Motion Tracking Technology Research Articles

Kinetic Connections: Exploring the Impact of Realistic Body Movements on Social Presence in Collaborative Virtual Reality

Professional and personal lives are undergoing a shift from physical to virtual meetings. While this offers numerous advantages, such as increased spatial autonomy, it also poses risks to the social bonds among employees, families, and friends. Even current collaborative virtual reality (VR) applications cannot bridge the separation in virtual meetings, as they do not provide a sense of social connectedness comparable to in-person interaction. Reasons include limited behavioral realism of VR avatars, e.g., in displayed body movements. We systematically investigated how realistic body movements influence Social Presence in a collaborative VR task. We explored three types of motion-tracking mechanisms: no motion-tracking beyond controllers, hand-tracking, and full-body motion-tracking with hand-tracking. To examine their influence on Social Presence, we designed a spatial collaboration task based on insights gained from semi-structured interviews ( N = 6). Subsequently, we conducted a controlled VR experiment ( N = 18), in which participants' counterparts employed the various motion-tracking technologies while performing said task. Our results demonstrate that realistic body movements do not influence self-reported Social Presence in VR. Nevertheless, they entail an increased interpersonal distance among users, attributable to a subconscious influence on Social Presence.

Анализ рынка нейромаркетинговых технологий и оценка их роли в повышении эффективности восприятия контента

The results of a study of the dynamics of the global market of neuromarketing technologies, in particular the market of eye movement tracking technology (eyetracking), are presented. The conclusion is made about the existing positive dynamics: in recent years, the market has been showing annual growth and, according to experts, by 2032 it may reach a value of $ 3.2 billion.; as well as the high demand for neuromarketing technologies in various fields such as healthcare, retail, the gaming industry, automotive, advertising, etc., due to the growing needs of businesses in monitoring consumer behavior, uncovering subconscious motives and emotional triggers in order to adapt company strategies to the needs of the target audience. The analysis of the market structure by region is carried out: the largest market share belongs to North America, the Asia-Pacific region and Europe. The dominant regions in the eyetracking market are North America and Europe. Neuromarketing tools are applicable for conducting research and experiments in various fields and allow you to measure responses to product advertising, packaging, price, ease of use, assessment of emotional state, as well as human perception of content posted on a website, advertising surface or presentation slides. Experiments with the use of trackers make it possible to understand how a person perceives information, what he reads first of all, what he looks at. The results of existing experiments with the use of eye trackers allow you to make decisions about content and its rational placement on the surface (slides, website, advertising banners, etc.), maximizing meaningful interaction. Further research and experiments are needed to optimize marketing efforts and increase the effectiveness of interaction with consumers.

Agreement in Knee Flexion and Hip Extension Range of Motion Assessment between Digital Goniometer and Video-based Motion Tracking Technology

Precise range of motion (ROM) measurements are critical for diagnosing musculoskeletal impairments, planning treatment strategies and monitoring rehabilitation progress. This study compares the reliability and accuracy of ROM measurements using the EasyAngle electronic goniometer device and the Kemtai pose estimation video-based motion tracking software. Participants performed hip extension and knee flexion movements, with measurements taken by two examiners using both tools. The results show that both EasyAngle and Kemtai provide high inter-repetition reliability for knee flexion (ICC 0.93 and. 0.91) and hip extension (ICC 0.96 and 0.93). Kemtai generally overestimated ROM compared to EasyAngle, with relative agreement ranging from poor to good (ICC = 0.71 for knee flexion, ICC = 0.66 for hip extension). Future development and research should focus on refining digital tools like Kemtai to enhance their accuracy and reliability. Given its low cost and ease of use, Kemtai could be a useful tool for clinical practice.

Preliminary Experience with Three Alternative Motion Sensors for 0.55 Tesla MR Imaging.

Due to limitations in current motion tracking technologies and increasing interest in alternative sensors for motion tracking both inside and outside the MRI system, in this study we share our preliminary experience with three alternative sensors utilizing diverse technologies and interactions with tissue to monitor motion of the body surface, respiratory-related motion of major organs, and non-respiratory motion of deep-seated organs. These consist of (1) a Pilot-Tone RF transmitter combined with deep learning algorithms for tracking liver motion, (2) a single-channel ultrasound transducer with deep learning for monitoring bladder motion, and (3) a 3D Time-of-Flight camera for observing the motion of the anterior torso surface. Additionally, we demonstrate the capability of these sensors to simultaneously capture motion data outside the MRI environment, which is particularly relevant for procedures like radiation therapy, where motion status could be related to previously characterized cyclical anatomical data. Our findings indicate that the ultrasound sensor can track motion in deep-seated organs (bladder) as well as respiratory-related motion. The Time-of-Flight camera offers ease of interpretation and performs well in detecting surface motion (respiration). The Pilot-Tone demonstrates efficacy in tracking bulk respiratory motion and motion of major organs (liver). Simultaneous use of all three sensors could provide complementary motion information outside the MRI bore, providing potential value for motion tracking during position-sensitive treatments such as radiation therapy.

Virtual reality, electrophysiology & motion tracking technologies in mental illnesses

The following mini-review paper explores the integration of Virtual Reality (VR), motion tracking, and electrophysiological sensors in the context of exposure therapy and mental health treatment. These technologies collectively offer innovative approaches for enhancing therapeutic goals, providing immersive environments, and enabling precise monitoring of physiological responses. The paper discusses their applications, benefits, and potential challenges, underscoring their transformative impact on mental health care.

Development of an ICT Laparoscopy System with Motion-Tracking Technology for Solo Laparoscopic Surgery: A Feasibility Study

The increasing demand for laparoscopic surgery due to its cosmetic benefits and rapid post-surgery recovery is juxtaposed with a shortage of surgical support staff. This juxtaposition highlights the necessity for improved camera management in laparoscopic procedures, encompassing positioning, zooming, and focusing. Our feasibility study introduces the information and communications technology (ICT) laparoscopy system designed to aid solo laparoscopic surgery. This system tracks a surgeon’s body motion using a controller, manipulating an embedded camera to focus on specific surgical areas. It comprises a camera module, a camera movement controller, and a motor within the main body, operating connected wires according to controller commands for camera movement. Surgeon movements are detected by an inertial measurement unit (IMU) sensor, facilitating precise camera control. Additional features include a foot pedal switch for motion tracking, a dedicated trocar for main body stability, and a display module. The system’s effectiveness was evaluated using an abdomen phantom model and animal experimentation with a porcine model. The camera responded to human movement within 100 ms, a delay that does not significantly affect procedural performance. The ICT laparoscopy system with advanced motion-tracking technology is a promising tool for solo laparoscopic surgery, potentially improving surgical outcomes and overcoming staff shortages.

Research on Evaluation and Optimization Algorithm of Athletes' Sports Skills Based on Trajectory Analysis and Machine Learning

Evaluating athletes' sports skills is significant for optimizing their training strategies and improving competitive outcomes. Although various studies are done to assess athletes' skills, they face challenges because of their limitations in capturing the complex, intricate patterns in athletes' movements. Hence, we proposed an innovative approach utilizing trajectory analysis and machine learning algorithms to evaluate and optimize athletes' sports skills. Initially, the trajectory data is collected using advanced motion tracking technology during either training or competitive sessions of the athletes. The collected data was pre-processed, and then feature extraction was performed to extract the most important and relevant features within the data. Further, the Gradient Boosting Decision Tree (GBDT) was trained using the extracted features to predict the athletes' performances. The GBDT is a powerful machine learning algorithm that can handle complex, non-linear interconnections among variables, enabling it to accurately predict the athletes' performances. Finally, we applied the Whale Optimization Algorithm (WOA) to refine the training process of the GBDT, enabling precise training and accurate predictions. The proposed methodology was implemented in the MATLAB software, and it is validated using the real-world athlete data collected during training sessions. The experimental results are validated in terms of parameters such as accuracy, precision, recall, and f-measure. Furthermore, we made a comparative study with the existing methods to validate the effectiveness and robustness of the proposed technique.

Innovative Application of Computer Vision and Motion Tracking Technology in Sports Training

The use of cutting-edge technology has resulted in a significant enhancement in athletic training. Computer vision and motion tracking are very important for enhancing performance, reducing the risk of accidents, and training in general. Some computer vision algorithms investigate how a sportsperson moves when competing or practising. It is possible that coaches who continuously evaluate their players’ posture, muscle activation, and joint angles would have a better understanding of biomechanical efficiency. It is possible to generate performance measurements from the real-time surveillance of athletes while competing in sports. Through the use of computer vision, it is possible to identify acts that might be hazardous. Notifications are given to coaches if there is a deviation in the form of an athlete, which enables them to address the situation as soon as possible. The three variables that these sensors monitor are the direction, speed, and acceleration. Athletes can encounter realistic environments thanks to the integration of motion tracking with virtual reality. One may use the feedback loop to increase their spatial awareness and decision-making ability. Augmented reality allows for enhancing an athlete’s eyesight by providing them with real-time data while practising. Last but not least, the use of computer vision and motion tracking is bringing about a significant improvement in the sporting training process. Through collaborative efforts, researchers, athletes, and coaches can accelerate humans' performance to levels that have never been seen before.

An augmented reality-guided biopsy system using a high-speed motion tracking and real-time registration platform.

Biopsies play a crucial role in diagnosis of various diseases including cancers. In this study, we developed an augmented reality (AR) system to improve biopsy procedures and increase targeting accuracy. Our AR-guided biopsy system uses a high-speed motion tracking technology and an AR headset to display a holographic representation of the organ, lesions, and other structures of interest superimposed on real physical objects. The first application of our AR system is prostate biopsy. By incorporating preoperative scans, such as computed tomography (CT) or magnetic resonance imaging (MRI), into real-time ultrasound-guided procedures, this innovative AR-guided system enables clinicians to see the lesion as well as the organs in real time. With the enhanced visualization of the prostate, lesion, and surrounding organs, surgeons can perform prostate biopsies with an increased accuracy. Our AR-guided biopsy system yielded an average targeting accuracy of 2.94 ± 1.04 mm and can be applied for real-time guidance of prostate biopsy as well as other biopsy procedures.

Exploring injury assessment using motion tracking technology and ergonomic tools in archery performance

Introduction: Archers face a notable annual risk of injury attributed to the repetitive strain exerted on their upper body muscles and joints. This groundbreaking study marks the first utilization of real-time motion tracking combined with ergonomic analysis in archery research, eliminating the need for extensive equipment setups and streamlining data collection.Methods: Thirteen participants were involved, undertaking four tasks with varying draw weights of bows and target positions.Results: The precise recording of human movements revealed distinctive postures adopted by both genders across different tasks. Furthermore, an assessment of exposed spinal force and its correlation with anatomical variables was conducted, providing valuable insights into injury risks during archery performances.

Optimizing wearable motion tracking by assessing sagittal joint angle accuracy with minimal sensor use

Introduction
 Wearable motion tracking technology often focuses on reducing the number of sensors to simplify design and lower costs. Research has shown that single IMUs can reconstruct leg kinematics (Gholami et al., 2020; Hossain et al., 2022; Lim et al., 2020) and ground reaction forces (Jiang et al., 2020) effectively. Additionally, model-based methods have demonstrated the feasibility of using fewer gyroscopes to estimate stride length and motion range in healthy individuals and patients with coxarthritis (Salarian et al., 2013). In this study, we aim to assess the precision of sagittal joint angle estimations using strain sensors while minimizing sensor count.
 Methods
 We conducted a study with ten participants based on our previous work that involved collecting single-leg treadmill running data to monitor lower limb joint angles with piezoresistive strain sensors. Subjects ran on an instrumented treadmill at 8-10 km/h, wearing athletic pants embedded with nine strain sensors located on the hip, knee, and ankle. Optical motion capture provided reference kinematics. Our prior research achieved less than 1.5° error in the sagittal plane using a machine-learning approach. The current study explores the extent to which sensor reduction is possible without meaningful loss of accuracy. Three evaluation measures were used for assessment: Pearson correlation, dynamic time warping, and root-mean-squared error.
 Results
 The results from our correlation analysis will be used to develop a model that optimally balances between accuracy and minimizing the number of sensors. This has practical implications in sports science, where athletes could benefit from less intrusive and more comfortable performance monitoring, and in healthcare, for remote monitoring of patients with mobility issues.
 References
 Gholami, M., Napier, C., & Menon, C. (2020). Estimating lower extremity running gait kinematics with a single accelerometer: A deep learning approach. Sensors, 20(10), Article 2939. https://doi.org/10.3390/s20102939
 Hossain, M. S., Bin, Dranetz, J., Choi, H., & Guo, Z. (2022). DeepBBWAE-Net: A CNN-RNN based deep superlearner for estimating lower extremity sagittal plane joint kinematics using shoe-mounted IMU sensors in daily living. IEEE Journal of Biomedical and Health Informatics, 26(8), 3906-3917. https://doi.org/10.1109/jbhi.2022.3165383
 Jiang, X., Napier, C., Hannigan, B., Eng, J. J., & Menon, C. (2020). Estimating vertical ground reaction force during walking using a single inertial sensor. Sensors, 20(15), Article 4345. https://doi.org/10.3390/s20154345
 Lim, H., Kim, B., & Park, S. (2020). Prediction of lower limb kinetics and kinematics during walking by a single IMU on the lower back using machine learning. Sensors, 20(1), Article 130. https://doi.org/10.3390/s20010130
 Salarian, A., Burkhard, P. R., Vingerhoets, F. J. G., Jolles, B. M., & Aminian, K. (2013). A novel approach to reducing number of sensing units for wearable gait analysis systems. IEEE Transactions on Biomedical Engineering, 60(1), 72–77. https://doi.org/10.1109/TBME.2012.2223465

Effects of Screen Color Mode and Color Temperature on Visual Fatigue under Different Ambient Illuminations

Viewing electronic screens for a long time can cause visual fatigue, even induce eye problems such as refractive errors, dry eyes, etc. The relationship between screen display and visual fatigue has received much attention. This article aims to study the optimal display color temperature and color mode under two common ambient illuminations—normal office lighting (450 lux) and dark environment (3 lux). In a 2 × 2×3 experimental design, 36 participants evaluated the effects of two display color modes (light mode and dark mode) and three screen color temperatures (2800 K, 4500 K, and 6500 K) on visual fatigue under two ambient illuminations. We used eye movement tracking technology to collect blink rate and pupil diameters as objective indicators and used the Richter scale to collect subjective visual fatigue and preference score as subjective indicators. Results showed that at 450 lux, lower visual fatigue was found in the dark mode, 4500 K and 6500 K. At 3 lux, the visual fatigue was lower in the dark mode and 4500 K color temperature. Whether at daytime or night, the 2800 K color temperature resulted in the highest visual fatigue. Our findings complement the research on screen display and visual fatigue. They have practical implications for reducing visual fatigue caused by prolonged viewing of electronic screens.

Integration of Virtual Reality and Motion Tracking Technologies for Enhanced Physical Rehabilitation: a Narrative Review

The recent application of Virtual reality (VR) and Motion Tracking Technologies (MTT) in physical rehabilitation is an emerging area addressing the insufficiencies of conventional methods. In this review paper, we describe how VR and MTT interact with each other and elaborate on their mutual capacities to improve treatment results in physical rehabilitation. This problem can be specified as the limited effectiveness of conventional rehabilitation methods in promoting patient motivation and engagement. VR and MTT are emerging innovations; however, their combined utilization for rehabilitation needs a detailed analysis to reveal their applicability and benefits. The primary purpose of this review is to assemble recent studies on VR and MTT application in physical rehabilitation, emphasizing the efficacy, specific domains where they can be used, and the peculiarities of their application in clinical practice. A narrative review method was employed for this paper, which covered a wide range of peer-reviewed articles, clinical trials, and metaanalyses. A significant finding of this study shows that VR and MTT, when used in combination, contribute to the substantial improvement in patient outcomes in motor function, balance, and cognitive recovery. The article's novelty is that it analyses the integrated use of virtual reality and mobile training technologies in rehabilitation, thus revealing its potential to overcome the limitations inherent in traditional therapies and ensure more intensive involvement and individualized treatment. The empirical significance of this study can be helpful for healthcare professionals and physical therapists who seek new ways and directions in their work with patients. Scope of Further Investigations: In terms of future research, this paper suggests the necessity of large-scale, randomized controlled trials to identify standard protocols, explore long-term impacts of the integration, and investigate applications in less-known rehabilitation domains. The authors emphasize that successful implementation requires a collaborative effort between healthcare professionals, engineers, and researchers to design appropriate protocols tailored to individual patient needs.

A survey on location and motion tracking technologies, methodologies and applications in precision sports

Sports involve commonly players and equipment of high dynamics. Their location and motion data are essential for sports digitalization-related applications, such as from monitoring player skill level to even media presentation of sports. Location and motion data of players and equipment are important elements for precision sport analytics. With the popularization of the Internet of things, a variety of sports location and motion tracking technologies have advanced in terms of sensors and tracking methodologies to achieve ubiquitous coverage from outdoors to indoors, higher precision, and applicability for increasing sports scenarios. This paper presents a systematic survey on location and motion tracking technologies that have been applied in sports to drive various sports-related analytics and applications. First, several wearable sensor-based technologies are introduced with their principles, advantages and shortages in sports, and the location and motion tracking methods of each technology. Then, vison-based technology and its methodologies that detect, track, and recognize objects including human and equipment in sports are illustrated. Furthermore, sports-related data analytics and applications are presented using location and motion data of human and equipment. Data privacy and ethics are also focused based on the location and motion tracking technologies. Finally, challenges and further development of location and motion tracking in precision sports are discussed. The comprehensive survey provides a survey about state-of-the-art of location and motion sensors and methodologies, as well future trends of these technologies, which are beneficial for developing forthcoming precision sports.

Endoscopic measurement of the size of gastrointestinal polyps using an electromagnetic tracking system and computer vision-based algorithm

PurposePolyp size is an important factor that may influence diagnosis and clinical management decision, but estimation by visual inspection during endoscopy is often difficult and subject to error. The purpose of this study is to develop a quantitative approach that enables an accurate and objective measurement of polyp size and to study the feasibility of the method.MethodsWe attempted to estimate polyp size and location relative to the gastro-oesophageal junction by integrating data from an electromagnetic tracking sensor and endoscopic images. This method is based on estimation of the three-dimensional coordinates of the borders of the polyp by combining the endoscope camera position and the corresponding points along the polyp border in endoscopic images using a computer vision-based algorithm. We evaluated the proposed method using a simulated upper gastrointestinal endoscopy model.ResultsThe difference between the mean of ten measurements of one artificial polyp and its actual size (10 mm in diameter) was 0.86 mm. Similarly, the difference between the mean of ten measurements of the polyp distance from the gastroesophageal junction and its actual distance (~ 22 cm) was 1.28 mm. Our results show that the changes in camera positions in which the images were taken and the quality of the polyp segmentation have the most impact on the accuracy of polyp size estimation.ConclusionThis study demonstrated an innovative approach to endoscopic measurements using motion tracking technologies and computer vision and demonstrated its accuracy in determining the size and location of the polyp. The observed magnitude of error is clinically acceptable, and the measurements are available immediately after the images captured. To enhance accuracy, it is recommended to avoid identical images and instead utilise control wheels on the endoscope for capturing different views. Future work should further evaluate this innovative method during clinical endoscopic procedures.

Quantitative Model Study of the Psychological Recovery Benefit of Landscape Environment Based on Eye Movement Tracking Technology

From the perspective of landscape and human health, we use the Self-Rating Restoration Scale (SRRS) as a tool to explore the mental health restoration benefits brought by a landscape environment to individuals and explore the characteristics of individual movement behavior when viewing the landscape through the eye movement tracking technology. We selected average blink duration, average gaze length, average saccade amplitude, blink number, number of fixation points, saccade number, and average pupil diameter as experimental indicators for data monitoring. Based on the eye movement heat map obtained by data visualization processing and the results of correlation analysis, we summarized the eye movement behavior characteristics of individuals when viewing the restorative landscape. We try to construct a quantitative evaluation model of the landscape mental recovery benefit with the objective eye movement index as the independent variable through the method of curve estimation. The study results show that individual eye movement behavior is related to the landscape type and the level of psychological recovery is also different. (1)The more singular that the constituent elements are, the more widespread and concentrated the regional distribution of individual attention areas, and the relative psychological recovery benefit is relatively weak. The more complex that the constituent elements are, the more scattered and smaller the individual interest area, and the psychological recovery benefit is better. Brightly colored, dynamic landscapes are easier to form areas of interest to improve the psychological response to the human body. (2) The psychological recovery benefit of the landscape is directly proportional to the changing trend of the average blink duration, number of fixation points, and number of saccades and is inversely proportional to the changing trend of the average gaze length. (3) The objective eye movement index of average blink duration can quantitatively predict the psychological recovery benefit value of the landscape environment. The number of fixation points, the number of saccades, and the average fixation length could predict the psychological recovery benefits of the landscape, while the other indicators had no prediction effect.

An Automated Skill Assessment Framework Based on Visual Motion Signals and a Deep Neural Network in Robot-Assisted Minimally Invasive Surgery.

Surgical skill assessment can quantify the quality of the surgical operation via the motion state of the surgical instrument tip (SIT), which is considered one of the effective primary means by which to improve the accuracy of surgical operation. Traditional methods have displayed promising results in skill assessment. However, this success is predicated on the SIT sensors, making these approaches impractical when employing the minimally invasive surgical robot with such a tiny end size. To address the assessment issue regarding the operation quality of robot-assisted minimally invasive surgery (RAMIS), this paper proposes a new automatic framework for assessing surgical skills based on visual motion tracking and deep learning. The new method innovatively combines vision and kinematics. The kernel correlation filter (KCF) is introduced in order to obtain the key motion signals of the SIT and classify them by using the residual neural network (ResNet), realizing automated skill assessment in RAMIS. To verify its effectiveness and accuracy, the proposed method is applied to the public minimally invasive surgical robot dataset, the JIGSAWS. The results show that the method based on visual motion tracking technology and a deep neural network model can effectively and accurately assess the skill of robot-assisted surgery in near real-time. In a fairly short computational processing time of 3 to 5 s, the average accuracy of the assessment method is 92.04% and 84.80% in distinguishing two and three skill levels. This study makes an important contribution to the safe and high-quality development of RAMIS.

Advanced Procedures for Series Production with 3D-Printed Core Packages

The application of additive-manufactured cores and molds is of great interest for complex cast components. Nevertheless, several challenges still exist in utilizing binder jetting in the multi-step additive manufacturing process for foundry applications to its fullest extent. This contribution shows methods that facilitate the use of 3D-printed sand molds and cores in casting series applications. The binder jetting process itself is assessed from an overall process chain perspective to highlight the benefits of its application in series production. The challenges associated with automating mold cleaning for highly complex casting contours are depicted. In particular, employing the method of cleanable mold partitioning is shown to enhance the automation level of the overall process. Mold design tailored to 3D printing is demonstrated to contribute to overall cost and time savings in enhanced core packages. Topology-optimized, lightweight part designs involving complex freeform surfaces may require mold partitioning associated with laborious burr removal processes. A new approach in answer to the shortage of skilled workers in the harsh and hazardous foundry environment is shown. Implementing motion tracking technology is demonstrated to enable economical automated burr removal for minor quantities or high variant diversity in the future foundry. All the methods shown are of great importance for introducing printed core packages into series production.

Documenting a Reduction in Signing Space in Nicaraguan Sign Language Using Depth and Motion Capture

In this paper, we use motion tracking technology to document the birth of a brand new language: Nicaraguan Sign Language. Languages are dynamic entities that undergo change and growth through use, transmission, and learning, but the earliest stages of this process are generally difficult to observe as most languages have been used and passed down for many generations. Here, we observe a rare case of language emergence: the earliest stages of the new sign language in Nicaragua. By comparing the signing of the oldest and youngest signers of Nicaraguan Sign Language, we can track how the language itself is changing. Using motion tracking technology, we document a decrease in the size of articulatory space of Nicaraguan Sign Language signers over time. The reduction in articulatory space in Nicaraguan Sign appears to be the joint product of several decades of use and repeated transmission of this newlanguage.

YouTubers vs. VTubers: Persuasiveness of human and virtual presenters in promotional videos

With the recent advances in motion tracking technologies and three-dimensional computer graphics software, communication through avatars has become increasingly popular. Can avatars be sufficiently persuasive, when compared to traditional forms of interpersonal communication? What factors contribute to the persuasiveness of virtual influencers? Existing literature has studied the differences in persuasiveness between human and virtual speakers extensively, particularly in education. However, few studies have been conducted on product promotion. Therefore, in this study, we investigated the characteristics of persuasiveness for humans and virtual influencers, as well as the differences between them in this regard in a more modern and practical situation: product introduction videos used in influencer marketing. Specifically, we recruited participants to watch product introduction videos on YouTube, presented by either humans or avatars. The videos were similar, except for the appearance of the presenter. Before and after watching the videos, the participants were asked to complete a questionnaire about their willingness to purchase the products and the characteristics of presenters' persuasiveness. The results show that although promotion via avatars can increase the participants' willingness to purchase, human influencers were more persuasive. However, the virtual YouTubers (VTubers) were more persuasive in certain product domains. VTubers who can change their appearance to match the product domain have potential for future applications. We also attempted to construct a model of persuasiveness in this pragmatic context based on Dyson's persuasiveness rating scale and the overall impression of the video. The degree of persuasiveness was found to be related to the presenters' likability, whether the presenter was a human or an avatar, the degree of familiarity between the presenter and the audience, the presenters' trustworthiness, and the quality as well as the entertainment level of the video. This model may be helpful for running successful promotions on YouTube. Our findings verify that avatars can be fairly persuasive in some situations, including promotional videos. These findings contribute to the future development of communication through avatars.