
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39261561
72095
10.1038/s41598-024-72095-7
Article
Sense of embodiment with synchronized avatar during walking in mixed reality
Tan Guoran
Uchitomi Hirotaka uchitomi@c.titech.ac.jp

Isobe Ryo
Miyake Yoshihiro
https://ror.org/0112mx960 grid.32197.3e 0000 0001 2179 2105 Department of Computer Science, School of Computing, Tokyo Institute of Technology, Yokohama, 226-8502 Japan
11 9 2024
11 9 2024
2024
14 2119816 6 2024
3 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Gait guidance systems that synchronize the gait rhythm with an avatar in a mixed reality (MR) environment are attracting attention owing to their rehabilitation applications. More effective gait guidance can be achieved by changing body sensations for the sense of embodiment (SoE), which refers to the feeling of owning, controlling, and being inside a body in MR. This study investigated full-body synchronous motion between a human and a virtual avatar to enhance the SoE in walking with actual position changes in the real world. The full-body motion and gait rhythm were measured using body-worn inertial measurement units and a visual avatar was provided through a transparent head-mounted display. The results showed that the SoE of the participants was enhanced under higher synchronization conditions. In addition, questionnaire results showed that the SoE in the synchronous condition was significantly higher than that in the asynchronous condition, and the SoE in the self-avatar condition was significantly higher than that in the other-avatar condition. This indicates that a higher synchronization level with the appearance of an avatar leads to a stronger SoE in the human perception mechanism, which is important for potential application in medical or other fields.

Subject terms

Psychology
Human behaviour
Information technology
Japan Society for the Promotion of Science22K17630 Uchitomi Hirotaka http://dx.doi.org/10.13039/501100002241 Japan Science and Technology Agency JPMJCR21C5 Miyake Yoshihiro issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

In recent years, mixed reality (MR) technologies combining virtual reality (VR) and augmented reality (AR) have revolutionized the manner in which people perceive and interact with the digital world by blurring the boundaries between the physical and virtual realms1,2. Avatars that represent personalized visualizations of users are used extensively in numerous tasks in MR, including the areas of robotic control and remote collaboration as well as medical rehabilitation. Our research group investigated a system wherein an MR avatar can walk with the human user for gait rehabilitation and gait guidance3. The avatar changed the movement during synchronized walking between the avatar and user, which affected the user gait movement, thereby demonstrating potential for actual clinical application. Specifically, when changes such as increasing or decreasing the distance between the user and the avatar, and changing the foot strike timing to slightly earlier or later than that of the user, are implemented during cooperative walking between the user and the avatar, the movement pattern of the user is affected.

To create a more immersive MR experience and improve application outcomes, improved fusion of virtual objects with the real world and a stronger perception of the virtual body must be considered. Recognizing one’s body is crucial for self-consciousness. The sense of embodiment (SoE) is elicited based on internal and external information, including different sensory stimulations4–7. The SoE has three subcomponents: sense of ownership (feeling that “this body is my own”), sense of agency (feeling that “this body is under my control”), and sense of self-location (feeling that “this body’s position is where I am inside”). Importantly, our SoE is related to the real body, and the SoE that occurs for the self-avatar in MR can affect the real body. This enhancement of physical sensation is expected to be effective in medical rehabilitation and other physical training.

The SoE over a person’s own body can be manipulated and expanded to that over an external virtual body from a human real body7,8. This is an extension of our bodily sensations to a third-person virtual avatar. However, rather than observing the back of our own virtual avatar body displayed in front of us, we actually perceive the virtual avatar as our own real body and feel the SoE. Lenggenhager9 proved that synchronized visual and tactile feedback could elicit a body-ownership illusion inside a virtual body. A fixed camera was used to capture a video of the participant in real time, and the video frames were transmitted and visualized through a head-mounted display (HMD) worn by the participant. Consequently, the participant perceived their body as being in front of them. The experiment involved two conditions. First, a synchronous condition, wherein the timing of a rod stroking the participant’s back was synchronized with the stroking of the avatar’s back, as viewed in the HMD. Second, an asynchronous condition, wherein the timing was not matched systematically. The results of a questionnaire regarding the SoE revealed that the synchronous condition significantly increased the sense of body ownership and agency in movement compared to the asynchronous condition. Moreover, the perception of the participant’s own body position shifted towards the frontal location of the avatar. Thus, the results of both the questionnaire and objective measurements indicated that synchronous external stimuli could elicit the illusion of the SoE from one’s own body to that of a virtual avatar. In this previous study, experimental participants stood upright and motionless; thus, the probability of the occurrence of such SoE when the participants moved their absolute position in real space was not investigated.

Previous studies have reported that the appearance of a virtual avatar and its level of synchronization were enhanced by the expansion of the SoE towards a virtual body. The appearance was closely related to the sense of ownership10. Lugrin11 and Maselli12 reported that a higher sense of ownership can be achieved when the clothes and skin tone of the avatar match those of the user, and even when certain body parts such as hands are more realistic than those of a non-anthropomorphic model. It was suggested that the SoE is stronger when the avatar is more similar to oneself. Moreover, the synchronization of an avatar is an important factor that is closely related to the judgement of the sense of agency. Fribourg10 investigated different levels of appearance and synchronization in their experiments using several levels of avatar appearances and different levels of synchronization between the participant and avatar. Their results demonstrated a higher SoE in the advanced levels of these two conditions. It was suggested that SoE can be enhanced by synchronizing the avatar’s movements with one’s own movements.

Previous studies have reported the relationship between the SoE and walking-in-place. Human steps during walking represent a full-body motion that is performed continuously, cyclically, and in a non-goal-oriented manner13,14. Lee15 studied the SoE and effects of synchronization in a walk-in-place task. Participants performed foot-stomping on a stationary platform within an area, and a virtual body was constructed and visualized using an HMD. The participants viewed their virtual lower limbs, and the movement was performed under synchronous foot-stomping with motion tracking and predetermined foot-stomping with fixed animation. The results indicated a higher sense of ownership in the synchronous condition.

As mentioned previously, existing research has reported that the SoE was elicited and enhanced in foot-stomping when somatosensory input based on walking-in-place of a real body and the visual input of virtual body movement via the HMD were synchronized. However, in this study, we moved the absolute spatial position using an actual walking motion. Gait with a moving body position is a highly automatic and unconscious body movement process. However, this aspect has not been investigated in previous studies and the SoE in the virtual body during walking movements that actually involve movement remains unclear. Therefore, this study aimed to investigate whether synchronous movement between the human and virtual avatar could elicit the SoE compared to the asynchronous movement of the avatar, with the body position of the participant changing during walking. For this purpose, we built a system wherein an MR avatar could walk with the experimental participant. We focused on both the avatar gait synchronization (synchronous and asynchronous conditions) and avatar appearance (self-avatar and other-avatar conditions) in our experiment. Previous studies have highlighted two perspectives on the induction of SoE from virtual avatars. First, the movement of the virtual avatar is synchronized with the walking-in-place movement of the participant10,15. Second, the appearance of the virtual avatar is similar to that of the participant10–12. Therefore, considering these two perspectives, this study investigated the occurrence of SoE from a virtual avatar displayed in front of the participant from a third-person perspective while the participant was walking.

Questionnaires were used as subjective metrics, whereas the gait trajectories were recorded as objective metrics for the evaluation.

Methods and experiment

Task and conditions

The experimental task comprised two separate phases, as shown in Fig. 1a: the adaption practice and walking phases. In the adaption practice phase, participants moved freely while watching the avatar move in one place to familiarize themselves with the avatar and environment. In the walking phase, participants walked through a corridor of approximately 55 m with the avatar projected in front of them. Finally, they completed a questionnaire orally while sitting on a chair.Fig. 1 Experimental task and conditions. (a) Experimental task with adaption practice phase and walking phase. (b) Synchronization conditions. In the synchronous condition, the avatar moved in the same manner as the participant, whereas in the asynchronous condition, the avatar moved independently with predetermined animation. (c) Avatar appearance conditions. In the self-avatar condition, the avatar was based on the participant, whereas in the other-avatar condition, the avatar was based on another person.

The experimental conditions are shown in Figs. 1b and c. Four conditions were established: (self, sync), representing a self-avatar with synchronous movement, (self, asyn), representing a self-avatar with asynchronous movement, (other, sync), representing an other-avatar with synchronous walking, and (other, asyn), representing an other-avatar with asynchronous walking. The self-avatar was created based on the appearance of each participant. The other-avatar was based on a person other than the participant. In the synchronous condition, the avatar moved synchronously and interactively with the participant, whereas in the asynchronous condition, the avatar moved independently with predetermined animation.

Experimental system

The systems for implementing the avatar and synchronization conditions are presented in this section.

Implementation of avatar appearance

In this study, a self-avatar was defined as an avatar that resembled the participant’s appearance. The self-avatar was created according to the following steps. First, a RealSense Depth Camera D455 (Intel) was used to scan the participant’s body information and three-dimensional (3D) modeling software (RecFusion Pro 2.3.0 ImFusion) was used to generate a 3D model of the user. Therefore, a virtual avatar was created for each participant in the experiment. The avatar matched their appearance, including gender and clothing. A turntable platform (ND-RC6008, BKL) was set for the user to stand on and rotate at a certain speed to generate a 3D model with higher accuracy and stability. Thereafter, the texture was pasted onto the generated 3D model and the 3D CG software Blender (Blender 2.93.4) was used to change the file format from obj to fbx and to adjust the size and rotation appropriately. Finally, the user 3D model that was converted into fbx format was established by manually specifying six joints using the 3D character modeling tool Mixamo (Adobe). Subsequently, the simple 3D model of the human shape was converted into a movable avatar with appropriate skeletal information. A self-portrait with the image of the person was created based on the above steps. The HoloLens2 (Windows Inc.) was used as see-through type HMD to display the virtual avatar with an external environment simultaneously. The experimental software, which was developed using Unity (2020.3.12, Unity Technologies) and is a comprehensive game development environment, was used to display the avatar 3 m in front of the user. The virtual avatar displayed on the HMD was always displayed 3 m in front of the participant. Consequently, when the participant moved forward by walking forward, the virtual avatar forward as well while maintaining a distance of 3 m from the participant.

Implementation of avatar synchronization

Two systems were used for synchronization in the adaption practice and walking phases, as explained in the following.

System for adaption practice phase

The system flowchart is shown in Fig. 2a. Participants wore a six-piece inertial measurement unit (IMU) sensor system (Sony mocopi 3D Motion Capture System) on their bodies. This IMU sensor system measured the acceleration and angular velocity of each joint in the head, wrists, hips, and ankles and output the movement information of the participants’ whole-body skeleton. The motion information of the whole-body skeleton was transmitted from this IMU sensor system to HoloLens2 via a dedicated PC server (DELL, Windows 10) using wireless communication. HoloLens2 (Microsoft) applied this whole-body skeletal motion information to the avatar and rendered the avatar in real time on the easy-through display of HoloLens2.Fig. 2 Experimental system and evaluation indices. (a) HMD (HoloLens2, Microsoft) and flowchart of experimental systems for adaption practice phase and walking phase in experimental tasks. (b) Questionnaires for evaluating SoE. (c) Virtual obstacle appearance as the threat stimulus and angle change of foot trajectory for evaluating SoE.

System for walking phase

Walking is a relatively stable, periodic movement.

In a previous study, we developed the biped virtual avatar WALK-MATE AVATAR, which can walk with the user in gait movement synchronization using interpersonal interactive gait rhythm entrainment3,16,17. Therefore, the WALK-MATE AVATAR system was used to synchronize the gait cycle of the participants.

The method that was used in previous studies was adopted to detect the timing of the foot contact3,16. The head trajectory was calculated using the acceleration data obtained from the IMU sensor that was installed on the HMD. Gait can be considered as periodic movement. Within one gait cycle, the foot contacts the ground when the vertical component of the head trajectory reaches its minimum value. In addition, the maximum values in the horizontal direction are used to determine whether the left or right foot contacts the ground. Specifically, when the head trajectory in the right (left) direction reaches its maximum value, the left (right) foot contacts the ground during the subsequent step.

As walking is periodic, the concept of phase can be introduced into the walking process. The gait phase is defined in the range of 0–2π; the phase when the left foot touches the ground is 0, whereas the phase when the right foot touches the ground is π. Thereafter, when the left foot touches the ground again, the phase returns to 2π; that is, 0 again, and then the cycle is repeated. In this case, the frequency ωh of the walking phase of a person is expressed by the following equation:1 ωh=θ˙h=πΔt

where θh denotes the gait phase of a human and Δt denotes the time interval between the left foot and right foot contact. When foot contact was detected, 0 or π was inserted into the human phase θh to update ωh.

The WALK-MATE model was used to synchronize the walking of the human and avatar system. This model is divided into submodules for synchronization between people and systems and for controlling the phase difference between them. The synchronization module can adjust the system phase to synchronize it to that of humans. The control module can control the difference between the landing time of the feet of the human and that of the avatar.

The module for synchronization between the human and system is described by Eq. (2):2 θ˙m=ωm+Kmsinθh-θm

This module accepts the previously obtained gait phase θh as the input. Further, θm is the phase of rhythm generated by the system, ωm is the natural frequency of the system, and Km is a coupling coefficient that indicates the phase error correction. The system phase θm approaches the human phase θh using this module.

The module for controlling the phase difference between the human and system is described by Eq. (3):3 ω˙m=-μsinΔθd-Δθm,

where Δθm is the phase difference between the human and system; that is, Δθm=θh-θm. In addition, Δθd is the target phase differenc and μ indicates the correction intensity. The phase difference between the human and system approaches the target phase difference using this module.

The target phase difference was set to Δθd=0 for the synchronous condition. When Δθd=0, the person and avatar always walked with the same rhythm.

In the synchronous condition, the avatar walked based on the rhythm generation model of WALK-MATE AVATAR and the walking was synchronized between the participant and avatar.

In the asynchronous condition, the avatar walked based on the predetermined walking pattern provided by Maximo (Adobe) at a predetermined gait speed and gait cycle, which was 30% faster than the normal gait speed of each participant.

Participants

A total of 10 participants were included in the experiment (9 males, 1 female, age: 24.2 ± 1.6). None of the participants had walking disorders. They could observe their heads with the naked eye through glasses. In addition, two people had previous experiences with MR, such as HoloLens2. This study was approved by the Research Ethics Review Committee of the Tokyo Institute of Technology, and all experiments were performed in accordance with the guidelines and regulations of the committee. Prior to conducting the experiment, all participants were briefed on the precautions and signed an informed consent form. Therefore, written informed consent was obtained from all participants in this study. Additionally, written informed consent was obtained from all participants in all figures for the publication of identifying information/images in an online open-access publication.

Procedure

Prior to the experiment, the participants were provided with tutorials for operating the HMD (HoloLens2), including opening and closing the program using their fingers and checking network connections. First, the adaption practice phase was performed for the participants to familiarize themselves with the avatar. When the experimenter provided instructions, the participants started moving their bodies at the starting point of the route of the walking phase to familiarize themselves with the avatar within 30 s, and another instruction was provided to stop. Subsequently, the real-world walking phase was performed. The walking environment considered was an indoor corridor with a straight path of 60 m. The participants waited for the white noise to act as a signal, performed a squatting motion, and then started walking. The squatting was added to record the triggering of starting the walking phase in the IMU data. During this process, white noise was used to prevent the influence of exterior auditory stimuli. The avatar was projected 3 m in front of the participant. When the participant reached the position of 40 m, a virtual obstacle suddenly appeared as the threat stimulus, and disappeared when they reached the position of 43 m. After reaching the destination (at 55 m), the program and gait measurements were stopped and the participants answered a questionnaire. The threat stimulus with this suddenly appearing virtual obstacle was among the methods used in the SoE evaluation in this study. The experiment was performed three times for each condition. The conditions were assigned randomly to reduce the effects of order. The participants could question any ambiguous points prior to conducting the experiment. A rest period was provided within each group and at any time when the participants requested it.

The participants were instructed to walk continuously. In the walking phase experiment, no participant stopped midway through the corridor.

The indoor corridor for the walking environment comprised a straight path of 60 m. In a previous study9, participants were provided synchronous stimulation for 60 s to test the induction of SoE to a virtual avatar. Thus, a certain period of time was required to induce SoE. This period was ensured by walking 40 m in this study.

In the walking phase experiment, the system for the walking phase was used to achieve the synchronous and asynchronous conditions. Figure S1 illustrates the realization of gait synchronization between a participant and virtual avatar. By using the above WALK-MATE model, the phase difference between the participant and virtual avatar (Δθm=θh-θm) could be stably converged to zero, and the rhythm of the virtual avatar could be generated. This meant that the rhythm of the virtual avatar can be generated to synchronize with the human rhythm. The generation of a coordinated walking rhythm by the virtual avatar for such participants was performed stably, as in previous studies17,18.

The suddenly appearing virtual obstacle was used as a threat stimulus to investigate the induction of SoE. Previous studies have suggested that threat stimuli can effectively evaluate the induction of SoE19–23. Specifically, a threat stimulus was presented to the virtual body. Consequently, the study investigated the avoidance behaviors, physical changes, and changes in questionnaire reports in response to the threat. Moreover, this study used a suddenly appearing virtual obstacle as a threat stimulus that occurred to a virtual avatar while walking.

Evaluation indices

Questionnaire

A questionnaire was used for the subjective evaluation, following a previous design24,25 with small changes. At the end of each trial, the participants were instructed to answer the questionnaire presented in Fig. 2b. There were 10 questions in total. Q1–Q9 were created based on the contents of a previous study on systemic illusion, and certain changes were made to conform to the experimental design of this study. Q10 was designed to investigate the subjective feelings towards virtual obstacles in the experiment. The experimenter displayed the questions using 10 pieces of paper that were shuffled in a random order and instructed the participants to answer orally. The questions were answered using a 7-point Likert scale ranging from − 3 to + 3, where − 3 was “no feeling at all,” 0 was “neutral,” and + 3 was “strong feeling.” Among the questionnaire items, Q1 and Q2 were related to the sense of body ownership, Q3 and Q4 were related to the sense of agency, and Q5 and Q6 were related to the sense of self-location. Furthermore, Q7 investigated whether the visual characteristics of the avatars were similar to themselves, Q8 and Q9 were control items, and Q10 investigated whether the participants wanted to avoid virtual obstacles. The expected enhancement of the SoE was considered to have occurred when Q1–Q6 were positive. Thus, we mainly report the results for Q1–Q6 for the evaluation.

The correspondence between the questionnaire employed in this study and those in the previous study is as follows. First, the questions on Ownership (Q1, Q2), Agency (Q3, Q4), and Self-location (Q5, Q6) in this study were modified to fit the experimental task. They were based on the questions on Ownership, Agency, and Self-location in the previous study25, respectively. Second, the questions on Control (Q8, Q9) and Avoidance (Q10) were modified to fit the experimental task. They were based on the questions on More body and Threat in a previous study25, respectively. Further, the question on Avatar appearance (Q7) was modified to fit the experimental task based on the questions on External appearance in another previous study24. Therefore, the study employed the questionnaire items used in the previous studies and proven to be effective in the evaluation of the induction of SoE in a virtual avatar with walking motion.

Gait trajectory

The angular change relative to the forward direction of the walking trajectory when creating virtual obstacles was used for the objective evaluation, as shown in Fig. 2c. If an individual wished to avoid a virtual obstacle as the threat stimulus when the virtual obstacle approached the avatar, the angular change relative to the forward direction was expected to increase. In contrast, if the user did not want to avoid the obstacle, the angular change relative to the forward direction was expected to decrease. The gait analysis system WM GAIT CHECKER (WALK-MATE LAB)26–28 comprising three IMU sensors for the left and right ankles was used to measure the gait trajectory. IMU sensors for measuring the acceleration and angular velocity during the walking were installed on three body parts: the left ankle, right ankle, and waist. The gait trajectories of both the left and right feet were measured. The trajectories of the five steps before and after the emergence of the obstacle were obtained to evaluate the angle change of the gait trajectory around the virtual obstacle as the threat stimulus. The coordinates when the foot left the ground and touched the ground and the angle of the trajectory relative to the forward direction of the step were obtained for each step. The average angle of the first five steps was obtained and used as the reference angle. Subsequently, the reference angle was removed from the angle of the previous five steps relative to the forward direction, and the angle with the largest absolute value was considered. The above process was performed with both the left and right feet, and the larger angle in the final obtained values was considered as the angular change relative to the forward direction in each test. As each experimental condition was performed three times by each participant, the average of the three angles was used for the analysis.

Results

The experimental results are presented in this section. “Questionnaire results“ outlines the main results of the questionnaire as the subjective evaluation, whereas “Gait trajectory“ explains the results of the gait trajectory as the objective evaluation. Statistical analysis was performed using 2 × 2 repeated ANOVA.

Questionnaire results

In this study, the degree to which the SoE occurred was evaluated using a questionnaire. The questionnaire results for Q1 to Q6, which related to the SoE, are shown in Fig. 3a and Table 1. The vertical axis represents the scores from − 3 to + 3 for Q1, which related to the sense of body ownership. Only the synchronous self-avatar condition showed a positive value. All other conditions were considered as negative. For Q2, which related to the sense of ownership, the synchronous condition exhibited a higher value, and the “self” condition scored higher than the “other” condition. For Q3 and Q4, which related to the sense of agency, the synchronous condition had a significantly higher score than the animation condition and the “self” condition also scored higher than the “other” condition. For Q5, which related to the sense of self-location, both synchronization conditions were negative but the “self” condition scored slightly higher than zero. For Q6, which was related to the sense of self-location, the synchronous condition had a higher score than the animation condition and the “self” condition also scored higher than the “other” condition. For supplementary results, Q7–Q10 were also evaluated, as shown in Fig. 3a and Table 1.Fig. 3 Questionnaire and gait trajectory results. (a) Questionnaire results for Q1–Q10. Q1 and Q2 are related to the sense of body ownership, Q3 and Q4 are related to the sense of agency, and Q5 and Q6 are related to the sense of self-location. Q7 is related to the perception of the avatar appearance, Q8 and Q9 are control questions, and Q10 is related to the willingness of the participants to avoid obstacles. The detailed contents of the questions are presented in Fig. 2. (b) Gait trajectory results when evaluating SoE with angle change of foot trajectory. If the SoE is elicited when a virtual obstacle appears in front of the avatar, as shown in Fig. 2, the participant responses to avoid collision with the obstacle are considered as an objective evaluation. In concrete, the trajectories of five strides before and after the appearance of the obstacle are presented using gait trajectories in the horizontal plane. In the center subfigure, a sample of a participant’s gait trajectory in the “sync & self” condition from a horizontal view, which shows a greater tendency to avoid obstacles, is shown. In contrast, the right subfigure presents a sample of the same participant’s gait trajectory in the “async & self” condition from a horizontal view, which indicates that the walking progressed in a straight line, meaning that the virtual obstacle was not avoided. The left subfigure shows the result of a statistical test based on repeated measures ANOVA. “ + ”: p < 0.1 indicates a trend towards significance between conditions in the repeated measures ANOVA.

Table 1 ANOVA results for Q1–Q10.

Number	Evaluation	Condition			ANOVA			
			Self	Other	{Sync, Asyn}	{Self, Other}	{Sync, Asyn}

 × {Self, Other}

	
Q1	Ownership	Sync	2.1 ± 0.7	− 1.4 ± 1.4	F (1, 8) = 63.21,	F (1, 8) = 43.72,	F (1, 8) = 11.71,	
		Asyn	− 0.2 ± 1.1	− 2.3 ± 0.9	p < 0.001 ***	p = 0.0001 ***	p = 0.0076 **	
Q2		Sync	2.1 ± 0.9	− 1.0 ± 1.3	F (1, 8) = 33.90,	F (1, 8) = 33.22,	F (1, 8) = 0.78,	
		Asyn	0.4 ± 1.5	− 2.2 ± 1.1	p = 0.0003 ***	p = 0.0002 ***	p = 0.3994 ns	
Q3	Agency	Sync	2.0 ± 0.8	0.9 ± 1.0	F (1, 8) = 33.83,	F (1, 8) = 21.41,	F (1, 8) = 0.03,	
		Asyn	− 1.0 ± 1.3	− 2.0 ± 1.0	p = 0.0003 ***	p = 0.0012 **	p = 0.8576 ns	
Q4		Sync	2.2 ± 0.7	1.3 ± 1.2	F (1, 8) = 35.63,	F (1, 8) = 13.96,	F (1, 8) = 0.56,	
		Asyn	− 1.2 ± 1.6	− 1.8 ± 1.2	p = 0.0002 ***	p = 0.0047 **	p = 0.4751 ns	
Q5	Self-location	Sync	0.9 ± 1.5	− 1.2 ± 1.3	F (1, 8) = 9.03,	F (1, 8) = 40.18,	F (1, 8) = 0.82,	
		Asyn	− 0.2 ± 1.2	− 2.2 ± 1.0	p = 0.0148 *	p = 0.0001 ***	p = 0.8166 ns	
Q6		Sync	1.8 ± 1.2	0.3 ± 1.5	F (1, 8) = 18.24,	F (1, 8) = 23.01,	F (1, 8) = 0.07,	
		Asyn	− 0.6 ± 1.4	− 2.0 ± 1.1	p = 0.0021 **	p = 0.0010 ***	p = 0.7941 ns	
Q7	Avatar appearance	Sync	2.6 ± 0.4	− 2.1 ± 1.2	F (1, 8) = 10.95,	F (1, 8) = 77.62,	F (1, 8) = 2.92,	
		Asyn	1.9 ± 0.9	− 2.3 ± 1.1	p = 0.0091 **	p < 0.001 ***	p = 0.1216 ns	
Q8	Control	Sync	− 0.6 ± 1.8	− 1.5 ± 1.3	F (1, 8) = 3.49,	F (1, 8) = 14.55,	F (1, 8) = 0.00,	
		Asyn	− 1.4 ± 1.0	− 2.3 ± 0.8	p = 0.0944 + 	p = 0.0041 **	p = 1.0000 ns	
Q9		Sync	0.9 ± 1.2	− 1.4 ± 1.4	F (1, 8) = 13.53,	F (1, 8) = 32.61,	F (1, 8) = 1.28,	
		Asyn	− 0.5 ± 1.4	− 2.3 ± 1.0	p = 0.0051 **	p = 0.0003 ***	p = 0.2876 ns	
Q10	Avoidance	Sync	1.2 ± 0.8	− 0.2 ± 1.1	F (1, 8) = 8.81,	F (1, 8) = 13.97,	F (1, 8) = 2.52,	
		Asyn	− 0.2 ± 1.2	− 0.9 ± 1.3	p = 0.0157 *	p = 0.0046 **	p = 0.1467 ns	
(***: p < 0.001, **: p < 0.01, *: p < 0.05, + : p < 0.1, ns: not significant).

Gait trajectory results

The degree to which the SoE occurred was also evaluated using the angle change of the gait trajectory. If the participant took avoidant action when the avatar displayed in front of the participant collided with a virtual obstacle, and an angle change in the gait trajectory was observed, it could be interpreted that the SoE was elicited and enhanced to the avatar. The gait trajectories of the participants were recorded and calculated using the gait analysis system WM GAIT CHECKER (WALK-MATE LAB). The trajectories of five steps ahead and after the appearance of the obstacle are presented as follows. In Fig. 3b, center subfigure, a sample of a participant who was more willing to avoid obstacles is shown, whereas in Fig. 3b, right subfigure, a sample of a participant who maintained normal walking is shown. The degree of SoE could be evaluated by the orbital angle changing significantly to avoid a collision in response to the obstacle. Figure 3b, left subfigure, shows the result of a statistical test based on repeated ANOVA. Table 2 shows details of ANOVA results for angular change in gait trajectory. Surprisingly, as a main effect, the angular change was significantly larger in the synchronous condition than in the asynchronous condition. This suggests that the participants took action to avoid the virtual obstacle immediately before the avatar displayed in front of them collided with the virtual obstacle as a threat stimulus.Table 2 ANOVA results for angular change in gait trajectory (***: p < 0.001, **: p < 0.01, *: p < 0.05, + : p < 0.1, ns: not significant).

Parameter	Condition			ANOVA			
		Self	Other	{Sync, Asyn}	{Self, Other}	{Sync, Asyn} × {Self, Other}	
Angular change	Sync	0.136 ± 0.091	0.083 ± 0.019	F (1, 8) = 4.32,	F (1, 8) = 3.15,	F (1, 8) = 2.68,	
Asyn	0.083 ± 0.024	0.080 ± 0.021	p = 0. 0674 + 	p = 0. 1098 ns	p = 0.1359 ns	

Discussion

The experiment was conducted with the walking avatar system under two conditions: avatar gait synchronization (synchronous and asynchronous) and avatar appearance (self-avatar and other-avatar). Questionnaires were used as subjective metrics, whereas gait trajectories were recorded as objective metrics for evaluation.

The findings showed that the questionnaire results revealed significantly higher scores for Q1–Q6 in the synchronous condition than in the asynchronous condition. The scores were positive for most questions, indicating that the sense of ownership, sense of agency, and sense of self-location were elicited. In addition, the self-avatar condition scored higher than the other-avatar condition in terms of the visual characteristics of the avatar. Moreover, if the SoE was elicited when a virtual obstacle appeared in front of the avatar, we considered the participant responses to avoid collision with the obstacle as an objective evaluation. The gait trajectory results indicated the tendency of participants to take avoidant action when the avatar displayed in front of them collided with the virtual obstacle as the threat stimulus.

These results suggested that synchronous movement between the participant and virtual avatar with the self-appearance of the participant could result in the SoE being induced into the virtual avatar under the situation of absolute position change of the participant’s own body by walking. These results are consistent with our expectations. In a previous study15, the SoE was elicited during synchronous walking-in-place, with no changes in the absolute position of the participant’ own body. However, the possibility of the induction of SoE when the absolute body position changes in space (e.g., during walking) remains unknown. This study indicated SoE in the synchronous condition with the self-avatar, although the absolute position of the participant’s own body changed while walking. Thus, synchronous external visual feedback is essential for constructing the SoE, particularly the sense of agency. Moreover, for most situations, the appearance of the avatar contributed to the SoE, particularly the sense of body ownership. To the best of our knowledge, these results have been obtained for first time.

The higher and positive scores in the synchronous condition, similar to the previous research15, may be explained by the synchronous condition that potentially activated and enhanced the internal model of recognizing the difference between the motor intention of the participant and external stimuli. According to previous research29,30, the brain generates an efference copy that predicts the incoming sensory feedback when attempting to execute a certain body motion. If the efference copy matches the actual feedback, a higher sense of agency should be elicited. The prediction error is defined as the difference between the predicted and actual feedback. However, the walking process is highly automatic and unconscious, which means that participants rarely pay attention to it. If participants do not feel a higher SoE in the synchronous rhythm, the potential cognition of prediction errors may not be constructed, or may be constructed obscurely in their brains. In this study, the synchronous condition may have helped to emphasize the existence of prediction errors. In the synchronous condition, the participants could see an avatar moving identically to themselves. During the real walking, the participants were more aware of the difference between the actual walking feedback and their walking intentions. They were more likely to feel harmonious walking feedback, thereby experiencing a higher SoE. In contrast, in the asynchronous condition, the participants saw the avatar moving without being controlled. A higher prediction error could be correctly generated and perceived, thereby resulting in a lower SoE.

Considering the experimental results in more detail, although most questions relating to the influence of the avatar appearance showed no interaction between the two conditions, Q1, which was related to the sense of ownership, revealed interaction effects. The effect of the synchronization conditions was generally amplified under the self-avatar condition. The synchronous condition had a much higher score than the asynchronous condition. However, the difference between the synchronous and asynchronous conditions was less significant for the other-avatar condition. This indicates that a more similar avatar appearance tended to promote the influence of the higher synchronization condition. A possible reason is that, as the participants talked after the experiments, they perceived greater differences between the two synchronization conditions if the avatar was similar to themselves, because they cared more about their own behavior and the results. For the other-avatar condition, despite the differences, they preferred to consider the avatar as “another walking person” who was not associated with them. Therefore, their questionnaire scores tended to show smaller differences.

However, Q1, which was related to the sense of ownership, and Q6, which was related to the sense of self-location, showed negative scores, except for the synchronous self-avatar condition. Two reasons can be considered in analyzing this phenomenon. The first is the perspective. In previous studies25,31, attempts were made to determine the influence of the point of view when visualizing the avatar in VR. The results suggested a much higher SoE, especially for the sense of ownership and sense of self-location, from the first-person view. This is because observing one’s body from an exterior view contradicts the fact that the eyes are on the face and one cannot see the body from a third-person view from a human anatomy perspective. In contrast, the other-avatar condition aids the natural perception process of observing another person walking in front of oneself, particularly in a real-world environment (MR). This research was conducted in MR from a third-person perspective; therefore, it is understandable that participants had a lower evaluation of the sense of ownership and sense of self-location. The second reason is the platform that was used in the experiments. Many previous studies have focused on VR rather than MR. VR generates and renders completely immersive environments that can easily be artificially manipulated. This implies that the virtual environment and sensory (visual and auditory) feedback are consistent and well combined. In a virtual environment, the visualization of the avatar is harmonious with the virtual environment, and users are less likely to distinguish or state discordance with the avatar. In contrast, in MR, the avatar is overlaid on the real world and is essentially an extension thereof. Thus, the avatar is similar to an auxiliary layer, but not the center of attention. The sensation of the external environment cannot be easily manipulated by the additional layer. Therefore, it is significantly easier for participants to distinguish their own body from the virtual body in MR than in VR.

In the supplementary results, the value of Q7 in the self-avatar condition was expected to exceed that in the other-avatar condition. The scores for Q7, which investigated whether the visual characteristics of the avatars were similar to those of the participants, were all positive and negative under the self- and other-avatar conditions, respectively.

Further, Q8 and Q9 were expected to be negative regardless of the experimental conditions and illusion, with no significant difference. As expected, under the synchronization condition (Q8 and Q9), the Q8 results were all negative. However, the mean score of the “self” condition in Q9 was slightly higher than zero. Although no significant differences were expected, Q9 exhibited significant effects in case of the synchronization and avatar appearance. In fact, positive scores were obtained in the synchronous and self-avatar conditions. Notable, this does not indicate that the participants could not distinguish their bodies from the virtual body; however, it may suggest that when participants perceived the avatar from a third-person perspective, a more similar appearance with the same motions was likely to be considered as another self; that is, similar to glancing into a mirror. A previous study29 suggested that the third-person perspective yielded higher scores than the first-person perspective when participants were asked whether two bodies could be perceived. Owing to the contradictory visualization of an avatar, participants may consider the avatar to be a mirrored self; thus, upon the induction of the SoE, the body may appear at two places simultaneously.

Finally, Q10 was expected to be higher under the synchronous condition than that under the asynchronous condition. As an experimental result, whether the participants wished to avoid imaginary obstacles was investigated in Q10. The “synchronous” and “self” conditions yielded positive values. Q10 was related to the subjective willingness of the participants to avoid collisions; whereas, the synchronous condition exhibited a significant difference. This result matched the objective evaluation of changes in the gait trajectory.

In terms of the application of findings in this research, the following viewpoints are important. The SoE for avatars as virtual bodies allows individuals to experience physical sensations for an avatar as if they were for their own real bodies. Feedback from avatars has traditionally been limited to audio-visual stimuli. However, by applying the SoE, the feedback may also include physical sensations, thereby expanding the modalities of such feedback. Using this enhanced feedback, where the avatar extends the human’s own physical senses, may aid in precisely modifying human behavior and controlling movement. Accurate feedback via avatars in VR, AR, and MR environments has the potential to be applied to training for improving motor skills and rehabilitating various movements, including walking. It is anticipated that SoE knowledge will further enhance cyber-physical systems, thereby enabling the transformation of walking movements and another movement, also through MR environments.

The limitations of this study and future challenges are as follows.

In this study, the two systems were used for synchronization between the experimental participant and the virtual avatar. The first system in the adaption practice phase was based on a six-piece IMU sensor system on their bodies, which output the movement information of the participants’ whole-body skeleton. The second system in the walking phase was based on the head mounted IMU and the biped virtual avatar WALK-MATE AVATAR, which could walk with the user under gait movement synchronization using interpersonal interactive gait rhythm entrainment3,16,17. In our pre-experiments with verification results of the experimental systems, this system could accurately measure the whole-body movement within a small range of approximately a few meters. However, we confirmed that in situation involving walking more than tens of meters, the body movement could not be accurately measured owing to factors such as drift in the IMU sensor data. This was considered to be the limit of this measurement system. Therefore, in the walking phase, we used a system that realized synchronization of walking rhythm during walking. At the very least, this study suggested that synchronization of walking movements between the experimental participant and the virtual avatar affected the induction of SoE. However, a new breakthrough is expected to be discovered in the future regarding the manner in which more detailed movements of each body segment affect each other.

In addition, owing to the use of the six-piece IMU sensor system, this study conducted an experiment involving long-distance walking, and the participants’ whole-body movements were not measured. However, for a comprehensive investigation, in addition, to embodiment, the movement of participants when they observe a self-avatar in MR environment must be investigated. Moreover, clarifying the phenomena that can be interpreted from the participants’ whole-body movements is an important challenge for future research.

This study involved 10 participants, and data were collected to investigate the induction of SoE for a virtual avatar during walking. By further increasing the sample size, the phenomenon addressed in this study is expected to be further clarified and a more detailed analysis could be facilitated. This aspect should be considered in future research.

Conclusion

This study investigated whether synchronous movement between a human and a virtual avatar could elicit the SoE compared to asynchronous movement of the avatar while the body position of the participant changed during walking. We built a system wherein the avatar could walk with the experimental participant. The experiment was conducted under two conditions: avatar gait synchronization (synchronous and asynchronous) and avatar appearance (self-avatar and other-avatar). Questionnaires were used as subjective metrics and gait trajectories were recorded as objective metrics for evaluation. The questionnaire results indicated that the scores of the SoE in the synchronous condition were significantly higher than those in the asynchronous condition. In addition, the scores of the SoE in the self-avatar condition were significantly higher than those in the other-avatar condition. These results suggest that when the participant walked with the walking avatar, the SoE was elicited to the avatar while the body position of the participant changed during walking. In the future, it is expected that the SoE knowledge of this study will be used in the research and development of MR technology in situations that involve substantial movement with absolute position changes in the real world, and that effective human–computer interaction systems will be created on this basis.

Supplementary Information

Supplementary Figure S1.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-72095-7.

Acknowledgements

This work was supported in part by the Japan Science and Technology Agency (JST) CREST, Grant Number JPMJCR21C5; JST COI-NEXT, Grant Number JPMJPF2101; and the Japan Society for the Promotion of Science (JSPS) KAKENHI, Grant Number 22K17630.

Author contributions

GT, HU, RI, and YM contributed to creating the hypothesis. GT, RI, and HU contributed to and designed the study, developed and implemented the system, conducted the evaluation experiments, discussed and interpreted the results, and drafted the manuscript. GT, HU, RI, and YM reviewed the manuscript.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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