity of dance performance. Machine learning techniques, such as human-pose detection, have been utilized to analyze body movement and generate visual models in realtime, offering new approaches to traditional art form. However, despite the growing interest in this field, there is a lack of comprehensive research that evaluates the impact of machine learning on dance from multiple perspectives. This systematic review addresses this gap by examining the impact of machine learning on four key aspects of dance performance: choreographic creation support; dataset or network collection and training; improved techniques of human-pose detection; perception and new visual representations of dance movement. This exploration reveals that machine learning contributes both positively and negatively to artistic development, introducing a sense of novelty and heightened interest in the performance while concurrently prompting ethical concerns regarding artistic ownership and authorship. Through a nuanced analysis of machine learning's effects on key aspects of dance, this study aims to provide valuable insights into how these technologies can enhance the artistic practice in dance while signaling areas that demand further research in this rapidly evolving field.

Event-Based Optical Flow via Transforming Into Motion-Dependent View.

Event cameras respond to temporal dynamics, helping to resolve ambiguities in spatio-temporal changes for optical flow estimation. However, the unique spatio-temporal event distribution challenges the feature extraction, and the direct construction of motion representation through the orthogonal view is less than ideal due to the entanglement of appearance and motion. This paper proposes to transform the orthogonal view into a motion-dependent one for enhancing event-based motion representation and presents a Motion View-based Network (MV-Net) for practical optical flow estimation. Specifically, this motion-dependent view transformation is achieved through the Event View Transformation Module, which captures the relationship between the steepest temporal changes and motion direction, incorporating these temporal cues into the view transformation process for feature gathering. This module includes two phases: extracting the temporal evolution clues by central difference operation in the extraction phase and capturing the motion pattern by evolution-guided deformable convolution in the perception phase. Besides, the MV-Net constructs an eccentric downsampling process to avoid response weakening from the sparsity of events in the downsampling stage. The whole network is trained end-to-end in a self-supervised manner, and the evaluations conducted on four challenging datasets reveal the superior performance of the proposed model compared to state-of-the-art (SOTA) methods.

Video2Haptics: Converting Video Motion to Dynamic Haptic Feedback with Bio-Inspired Event Processing.

In cinematic VR applications, haptic feedback can significantly enhance the sense of reality and immersion for users. The increasing availability of emerging haptic devices opens up possibilities for future cinematic VR applications that allow users to receive haptic feedback while they are watching videos. However, automatically rendering haptic cues from real-time video content, particularly from video motion, is a technically challenging task. In this paper, we propose a novel framework called "Video2Haptics" that leverages the emerging bio-inspired event camera to capture event signals as a lightweight representation of video motion. We then propose efficient event-based visual processing methods to estimate force or intensity from video motion in the event domain, rather than the pixel domain. To demonstrate the application of Video2Haptics, we convert the estimated force or intensity to dynamic vibrotactile feedback on emerging haptic gloves, synchronized with the corresponding video motion. As a result, Video2Haptics allows users not only to view the video but also to perceive the video motion concurrently. Our experimental results show that the proposed event-based processing methods for force and intensity estimation are one to two orders of magnitude faster than conventional methods. Our user study results confirm that the proposed Video2Haptics framework can considerably enhance the users' video experience.

Flipping the script in organic reaction mechanism instruction: using generative pedagogies instead of lecture to improve learning outcomes

Two generative approaches to reaction mechanism instruction for novice students were compared to lecture instruction. In both approaches, students were coached to propose selected reaction mechanisms based on prior knowledge. New instructional methods were correlated with increased skill in representations of electron movements and other gains. Students who saw a larger amount of new pedagogy showed stronger abilities to propose mechanisms for unfamiliar reactions. In the group that saw a larger amount of new pedagogy, first-generation college student (FGS) grades rose to match non-FGS grades. Learning gains were interpreted with respect to cognitive load theory, flagging high element interactivity as a likely obstacle for novice students. Problem solving during mechanism instruction for novice students offers the potential to improve learning outcomes.

Accuracy of Video-Based Hand Tracking for People With Upper-Body Disabilities.

Utilization of hand-tracking cameras, such as Leap, for hand rehabilitation and functional assessments is an innovative approach to providing affordable alternatives for people with disabilities. However, prior to deploying these commercially-available tools, a thorough evaluation of their performance for disabled populations is necessary. In this study, we provide an in-depth analysis of the accuracy of Leap's hand-tracking feature for both individuals with and without upper-body disabilities for common dynamic tasks used in rehabilitation. Leap is compared against motion capture with conventional techniques such as signal correlations, mean absolute errors, and digit segment length estimation. We also propose the use of dimensionality reduction techniques, such as Principal Component Analysis (PCA), to capture the complex, high-dimensional signal spaces of the hand. We found that Leap's hand-tracking performance did not differ between individuals with and without disabilities, yielding average signal correlations between 0.7-0.9. Both low and high mean absolute errors (between 10-80mm) were observed across participants. Overall, Leap did well with general hand posture tracking, with the largest errors associated with the tracking of the index finger. Leap's hand model was found to be most inaccurate in the proximal digit segment, underestimating digit lengths with errors as high as 18mm. Using PCA to quantify differences between the high-dimensional spaces of Leap and motion capture showed that high correlations between latent space projections were associated with high accuracy in the original signal space. These results point to the potential of low-dimensional representations of complex hand movements to support hand rehabilitation and assessment.

Body schema and the system of mental representation of human movements

Body schema and the system of mental representation of human movements

Safer and efficient assemblies: Harnessing real time worker movements with digital twins

This paper addresses a critical gap in digital twin simulation within manufacturing environments by focusing on the dynamic representation of worker movements during assembly processes. We introduce an innovative approach that utilises Ultra-Wideband (UWB) sensors to incorporate worker trajectory data into Siemens Process Simulate software, enabling the creation of a digital twin of assembly line operations. Our methodology involves comprehensive data collection using UWB sensors, followed by pre-processing steps such as data cleaning, interpolation, and classification of points into dwell and transit locations. Within the framework of Process Simulate, we develop the assembly process digital twin, integrating simulations of tricycle assembly alongside dynamic worker path and movement simulations. Our digital twin facilitates ergonomic analysis, process optimisation, and worker interaction analysis, offering insights for enhancing factory efficiency and safety. Notably, through visualisation of worker paths and identification of bottlenecks, our digital twin enables optimisation of resource allocation. Quantitative results demonstrate significant improvements, such as a reduction in the time of completion of six products by 11% compared to Discrete Event Simulation under similar process conditions. This study highlights the transformative potential of digital twin technology in manufacturing, providing a robust framework for simulating and optimising worker movements within real-world factory environments.

Editorial

Looking at the Mediterranean as a geo-cultural space where people have met, assimilated, transformed and continue to do so, and at the relationship of cinema and media as representations of these ongoing movements and processes, the contributions of this Special Issue are pivotal in understanding the contemporary Mediterranean cultural identity. The authors’ analyses of a wide range of contemporary films and TV series from Egypt, France, Greece, Italy, Malta, Spain and Tunisia confirm that the Mediterranean identity does not belong to a group of sameness but to a group that embraces being and becoming. The guest editors, Giovanna Summerfield and Rosario Pollicino, intend to provide important reflections on the complexities of Mediterranean realities. Above all, their aim is to inspire and launch a dialogue between Mediterranean studies and media studies.

‘Grounding together’ or digging movements into the ground? South African scholar-activism 30 years after democracy

The fiftieth anniversary of ROAPE coincidentally marks 30 years of what may be called ‘bourgeois democracy’ in South Africa. Walter Rodney’s debate with mainly white lecturers (including early contributors and founders of ROAPE) at Dar es Salaam in 1971 offers a pivot from which to explore the representation of popular movements in South Africa in the 2000s, which centred on the assumption that the working class had fallen victim to the adoption of neoliberal policies by the ruling African National Congress. This article explores the relationship between race, class and knowledge production as well as contested meanings of transformation in this context. While the independent left (those outside of mainstream political parties as well as the tripartite alliance) in South Africa has at times heroically supported the struggles of grassroots movements, the article argues that we have reached an impasse. Our consistent socialist rhetoric and methods of movement building tend to be out of touch with grassroots movements. A renewed political dialogue is required to explore the extent to which it remains possible to ‘ground together’ (Rodney 1969) in collaboration with the various streams of discontent and militancy in the country.

Demonstration and Analysis of DRN Deep Learning Architecture for Step-by-Step Disassembly of Dahongquan

Abstract The Dahongquan martial arts style is characterized by its intricate and varied maneuvers, posing challenges for traditional video demonstrations to fully satisfy learners’ needs. This study introduces a cutting-edge approach utilizing a visual neural network to deconstruct and map these martial arts movements in a 3D virtual environment. Initially, preprocessing involves extracting data from exercise videos, employing a combination of video annotation and skeleton feature extraction. Subsequently, a deep residual network (DRN) with multi-scale feature extraction and dense residual attention mechanisms is employed, facilitating a systematic breakdown of the martial arts movements. The third phase involves constructing a 3D action mapping and demonstration process, utilizing cubic B-spline curve fitting and cylinder deformation techniques to enhance the representation of movement based on the skeletal model. Remarkably, the DRN network, without the need for extensive training datasets, achieves flawless recognition of various gongfu combinations and records a recognition rate of 92.92% for the most challenging boxing movements. The efficacy of this model is further corroborated by its enhancement of the demonstration process, achieving an overall learner satisfaction rating of 5.26. The disassembly and demonstration strategy proposed in this study has proven effective during experimental sessions, demonstrating significant potential for advancing martial arts training methodologies.

Facial Prior Guided Micro-Expression Generation.

This paper focuses on the facial micro-expression (FME) generation task, which has potential application in enlarging digital FME datasets, thereby alleviating the lack of training data with labels in existing micro-expression datasets. Despite obvious progress in the image animation task, FME generation remains challenging because existing image animation methods can hardly encode subtle and short-term facial motion information. To this end, we present a facial-prior-guided FME generation framework that takes advantage of facial priors for facial motion generation. Specifically, we first estimate the geometric locations of action units (AUs) with detected facial landmarks. We further calculate an adaptive weighted prior (AWP) map, which alleviates the estimation error of AUs while efficiently capturing subtle facial motion patterns. To achieve smooth and realistic synthesis results, we use our proposed facial prior module to guide motion representation and generation modules in mainstream image animation frameworks. Extensive experiments on three benchmark datasets consistently show that our proposed facial prior module can be adopted in image animation frameworks and significantly improve their performance on micro-expression generation. Moreover, we use the generation technique to enlarge existing datasets, thereby improving the performance of general action recognition backbones on the FME recognition task. Our code is available at https://github.com/sysu19351158/FPB-FOMM.

Enhancing Parkinson's Disease Recognition through Multimodal Analysis of Archimedean Spiral Drawings

Parkinson's disease is one of the most common neurodegenerative diseases, which is incurable according to recent clinical knowledge. Evaluating motor symptoms across diverse modalities such as speech, handwriting, and movement composes a conventional diagnostic approach. However, concurrently utilizing multimodal datasets encompassing drawing and acceleration data remains an underexplored f ield. Our investigation involved examining drawing and movement data of 45 Parkinson's disease (PD) patients and 47 healthy individuals (HC). The PD group presented mild symptoms in the right hand. We transformed drawing data into spiral images and used visual representations of motion data, employing pre-trained models for feature extraction and classifiers. While motion representations exhibited superior performance compared to drawing images, a comprehensive evaluation with the Mann-Whitney U test at a significance level of 0.05 revealed no statistically significant difference between the efficacy of movement and drawing data in all classification scenarios. Significant improvements were made by combining the drawing data predictions with the motion data predictions. The key finding of the research is that the recognition of the disease can be improved by connecting (post-model) the two modalities. Furthermore, it can be concluded that with the present approach, neither the drawing nor the movement data produced lower results on average.

José Limón's Chaconne

Abstract: In 1942, choreographer José Limón created a solo for himself to J. S. Bach's "Chaconne" for solo violin, the last movement of Violin Partita No. 2 in D Minor BWV 1004. Many of Limón's works revolve around a central thematic narrative, often celebrating the majesty of the human spirit. In his Chaconne , however, Limón created an abstract movement representation of Bach's music, employing theme and variation as a stylistic compositional device. Chaconne is not, however, devoid of connotative references, as certain gestures, shapes, and stances spark various associations. But these occasional veiled echoes of a literal scenario do not explain the continuing appeal of the work, which instead is attributed mainly to its impressively crafted choreographic design, the carefully built relationships it exhibits between dance and music, and the openness and interpretative flexibility it offers as a vehicle for empowering the dancer. Limón intended the dance to reflect the meaning of the music, not strictly a visualization of the music, though it does have its share of such music-dance matches. The dance partakes in certain aspects of the music's form and structure, utilizing similar or parallel compositional design and techniques and following and countering the music's phrasing, melodic contour, and rhythms. Some of the congruences are obvious and satisfying, such as the many four-measure aaab dance phrases joined to equivalent four-measure aaab phrases of Bach's music. Some of the music-dance congruences are more subtle, such as extended physical movements riding ascending and descending musical scales. This choreographic focus on melodic contour draws attention to how Bach pairs ascent and descent, or chordal arpeggiation and stepwise scalar runs, across pairs of four-measure sequences. Separate from, but hand in hand with, its relationship to the music, the dance also has its own shape. Limón conceived of the material as developing from "a seminal dance phrase from which the entire work would flow." He did not elaborate on that phrase or how it evolves throughout the work. Still, generations of dancers in his namesake company have contributed to and accumulated a treasure trove of observations about and interpretations of Limón's solo, and how it relates to the music—and this cache may be usefully consulted. A choreomusical analysis of the dance incorporating the insights of dancers reveals how Limón developed the steps, gestures, positions, and phrases of his material; what musical relationships are pertinent to dancing it; how choreographic variation structures the dance; and how the dance illuminates aspects of design in the music. In particular, a principle of diminution pervades the design of the dance and the music; material is repeated in some way in faster or in smaller units, thus accelerating one's experience of, and increasing the tension in, a performance. However, such analysis can only be tentative, its conclusions temporary. There is no agreed-upon original or definitive dance score. Multiple versions exist on video and in the company's collective memory. Various dancers perform the dance differently. Furthermore, it is a living, growing artwork, as each new performer brings their individual experience to bear upon their performance—an artistic stance encouraged by Limón's conceptualization of his dance as a score open to each dancer's interpretation.

Movement Representation Learning for Pain Level Classification

Movement Representation Learning for Pain Level Classification

Debating representations of the 2019 Hong Kong protests online: New evidence for ‘metalinguistic density’

The current paper replicates findings related to the analytical heuristic of ‘metalinguistic density’. It provides updated theoretical motivations for an analytical focus on explicit metalanguage in online text-based settings, based on notions of symbolic interactionism. An analysis of online user comment data of the 2019 Hong Kong protests reconfirms that the relative occurrence of metalanguage focusing on certain terms indicates the extent to which these terms’ denotational norms are shared amongst a community of language users.While most terms in the corpus do not regularly attract explicit metalanguage, several terms thematically related to the protests did. This disproportionate metalinguistic attention may be explained by political disputes on the movement's legitimacy, which led to normative debates on the discursive representation of the protest movement. Finally, certain phrases had become indexical of a certain political position to the extent that they were the frequent target of irony. In general, the results suggests that ‘metalinguistic density’ is a useful heuristic to employ in text-analytical investigations that seek to explain participants’ interpretations of discursive interactions.

Effect of Reaching Movement Modulation on Experience of Control in Virtual Reality

Users’ motion representation in virtual reality (VR) can be modulated visually by introducing a mismatch with their real motion, which can bring benefits to exercise and rehabilitation and has great potential for exergame applications in VR. Users’ experience of control is a critical consideration for user experience in human–computer interaction and should be paid special attention when movement modulation is implemented in VR. However, how movement modulation affects users’ experience of control and motor performance has not been fully investigated in detail. This research included 49 participants and investigated how the experience of control is influenced by reaching movement modulation in two types: the enhancement and reduction modes. Different modulation modes were designed to study their influence on the explicit experience of control in self-ratings and the implicit measured experience of control in intentional binding and electroencephalography. Participants’ movement trajectory, velocity, and completion time were analyzed for motor performance. The results illustrate a significant effect of movement modulation on the users’ motor performance and experience of control in self-ratings and EEG. This study makes a major contribution through a comprehensive analysis of the experience of control with movement modulation and provides important and practical design considerations on movement modulation design in future exercise-based applications with positive controlling experiences in VR.