Motion Capture Technology Research Articles

Application of motion capture technology in biomechanical research of massage techniques

Application of motion capture technology in biomechanical research of massage techniques

Research on Teaching and Dance Creation of Chinese Folk Dance in the Information Age

Abstract In this paper, we use motion capture technology to collect typical movements of Chinese folk dances and establish three-dimensional character models with the characteristics of human motion continuity and bone length invariance to discriminate the trajectory of skeletal movements. Video is used to export the data of Chinese folk dance. Design methods for extracting folk music and dance features to form a model for creating dances. Suppressing the noise of the original dance music, improving the accuracy of the fundamental frequency extraction of the music signal, and manually scoring the dance creation generation program are all benefits of using the Chebyshev filter. We propose the teaching method of Chinese folk dance in online broadcasting mode and carry out teaching experiments to compare the cooperative learning effect and dance technique evaluation effect between traditional dance teaching method and online broadcasting video lecture teaching method. The dance creation and generation program proposed in this paper is able to achieve a dance movement similarity of 0.92, which is able to preserve the original dance posture of Chinese folk dances to a greater extent. The results of the technical evaluation show that the teaching effects of the two teaching methods present significant differences in the four methods of basic technique, pair cooperation, dance expression, and total score, i.e., P<0.05, which shows that the online live video explanation method is more suitable for the teaching of ethnic folk dance in the information age.

Synthetic IMU Datasets and Protocols Can Simplify Fall Detection Experiments and Optimize Sensor Configuration.

Falls represent a significant cause of injury among the elderly population. Extensive research has been devoted to the utilization of wearable IMU sensors in conjunction with machine learning techniques for fall detection. To address the challenge of acquiring costly training data, this paper presents a novel method that generates a substantial volume of synthetic IMU data with minimal actual fall experiments. First, unmarked 3D motion capture technology is employed to reconstruct human movements. Subsequently, utilizing the biomechanical simulation platform Opensim and forward kinematic methods, an ample amount of training data from various body segments can be custom generated. Synthetic IMU data was then used to train a machine learning model, achieving testing accuracies of 91.99% and 86.62% on two distinct datasets of actual fall-related IMU data. Building upon the simulation framework, this paper further optimized the single IMU attachment position and multiple IMU combinations on fall detection. The proposed method simplifies fall detection data acquisition experiments, provides novel venue for generating low cost synthetic data in scenario where acquiring data for machine learning is challenging and paves the way for customizing machine learning configurations.

Selection of motion capture technologies for Industry 5.0 production systems: A structured literature review

The use of motion capturing systems within the Industry 5.0 is a promising opportunity in various scenarios, e.g., the ergonomic evaluation, human-robot-interaction, or safety applications. The steady technological development of such systems makes it increasingly harder for the potential user, to choose a suitable technology. This research conducts a systematic literature review to structure the existing technologies and using a set of evaluation criteria derived from the literature. We identify 17 publications in the domain of engineering to draw insights on the matter.

ASL champ!: a virtual reality game with deep-learning driven sign recognition

We developed an American Sign Language (ASL) learning platform in a Virtual Reality (VR) environment to facilitate immersive interaction and real-time feedback for ASL learners. We describe the first game to use an interactive teaching style in which users learn from a fluent signing avatar and the first implementation of ASL sign recognition using deep learning within the VR environment. Advanced motion-capture technology powers an expressive ASL teaching avatar within an immersive three-dimensional environment. The teacher demonstrates an ASL sign for an object, prompting the user to copy the sign. Upon the user’s signing, a third-party plugin executes the sign recognition process alongside a deep learning model. Depending on the accuracy of a user’s sign production, the avatar repeats the sign or introduces a new one. We gathered a 3D VR ASL dataset from fifteen diverse participants to power the sign recognition model. The proposed deep learning model’s training, validation, and test accuracy are 90.12%, 89.37%, and 86.66%, respectively. The functional prototype can teach sign language vocabulary and be successfully adapted as an interactive ASL learning platform in VR.

Motion Capture Technology in Animation

Motion Capture Technology in Animation

Visual Culture: A Study on the Presence of Alphabetical Pattern in ‘Senaman Tua’ by using Motion Capture Technology

Senaman Tua (Malay’s Ancient Exercise) is a therapeutic exercise from Malay culture. This exercise is blend well aesthetically with Malay culture and Islam which give holistic positive effects on the spiritual side of being able to provide, maintain inner peace, patience in the individual and also able to understand their own inner selves. According to the founder, the essence of the holistic positive effect is from the unseen pattern that embedded in the movement. The aim of this study is to visualize the micro-line the embedded in Senaman Tua (Malay’s Ancient Exercise) movement by using Motion Capture Technology. With the permission of Senaman Tua’s founder, Selangkah Guru (A Guru’s movements) is a dynamic exercise movement of Senaman Tua for beginner will be captured by using Motion Capture Technology. There are 33 markers of human anatomy have been captured by using Motion Capture Technology in 1 minute 08 second. The finding show there are presence of alphabetic pattern that generated from the “Selangkah Guru” (A Guru’s Movements). It can be concluded that visual pattern of “Lam Alif” alphabet clearly shows in the mapping of Motion Capture Technology.

Kajian pemanfaatan teknologi motion capture dalam melestarikan tarian budaya nusantara

This article discusses methods for preserving Indonesian dances in Indonesia using motion capture technology. Indonesian archipelago dances such as the Khas Semarangan dance, Topeng Cirebon, and Lengger Lanang have had their movements recorded using motion capture. This article discusses how this dance is preserved using motion capture technology along with its advantages and disadvantages. This article aims to determine the advantages and disadvantages of motion capture technology in preserving Indonesian dances in Indonesia. This research is literature review research and the method used is literature study. The preparation of this literature review research used several national journals and media reports. Literature collection was carried out using the Google Scholar search engine. The results obtained are that motion capture technology can be used as an introduction tool, basic learning, and as a reference for learning dance, especially the Semarangan Typical dance, Cirebon Mask, and Lengger Lanang. Motion capture technology can also produce dance simulation game applications. Apart from that, there are seven advantages and seven weaknesses in preserving Indonesian dance using motion capture technology. Preserving and documenting traditional Indonesian dances digitally using motion capture technology is very possible while still considering the existing advantages and disadvantages.

Markerless motion capture technology to quantify functional performance in dementias: a systematic review

AbstractBackgroundQuantifying functional performance objectively and unobtrusively could offer vital insights for clinical decision making on the level of support required by people living with dementia and other neurodegenerative conditions. Markerless motion capture (MMC) is more suitable for deployment in clinical and real‐world settings because single sensor MMC systems are less expensive and less complex compared to marker‐based systems. The aim of this study was to complete a systematic review of published literature on the use of MMC with full‐body tracking in people with dementias.MethodWe systematically searched for relevant articles using the search terms motion capture, motion analysis and movement analysis combined with dementia, mild cognitive impairment (MCI) and Parkinson’s disease (PD) which yielded a total of 1103 results. Inclusion criteria were MMC and full‐body tracking. Studies evaluating marker‐based motion capture, body‐worn sensors or Inertial Measurement Units, virtual reality, kinetics and interventions like DBS or exercises were excluded. 134 studies were included for full article screening out of which 17 eligible studies that met the selection criteria were included in the review.ResultMMC devices used in the reviewed studies included Microsoft Kinect (n = 15) and unspecified 2D motion camera (n = 2). Patient groups included in the studies were PD (n = 12), dementia (n = 4) and MCI (n = 1). Functional performance components evaluated were gait (n = 16), sit to stand (n = 2), turning (n = 1) and stepping in place (n = 1). About half the studies used advanced machine learning methods whereas the other half used descriptive statistical methods. The lack of standardisation in the measures used prevented us from comparing and synthesizing study results.ConclusionAlthough MMC has the potential to be used for quantifying functional performance in people with dementia, MCI and PD, there appears to be significant variation in the methods used in its evaluation. Although features of mobility were measured, none of the reviewed studies analysed activities of daily living tasks, a key component of functional performance. Standardising the process for extracting features and assessing accuracy would enable more effective validation of real‐world impact. Further research is required in people with neurodegenerative conditions for MMC to be routinely used in clinical and real‐world applications.

Wrist Motion Assessment in Tennis Players using Three-Dimensional Motion Capture and Dynamic Electromyography.

Background Tennis players often present with ulnar-sided wrist pain, which may reflect repetitive stress and/or faulty mechanics. There is a role for investigating the biomechanics of tennis strokes and how they may relate to wrist pathology. The purpose of this study was to investigate whether three-dimensional motion capture technology and dynamic electromyography (EMG), when used to study groundstrokes in elite junior tennis players, reveals patterns of upper extremity motion that may correlate with the development of clinically relevant pathology. Case Description Three-dimensional kinematic and EMG data were collected from two United States Tennis Association-ranked adolescent tennis players during groundstrokes. There were several observed differences in the two players' degree and timing of pronation/supination, ulnar/radial deviation, and flexion/extension during their strokes. Clinical Significance Advanced motion capture technology facilitates a nuanced understanding of complex movements involved in groundstroke production. This methodology may be useful for identifying athletes who are at risk for injury and guiding rehabilitation for players experiencing pain. Level of Evidence IV.

The speed-gene study: methods, study design and preliminary results

The Speed-Gene study aims to identify genetic variants influencing athletic performance and human locomotion using motion capture technology. Currently, 60 female participants have completed the testing protocol, and the overall aim is to recruit 283 moderately trained, healthy Southeast Asian individuals (18–45 y, BMI < 30). Participants will undergo biomechanical analysis and genetic testing. Several analyses will be performed, including (but not limited to) linear and angular kinematic analysis using motion capture technology, force plate dynamometry and genetic analyses to define novel power/torque related outcomes that would be more sensitive to allele-specific differences in athletic performance. Pretesting beverages will be provided, and activity history and current activity levels will be assessed by a questionnaire. The kinematic data will be obtained using a Qualisys Track Manager (QTM) system, and DNA will be extracted from white blood cells. The participants serve as their own controls. Although the Speed-Gene study is tightly controlled, our preliminary findings still indicate considerable individual variability. More participants and further genetic analysis are required to allow the investigation of potential underlying genetic mechanisms responsible for this individual variability.

KeepRunning: A MoCap-Based Rapid Test to Prevent Musculoskeletal Running Injuries

The worldwide popularisation of running as a sport and recreational practice has led to a high rate of musculoskeletal injuries, usually caused by a lack of knowledge about the most suitable running technique for each runner. This running technique is determined by a runner’s anthropometric body characteristics, dexterity and skill. Therefore, this study aims to develop a motion capture-based running analysis test on a treadmill called KeepRunning to obtain running patterns rapidly, which will aid coaches and clinicians in assessing changes in running technique considering changes in the study variables. Therefore, a review and proposal of the most representative events and variables of analysis in running was conducted to develop the KeepRunning test. Likewise, the minimal detectable change (MDC) in these variables was obtained using test–retest reliability to demonstrate the reproducibility and viability of the test, as well as the use of MDC as a threshold for future assessments. The test–retest consisted of 32 healthy volunteer athletes with a running training routine of at least 15 km per week repeating the test twice. In each test, clusters of markers were placed on the runners’ body segments using elastic bands and the volunteers’ movements were captured while running on a treadmill. In this study, reproducibility was defined by the intraclass correlation coefficient (ICC) and MDC, obtaining a mean value of ICC = 0.94 ± 0.05 for all variables and MDC = 2.73 ± 1.16° for the angular kinematic variables. The results obtained in the test–retest reveal that the reproducibility of the test was similar or better than that found in the literature. KeepRunning is a running analysis test that provides data from the involved body segments rapidly and easily interpretable. This data allows clinicians and coaches to objectively provide indications for runners to improve their running technique and avoid possible injury. The proposed test can be used in the future with inertial motion capture and other wearable technologies.

Research and Effectiveness Analysis of Innovative Teaching Models of Physical Education in Colleges and Universities under Convergent Network Architecture

Abstract In order to realize the innovation of sports teaching mode, this paper first combines the motion capture technology and three-dimensional modeling technology, based on the objectives and theories of sports teaching in colleges and universities, and constructs a college sports auxiliary teaching system under the fusion network architecture. Then, the three-dimensional modeling of sports action, the extraction of key sports action features, and the use of generalized discriminant analysis and hierarchical SVM construction method for the degradation and classification, respectively, to achieve the recognition of the sport in sports teaching. Finally, the effectiveness of the system and teaching model was tested and evaluated through the use of Loadrunner and SPSS software. The results show that the response time is 2s when the number of concurrent users is 100, the utilization rate of CPU is 64.2%, and the mastery of sports knowledge and movement skills of the experimental class is higher than that of the control class by 0.18 and 0.26, respectively. The innovative teaching mode of physical education in this study is effective.

I am a Genius! Influence of Virtually Embodying Leonardo da Vinci on Creative Performance.

Virtual reality (VR) provides users with the ability to substitute their physical appearance by embodying virtual characters (avatars) using head-mounted displays and motion-capture technologies. Previous research demonstrated that the sense of embodiment toward an avatar can impact user behavior and cognition. In this paper, we present an experiment designed to investigate whether embodying a well-known creative genius could enhance participants' creative performance. Following a preliminary online survey (N = 157) to select a famous character suited to the purpose of this study, we developed a VR application allowing participants to embody Leonardo da Vinci or a self-avatar. Self-avatars were approximately matched with participants in terms of skin tone and morphology. 40 participants took part in three tasks seamlessly integrated in a virtual workshop. The first task was based on a Guilford's Alternate Uses test (GAU) to assess participants' divergent abilities in terms of fluency and originality. The second task was based on a Remote Associates Test (RAT) to evaluate convergent abilities. Lastly, the third task consisted in designing potential alternative uses of an object displayed in the virtual environment using a 3D sketching tool. Participants embodying Leonardo da Vinci demonstrated significantly higher divergent thinking abilities, with a substantial difference in fluency between the groups. Conversely, participants embodying a self-avatar performed significantly better in the convergent thinking task. Taken together, these results promote the use of our virtual embodiment approach, especially in applications where divergent creativity plays an important role, such as design and innovation.

Exploring attunement among clinicians-in-training via group drumming

Referring to profound, deeply felt and embodied states of oneness, experiences of attunement are foundational to healthy human development. In clinical practice, these experiences promote therapeutic alliance and support healing, particularly in the context of relational wounding. Occurring through a process of ‘tuning in,’ attuned states contribute to the development of relationally based and embodied knowledge and may be facilitated through group arts-based experiences. Within this exploration of attunement, master’s level clinicians-in-training engaged in an improvisational group drumming intervention. Drawing on a synthesis of knowledge from diverse fields, multimodal forms of measurement, including perceptual, behavioral, and physiological, were utilized to elucidate and contextualize an occurrence of attunement. Findings shed light on the phenomenon of attunement, its relevance to the education of mental health practitioners and arts-based therapies, and how it may be facilitated to promote effective clinical practice. Use of advanced motion capture and physiological monitoring technologies opens doors for future research focused on the interpersonal nature and benefits of arts-based interventions.

The existing motion capture technologies and their application

Motion Capture technology refers to the technology of recording and processing the actions of people or other objects, and generating corresponding virtual asset action animations. It has been widely used in our daily life. Virtual characters like Hulk, Gollm, and Avatar were all built based on the technology. It can also be applied to sports analysis, human biomechanics, automotive, virtual reality, etc, showing its huge application prospects. Specifically, 3D Motion Capture Market was forecast to reach $270.9 million by 2026 suggested by industry ARC. To help readers get familiar with the field without much background knowledge, this paper reviews the origin of the motion capture technology, the way motion capture technology was realized and the mainstream methodologies of capturing motion. This paper provides the reader with some existing applications of motion capture technology in different fields so that the reader can understand the importance of the technique. Readers can also get some insight into what future studies may be focused on and if there is any promotion of the motion-capturing methods.

Risks that induce bicycle accidents: Measurement and analysis of bicyclist behavior while going straight and turning right using a bicycle simulator

In 2021, 69 % of those who died in Japan while riding a bicycle were of an older age. Preventing such accidents is an important issue because older bicyclists are more likely to be fatally injured in an accident. We developed a bicycle simulator that can safely simulate dangerous traffic environments by combining VR technology, motion capture technology, and various sensors to investigate the driving behavior of bicyclists who are involved in accidents. The simulator measures operating data such as floor reaction force, wheel rotation angle, brake lever displacement, position and posture of motion capture devices, and position and posture of the bicycle and vehicles at 60 Hz. We projected images of the virtual traffic environment to reflect the driving behavior in real-time onto three screens installed at the front, right side, and rear of the bicycle using three projectors. The constructed simulator was implemented for a “crossing inspection” where a rider checks for safety in front and behind while riding down a straight road with one lane and crossing this roadway and compared this to a “tracing inspection” where a model route is traced using a previously measured safe route taken by a younger rider. We measured and analyzed the bicyclist behaviors of nine younger and six older participants during two types of inspections as a usability study. In the crossing inspection, the crash rate for the older riders in the near lane was 5.3 times higher than that for the young. Riders collided with vehicles exhibited minimal rearward checking angles before entering a roadway, extended durations from the end of the last rearward check to roadway entry, and considerable standard deviations during road crossings. Moreover, in the tracing inspection, younger participants demonstrated superior trajectory passage rates and maintained closer proximity to the model, whereas older participants manifested diminished trajectory passage rates and remained at more extended distances from the model. Notably, a declining trajectory passage rate corresponded to an increase in the standard deviation of the crossing route and the time taken to enter the roadway.

Retracted: The Construction of Basketball Training System Based on Motion Capture Technology.

[This retracts the article DOI: 10.1155/2021/2481686.].

Clinical gait analysis 1973–2023: Evaluating progress to guide the future

Clinical gait analysis has been used to inform treatment for over 50 years. Over that period there have been significant advances in motion capture technology and software development, driven in part by innovations in biomechanics. The aim of this paper is to review the current state of the art in gait analysis, mapping progress over the last five decades using the collective experience of the community of researchers and clinicians.An online survey was circulated to gait analysts to canvas opinion and responses were received from 229 people from 28 countries.Respondents identified the greatest progress in the areas of hardware, automation of processes, and software development. Despite laboratories being better equipped, many of today’s challenges would have been very familiar to those working in 1973. Better algorithms and more evidence are needed to establish a secure link between gait analysis data and clinical decision making. Biomechanical models require further refinement to overcome well known limitations. Despite innovation, clinical gait analysis remains relatively unknown in the wider healthcare field.Growth in the global Gait Analysis communities and advances in remote communication technology have created new opportunities for taking on this challenge over the next 50 years. Hopefully, future innovation will lead to clinical gait analysis becoming more accessible, more flexible to real world mobility and more able to exploit emerging advanced modelling techniques.

Kinematic and Kinetic Comparisons of Arm Slot Position Between High School and Professional Pitchers.

Throwing arm kinetics differ in pitchers at varying arm slot (AS) positions (frontal-plane arm position at ball release relative to the vertical axis). To determine how kinematic and kinetic values differ between professional and high school pitchers with varying AS positions, and whether these differences are similarly observed in both populations. High school (n = 130) and professional (n = 288) pitchers threw 8 to 12 fastballs under 3-dimensional motion capture technology. Pitchers in each cohort were subdivided based on mean AS position at ball release: AS1 (least degree of AS: most overhand throwing styles), AS2 (intermediate degree of AS: three-quarter throwing styles), or AS3 (greatest degree of AS: most sidearm throwing styles). Kinetic and kinematic parameters were compared between groups. Controlled laboratory study. High school pitchers had a more overhand AS at ball release (50° ± 11°) compared with professional pitchers (58° ± 14°) (P < .001). In both cohorts, AS1 pitchers had significantly greater shoulder abduction (high school, P <0.001; professional, P <0.0001) and lateral trunk flexion (high school, P < 0.001; professional, P <0.0001) at ball release compared with AS3 pitchers. Professional pitchers with an AS3 position had significantly delayed timing of maximum upper trunk angular velocity compared with AS1 pitchers (64% ± 7% vs 57% ± 7% of pitch time, respectively; P < .0001). A significant positive correlation between AS and elbow flexion torque was found in high school pitchers (P = .002; β = 0.28), and a significant negative correlation between AS and elbow varus torque (P < .001; β = -0.22) and shoulder internal rotation torque (P < .001; β = -0.20) was noted in professional pitchers. AS position was related to shoulder abduction and trunk lateral tilt. Professional and high school pitchers with varying AS positions did not experience similar changes in throwing arm kinetics. In professional pitchers, the earlier onset of maximum upper trunk angular velocity with overhand throwing style may reflect inappropriate pelvis-trunk timing separation, a parameter implicated in upper extremity injury, and the negative correlation between AS and elbow varus and shoulder internal rotation torque suggests that both excessive and minimal AS positions have negative implications.