Hakamata et al.
Journal of Physiological Anthropology(2022) 41:41
https://doi.org/10.1186/s40101-022-00315-y

Open Access

ORIGINAL ARTICLE

Haptic feedback intervention decreases
the spatial margin when older adults walkthrough a narrow space
T. Hakamata1,2, D. Muroi3, K. Kodama4, Y. Kondo5 and T. Higuchi1*   

Abstract
Background: The ability to avoid obstacles efficiently and safely is important for older adults to prevent injuries fromtripping and falling. It is important to find an optimal spatial margin between the body and an obstacle considering both safety and efficiency. One side of finding the optimal margin is to decrease the margin in terms of motor
efficiency. In this study, we tested whether fingertip-contact intervention to obtain haptic feedback information toperceive the relationship between body and the environment could immediately improve spatial perception and collision avoidance behavior (an instantaneous effect).
Methods: Twenty-seven older adults (12 males and 15 females) participated in the experiment. In the interventionof the fingertip-contact group, they lightly touched the edge of a door with both fingertips while walking. The test
task before and after the intervention involved grasping a horizontal bar and passing through a narrow opening. As
dependent variables, we measured the spatial margin and the collision rate.
Results: The fingertip-contact group showed a significant decrease in the spatial margin after the intervention. On
the other hand, there was no significant improvement in the collision rate after the intervention but rather a decrease
only in the control group.
Conclusion: The results obtained in this study indicate that touching obstacles with the fingertips had an instantaneous effect, leading to efficient movement learning, although a possible side effect of an increased collision rated
was also found. The proposed intervention might promote an efficiency-based strategy due to learning the spatial
relationship between the body and the environment, and it may suppress the excessive avoidance of older adults.
Keywords: Obstacle avoidance, Aperture passing, Haptic feedback, Fingertip contact, Error learning
Background
The modification of gait patterns in response to environmental constraints is referred to as adaptive locomotor
adjustment [1, 2]. Due to aging-related changes in physical and perceptual/cognitive functions, the characteristics of adaptive locomotor adjustments in older adults*Correspondence: higuchit@tmu.ac.jp
1
Department of Health Promotion Science, Tokyo Metropolitan University,
Tokyo, Japan
Full list of author information is available at the end of the article

are likely to be different from those in younger adults.
This could lead to collision with an obstacle with insufficient and delayed modification [3–5] or destabilization
as a result of avoiding the obstacle in an excessive manner [6, 7]. Finding a way to improve collision-avoidance
behavior provides the requisite information for predicting
collision-induced falls and injuries in older adults. Several
studies have reported that repeated collision-avoidanceexperiences in a real environment [8] or virtual environment [9–11] improved participants’ obstacle-avoidance
behavior [9, 10] or general mobility/stability [8, 11, 12].
Repeated experiences also improved their perceptual© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother 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 thislicence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​
mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Hakamata et al. Journal of Physiological Anthropology(2022) 41:41

Page 2 of 9

judgment regarding the passability of a narrow doorway[13], which could lead to safe navigation without collision.
These studies suggest that obstacle-avoidance behavior
improves with “learning by doing” [13].
Improvement of obstacle-avoidance behavior can beassessed from the viewpoints of two different strategies. The first strategy focuses on increasing the size ofthe spatial margin people keep between the obstacle andtheir body: a safety-based strategy. This strategy enables
people to decrease their collision risk because they cankeep a large spatial margin. The safety-based strategy,
however, can lead to balance instability because people
must change their posture dynamically during locomotion to keep too much margin [7]. For example, in theaperture-passing task, they must rotate their body if theykeep the margin large. Rotating too much can cause balance instability and increase the fall risk.
A second strategy focuses on keeping the optimal spatial margin—an efficiency-based strategy. This strategy
enables people to decrease their fall risk due to the abovementioned balance instability and to increase energy
efficiency because they do not need to move largely.
The efficiency-based strategy, however, can lead to anincreased collision risk because people must be close
to the obstacle when passing the aperture to keep the
margin small. Thus, it is important to find and keep an
optimal margin considering both safety and efficiency in
obstacle-avoidance tasks. Finding such an optimal spatial
margin is not simple, considering that the optimal relationship between the body and the environment shouldchange depending on constraints of the performer, theenvironment, and the task [14, 15].
The intervention for the efficiency-based strategy,
which enables participants to keep an optimal spatial
margin, remains unknown. Considering that the safetybased strategy can lead to balance instability [7], it isworth seeking an intervention method to improve obstacle-avoidance efficiency. To do so, we assumed that actually touching the obstacle can increase the perception of
the spatial relationship between the body and the environment. The theoretical backgrounds upon which we
decided to test the effect of actually touching the obstacle
are as follows. There are two approaches to motor learning—reductive and emergent views [16]. The reductive
approach focuses on body functions and reduces them torepresentations and computations in the internal model[16–18]. From this view, fingertip-contact intervention
is reasonable since the input of error signals (i.e., haptic
information when touching the obstacle) is essential forlearning and selecting modules in motor learning theory
based on an internal model. On the other hand, the emergent approach focuses on task- or goal-specific organization or the emergence of an action system through aperception–action cycle within the environment [15, 16].
Behavior in the system is flexibly organized dependingon the task or goal through interaction among the body,brain, and environment. Such fine-tuning of the task
is called calibration [16, 19]. From the emergent view,
fingertip-contact intervention is supposed to promote a
perception–action cycle for learning the body–environment relationship and calibrating the system.
Based on these theoretical backgrounds, we hypothesized that the actual touching of the obstacle can increase
perception of the spatial relationship between the bodyand the environment; as a result, the margin decreases,
and the participant can acquire an efficiency-based strategy. To examine this hypothesis, we selected a walkingthrough-an-aperture task in accordance with previous
studies [13, 20, 21]. We required participants to hold ahorizontal bar [22, 23] in order to make the task relatively
difficult, since it was hard for participants to improvetheir performance if the task was too simple.

Materials and methods
Participants

Twenty-seven older individuals (12 males and 15 females,mean age = 73.8 years, SD = 4.8 years) participated in theexperiment. All participants had normal or corrected-tonormal vision. Their mean standing height was 159.6 cm(SD = 9.4 cm), and their mean body width at the shoulders, defined as the distance between the heads of theright and left humeri, was 40.3 cm (SD = 3.8 cm). Testing
was approved by the Ethics Committee of Tokyo Metropolitan University, Japan (H29-8). Written informed
consent was obtained from all participants in accordance with the Ethics Committee of Tokyo Metropolitan
University and the Declaration of Helsinki. Participantsreceived a bookstore gift card prior to participating in theexperiment.
Apparatus

The experiment was conducted in a room measuring
6.7 m × 4.9 m. The experiment was performed along a
straight 5.5-m path. A custom-made, moving-door apparatus (Uchida Electronics Co., Ltd., Japan) was used topresent an aperture. The apparatus consisted of an aluminum frame (2.4 m wide and 2.3 m tall) and two boards(0.6 m wide and 1.75 m tall). An aperture was createdas the space between the two boards. Participants wereto touch locations indicated by red sticky notes (2.5 cm
wide and 7.5 cm tall) attached to the doors on both sides.
The height of the note placement was set for each participant so that their upper limbs were naturally abductedwhen touching the notes.
In pre- and posttests, participants walked while holding a horizontal bar (1.5 cm in diameter). Holding a

Hakamata et al. Journal of Physiological Anthropology(2022) 41:41

Page 3 of 9

bar creates a task that requires more detailed perceptual readjustment. The bar was twice the participant’s
shoulder width (distance between two acromia). Twelve
three-dimensional motion-analysis cameras (OQUS300,
manufactured by Qualisys, Sweden) were used to analyze the walking motion. The sampling frequency ofthe motion analysis was 120 Hz. The cameras tracked
a total of 16 reflection markers. Three of these markers were attached to the frame of overhead headphones(Audio–Technica) to track the head movement (one at
the top and one at each of the bilateral heads). Sevenmarkers were attached to the participant’s body: one ateach shoulder (lateral sides of the acromia), one at theintersection of the straight line connecting the lower
shoulder blades and the spine, one on each side of theposterior superior iliac spine, and one on each index fingernail. Three markers were placed on each short board
in a noncollinear arrangement to represent the board as
a rigid body.

cognitive and mobility functions. Cognitive function
was assessed using the Mini-Mental State Examination(MMSE). The MMSE is an 11-question test that measures five areas of cognitive function, with the maximum
score being 30 [24]. A score of 23 or lower is indicativeof cognitive impairment. Mobility function was assessedwith the Timed Up and Go (TUG) test [25]. During the
TUG test, participants were instructed to stand up froma standard chair with a seat height of 40 cm, walk for 3 m
at a comfortable pace, turn, walk back to the chair, andsit down. The time required from the verbal command to
begin the task to sitting down was measured with a stopwatch. Each participant performed the TUG task twotimes around the right and two times around the left; theaverage of these four times (in seconds) was used as the
TUG score.

Tasks and procedures

The inclusion criterion was age ≥ 65 years, and participants were randomly assigned to one of two intervention
groups: fingertip contact (n = 14) or control (n = 13).
The experiment consisted of four parts (Fig. 1): (a) measurements of participants, (b) baseline measurements of
the walking-through-an-aperture task (pretest), (c) intervention, and (d) post-test measurement of the walkingthrough-an-aperture task (posttest).
Participants’ details

Participants’ height and body width at their shoulders
were measured in cm. We also measured participants’Fig. 1 Flow chart of the procedure

Pre‑ and posttests

Participants held both ends of a horizontal bar with bothindex fingers and fixed them at chest-high level (Fig. 2).
This is a posture similar to that during the fingertipcontact intervention described later. Participants thenwalked toward each aperture from a distance of 4 m andtried to cross the aperture without collision. They wereasked to do so while trying to minimize the spatial margin created between the bar and the doors. These instructions required more fine-tuning of their behavior. Threedifferent aperture widths were randomly presented: 0.9,
1.0, and 1.1 times the bar length. In total, participants
performed six main trials for each test (three aperture
widths × two trials). Three practice trials (three aperture widths × one trial) were performed prior to themain trials in the pre-test session so participants couldHakamata et al. Journal of Physiological Anthropology(2022) 41:41

Page 4 of 9

Fig. 2 Method of gripping horizontal bars in pre- and posttests

understand and familiarize themselves with the experimental procedure.
Intervention

As in the pre and posttests, participants walked andcrossed the aperture during the intervention sessions.
However, unlike the walking in the pre- and posttests,
they did not hold the horizontal bar. Participants in thefingertip-contact group initiated their walking, whileboth index fingers were held in the extended position
with the upper limbs abducted (Fig. 3a). They were asked
to walk through apertures of various widths while touching the red tape attached to each side of the door withthe tips of their index fingers. They were instructed not tostop or suddenly slow down when directly in front of theaperture in an effort to touch the tape accurately. Participants in the control group walked normally and crossed
the aperture (Fig. 3b). As with the fingertip-contact
group, they were also instructed not to stop or suddenly
slow down when directly in front of the aperture. However, they were not instructed to walk through the aperture with a minimal spatial margin. The aperture widths
were the same as those presented in the pre- and posttests (i.e., 0.9, 1.0, and 1.1 times the bar length). The postural requirement of touching the door with both hands
resulted in a wide aperture width, and the task was performed without trunk rotation. Participants performed

24 main trials (three aperture widths × eight trials).
Three practice trials (three aperture widths × one trial)
were performed prior to the main trials.
Data analyses

To test participant homogeneity between the two experimental groups, the Mann–Whitney U-test was performed to statistically compare all participant details(age, height, shoulder width, MMSE score, and TUG testscore), excluding gender. A Pearson’s chi-squared test
was conducted to identify the gender ratio.
To determine whether collision-avoidance behavior
was improved in terms of efficiency after intervention,
two dependent variables obtained from pre- and posttest
performances were compared statistically.
The first variable was the spatial margin at the timeof aperture crossing during successful trials (i.e., trials where no collision occurred). The spatial margin
was calculated as the distance between the positionof the marker on the index finger (virtual indication of
the position of the bar edge) and the inner edge of theboard. The time of aperture crossing was defined as thetime one of the two markers on the index fingers crossed
the aperture first. The values were averaged over the successful trials for each participant and statistically compared using a two-way (group × test) ANOVA withrepeated measures test.

Fig. 3 Intervention in the a fingertip-contact group and b control group in an intervention session

Hakamata et al. Journal of Physiological Anthropology(2022) 41:41

Page 5 of 9

The second variable was the collision rate. The collision rate during each test (out of a total of six trials) was
calculated for each participant. Given that the error-rate
distribution was not normal, we adjusted it using the arcsine transformation for the statistical analysis of a twoway (group × test) analysis of variance (ANOVA). All
statistical analyses were conducted using RStudio software (version 2022.02.3).
Several kinematic variables obtained during the preand posttests were also analyzed. The mean movement
speed at the time of aperture crossing during successful trials was measured, based on the reflection marker
placed at the top of the overhead headphones. Measuring the movement speed was necessary to determine
whether the improvement in efficient behavior would
be accompanied by reduced movement speed (i.e., thespeed-accuracy tradeoff ). The mean absolute angle ofhead rotation in the yaw dimension, calculated using
left and right markers on the overhead headphones,
was measured at the time of aperture crossing during

successful trials to address whether the finger-tip contact intervention would affect the head rotation behaviorof looking at either side of the space to avoid collision.
Both variables were analyzed statistically with a two-way(group × test) analysis of variance (ANOVA). Other kinematic measurements of the reflective markers placed on
the body were not used for achieving the purpose of thestudy and are not reported here.

Table 1 Participants’ details in each experimental group
Fingertipcontact group(n = 14)

Control group (n= 13)P-value

Gender (male/
female)a

7/7

5/8

0.54

Age (y)b73.6.1 ± 5.1

73.9 ± 4.7

0.79

39.9 ± 4.4

Height (cm)bShoulder width(cm)b
MMSE (points)b
TUG (s)b160.9 ± 9.2
28.3 ± 1.6
6.5 ± 0.7aPearson’s chi-square testb

Mann–Whitney U-test

158.1 ± 9.6

0.48

40.7 ± 3.2

0.58

28.3 ± 2.2

0.65

6.4 ± 1.3

Fig. 4 The mean spatial margin in each group

0.79

Results
Participants’ characteristics

Participants’ characteristics are summarized in Table 1.
No significant main effects between the two groups were
found in any of the measurements.
Spatial margin

The mean spatial margin in each experimental conditionis shown in Fig. 4. An ANOVA showed the main effect of
the test (F (1, 25) = 28.809, p < 0.001, ηp2 = 0.131). The
main effect of the group was not significant (F (1, 25) =1.197, p = 0.284, ηp2 = 0.039, ns). A significant interaction was found (F (1, 25) = 6.265, p = 0.019, ηp2 = 0.032).
In the posttest, the spatial margin for the fingertip-contact group was significantly smaller in the posttest thanin the pretest (F (1, 50) = 31.617, p < 0.001, ηp2 = 0.207).
Collision rate

The mean collision rate in each experimental condition isshown in Fig. 5. An ANOVA for the adjusted data using
the arcsine transformation showed no main effect of thetest (F (1, 25) = 0.583, p = 0.452, ηp2 = 0.007, ns). The
main effect of the group was not significant (F (1, 25) =0.260, p = 0.615, ηp2 = 0.007, ns). A significant interaction was found (F (1, 25) = 4.36, p = 0.047, ηp2 = 0.051).
In the posttest, using Holm corrections, the collision rate

Hakamata et al. Journal of Physiological Anthropology(2022) 41:41

Page 6 of 9

Fig. 5 The mean rate of collision with the door in each group

Table 2 Mean movement speed and absolute angle of headrotation in each experimental condition
Fingertip-contact
group

Control group

PretestPretestPosttest

Posttest

Movement speed(cm/s)

91.0 (19.5) 88.0 (19.6) 100.4 (22.7) 99.0 (18.7)

Head rotation angle(deg)

19.3 (9.4)

18.6 (9.6)

13.2 (7.7)

9.2 (5.2)of the control group was significantly smaller in the posttest than in pretest (F (1, 25) = 5.333, p = 0.040, ηp2 =0.111).
Kinematic measurements

The mean movement speed and the head-rotation angle
at the time of aperture crossing in each experimental
condition are shown in Table 2. For the movement speed,
neither the main effect of the test (F (1, 25) = 0.508, p= 0.482, ηp2 = 0.02, ns) nor that of the group (F (1, 25)= 2.055, p = 0.164, ηp2 = 0.076, ns) was significant. No
significant interaction was found (F (1, 25) = 0.066, p =0.799, ηp2 = 0.003, ns). For the absolute angle of headrotation for each group, the main effect of the test was
not significant (F (1, 25) = 3.118, p = 0.090, ηp2 = 0.111,
ns). The main effect of the group was significant (F (1, 25)= 7.260, p < 0.05, ηp2 = 0.225). No significant interaction
was found between the two factors (F (1, 25) = 1.758, p =0.197, ηp2 = 0.066, ns).

Discussion
Spatial margin

The fingertip-contact group showed a significant
decrease in the spatial margin in the aperture-passing

task after intervention. This result agreed with the
hypothesis. From a reductive view, the spatial relationship between the fingertip and the door was learned
based on the error input [17, 18]. It is supposed that
repeated adjustment of movements using such haptic feedback information updates the internal model tocope with the discrepancy between the target and actual
situations [26]. Notably, an analysis of movement speed
showed no significant decrease from the pre- to the posttests in the intervention group. This suggests that the
improvement in efficient behavior observed in the post
test was not simply derived from decreased movement
speed (i.e., the speed–accuracy tradeoff ). Analysis of
the head-rotation angle showed that although the main
effect of the test was significant, the head-rotation angle
remained unchanged between the pre- and posttests in
the intervention group (Table 2). The head rotation in
the yaw dimension at this moment was considered to berelated to looking at either side of the space to avoid collision. The results indicate that improvement in efficient
behavior did not result from a change in strategy of looking at the space. Rather, the improvement in the efficient
behavior may have resulted from improved perception of
the body-environment relationship based on the haptic
information.
From an emergent view, it is supposed that the task/
goal (i.e., perceptual learning of the body-environment
relationship) was achieved by the repeated perceptionaction cycle through haptic feedback, and a transfer oflearning might occur from the intervention task (i.e., fingertip-contact task) of the test task (i.e., walking throughan aperture with a minimal margin). Considering these
theoretical interpretations, the proposed intervention
might promote the perception of a spatial relationshipbetween the body and the environment and improve

Hakamata et al. Journal of Physiological Anthropology(2022) 41:41

Page 7 of 9

obstacle-avoidance behavior in terms of an efficiencybased strategy.
There was no significant difference between pre- andposttests for the control group. This suggests that intervention without any haptic feedback cannot decreasea participant’s spatial margin when passing the narrow
aperture. Such intervention might not improve obstacle
avoidance in terms of an efficiency-based strategy.
These results indicated that the proposed intervention(i.e., fingertip contact) can decrease the spatial margin
between the body and the environment by learning basedon perceptual feedback using haptic information and can
improve obstacle-avoidance behavior in terms of motor
efficiency. We speculate that such intervention can suppress the excessive avoidance behavior that leads to thebalance instability often observed in older adults [6, 7].

this case, participants penetrated and touched the door
without rotating their body (Fig. 3). As a result, the test
and intervention tasks have different task demands andbehavioral patterns. The differences in these two tasks
might cause the difficulty in decreasing the collision ratein the fingertip-contact group.
On the other hand, for the control group, participants
were required to avoid contact with the door in boththe test and intervention tasks. Furthermore, they could
learn repeatedly the spatial relationship between theirbody and the door visually. The similarity in these task
demands and repeated visual leaning might cause learning and improvement in passing the door without collision and decreasing the collision rate.
The present results suggest that the proposed intervention method of fingertip contact possibly improves theefficiency-based strategy in terms of reducing the spatial
margin and keeping a minimal margin. According to thetrade-off relationship between safety and efficiency [27],the collision rate or risk might not always decrease. However, it is important to keep an optimal margin considering both safety and efficiency in obstacle-avoidance tasks.
According to previous studies, the excessive avoidance
behavior involved in the safety-based strategy can lead tothe destabilization of balance during obstacle avoidancein older people [6, 7]. Thus, not only the safety-based
strategy but also the efficiency-based strategy is important for finding the optimal spatial relationship between
the body and the environment. To do so, the proposedintervention of touching the environment might be useful and meaningful for learning the body-environment
relationship. Moreover, learning the optimal body-environment relationship should lead to decreased collisionrisk and the prevention of falls in older people. Furthermore, there is potential for new interventions incorporating tactile feedback not only in aperture passage but
also in training for the avoidance of various obstacles. For
example, a target object could be placed above the step
(typical foot-lift height) during obstacle avoidance, andtouching it would provide feedback regarding the heightof the foot lift.
This study has several limitations. First, the long-term
learning or retention effect of the proposed intervention
should be examined in a future study. Second, it should
be investigated whether the excessive avoidance behaviors of older adults can be suppressed by the proposedintervention in terms of efficiency-based strategy. Third,
the present study found that participants transferred the
behavior learned with the fingertip-contact intervention
to walking while holding the horizontal bar. The manipulation of holding the bar was necessary to increase taskdifficulty during pre- and post-test measurements. However, it limited the natural arm swing during walking.

Collision rate

For the fingertip-contact group, there was no significant
improvement in the collision rate. These results indicate that touching the obstacle with the fingertips, while
reducing the spatial margin to the door, does not necessarily contribute to decreasing collision rates. Three reasons are considered as to why the collision rate did notchange after the fingertip-contact intervention. First, as
mentioned in the introduction, an efficiency-based strategy can lead to an increased collision risk because participants get close to the obstacle when passing the aperture
to keep the margin small. As a result, considering thetrade-off relationship between safety and efficiency [27],the collision rate did not decrease, while the spatial margin was reduced in the fingertip-contact group.
Second, participants may have been able to recognize
from the haptic information of their fingertips that therisk of collision with the door was low by lightly touching the door. A previous study showed that haptic/tactile
information from the fingertips is important for perceiving the material of an object [28]. The door used in thisstudy was equipped with a shock-reducing mechanism,
so the risk of injury was extremely low even if participants collided with the door. As a result of perceiving thematerial of the door from the haptic information of thefingertips, it can be inferred that participants were lessafraid of colliding with the door.
Third, there were differences between the test andintervention tasks. The test task required participants
to avoid contact with the door. In this case, it is known
that participants tend to rotate their body several meters
before reaching the door to avoid collision [20, 29]. Thus,
participants penetrated and passed the door from either
the left or right side of the body by rotating the body(Fig. 2). Contrarily, the intervention task of the fingertipcontact group required participants to touch the door. In

Hakamata et al. Journal of Physiological Anthropology(2022) 41:41

Page 8 of 9

Therefore, it was not certain whether the learned behavior would also be transferred to normal walking. Finally,
how this intervention can lead to preventing falls in older
adults should be also surveyed in the future.

4

Conclusion
The present study revealed that the spatial margin between
the body and an obstacle when walking through a narrow
aperture immediately decreased after fingertip-contact
intervention in healthy older adults, although a possible side effect of increased collision rates was also found.
This result suggests that fingertip-contact intervention can
improve obstacle-avoidance behavior with a minimal margin (i.e., efficiency-based strategy). Although some older
adults tend to show excessive obstacle-avoidance behavior
by keeping a larger spatial margin, which can cause balance instability, the proposed intervention might promote
an efficiency-based strategy due to learning the optimal
spatial relationship between the body and the environment
and, thus, suppress excessive avoidance. Further investigation is needed to reveal whether such a proposed intervention can prevent falls by older adults in the future.

References
1. Higuchi T. Visuomotor control of human adaptive locomotion: understanding the anticipatory nature. Front Psychol. 2013;4:277. https://​doi.​
org/​10.​3389/​fpsyg.​2013.​00277.
2. McFadyen BJ, Fiset F, Charette C. Substituting anticipatory locomotor
adjustments online is time constrained. Exp Brain Res. 2018;236(7):1985–
96. https://​doi.​org/​10.​1007/​s00221-​018-​5277-4.
3. Menant JC, St George RJ, Fitzpatrick RC, Lord SR. Impaired depth perception and restricted pitch head movement increase obstacle contacts
when dual-tasking in older people. J Gerontol A Biol Sci Med Sci.
2010;65(7):751–7. https://​doi.​org/​10.​1093/​gerona/​glq015.
4. Persad CC, Giordani B, Chen HC, Ashton-Miller JA, Alexander NB, Wilson
CS, et al. Neuropsychological predictors of complex obstacle avoidancein healthy older adults. J Gerontol B Psychol Sci Soc Sci. 1995;50(5):272–7.
https://​doi.​org/​10.​1093/​geronb/​50B.5.​P272.
5. Weerdesteyn V, Nienhuis B, Geurts AC, Duysens J. Age-related deficits inearly response characteristics of obstacle avoidance under time pressure.
J Gerontol A Biol Sci Med Sci. 2007;62(9):1042–7. https://​doi.​org/​10.​1093/​
gerona/​62.9.​1042.
6. Muir BC, Haddad JM, Heijnen MJ, Rietdyk S. Proactive gait strategies to mitigate risk of obstacle contact are more prevalent with advancing age. Gait
Posture. 2015;41(1):233–9. https://​doi.​org/​10.​1016/j.​gaitp​ost.​2014.​10.​005.
7. Yamagata M, Tateuchi H, Pataky T, Shimizu I, Ichihashi N. Relation
between frontal plane center of mass position stability and foot elevation
during obstacle crossing. J Biomech. 2021;116:110219. https://​doi.​org/​10.​1016/j.​jbiom​ech.​2020.​110219.
8. Jeong YG, Koo JW. The effects of treadmill walking combined withobstacle-crossing on walking ability in ambulatory patients after stroke: apilot randomized controlled trial. Top Stroke Rehabil. 2016;23(6):406–12.
https://​doi.​org/​10.​1080/​10749​357.​2016.​11685​92.
9. Kim A, Schweighofer N, Finley JM. Locomotor skill acquisition in virtual
reality shows sustained transfer to the real world. J Neuroeng Rehabil.
2019;16(1):113. https://​doi.​org/​10.​1186/​s12984-​019-​0584-y.
10. Kondo Y, Fukuhara K, Suda Y, Higuchi T. Training older adults with virtual
reality use to improve collision-avoidance behavior when walking
through an aperture. Arch Gerontol Geriatr. 2021;92:104265. https://​doi.​
org/​10.​1016/j.​archg​er.​2020.​104265.
11. Yang YR, Tsai MP, Chuang TY, Sung WH, Wang RY. Virtual reality-based
training improves community ambulation in individuals with stroke: arandomized controlled trial. Gait Posture. 2008;28(2):201–6. https://​doi.​
org/​10.​1016/j.​gaitp​ost.​2007.​11.​007.
12. Muroi D, Ohtera S, Kataoka Y, Banno M, Tsujimoto Y, Tsujimoto H, et al.
Obstacle avoidance training for individuals with stroke: a systematic
review and meta-analysis. BMJ Open. 2019;9(12):e028873. https://​doi.​org/​
10.​1136/​bmjop​en-​2018-​028873.
13. Franchak JM, van der Zalm DJ, Adolph KE. Learning by doing: action performance facilitates affordance perception. Vision Res. 2010;50(24):2758–
65. https://​doi.​org/​10.​1016/j.​visres.​2010.​09.​019.
14. Newell K. Constraints on the development of coordination. In: Motor development in children. Aspects of coordination and control; 1986. p. 341–60.
15. Davids K, Glazier P, Araújo D, Bartlett R. Movement systems as dynamicalsystems. Sports Med. 2003;33(4):245–60. https://​doi.​org/​10.​2165/​00007​
256-​20033​3040-​00001.
16. van Dijk L, van der Sluis C, Bongers RM. Reductive and emergent views on
motor learning in rehabilitation practice. J Motor Behav. 2017;49(3):244–
54. https://​doi.​org/​10.​1080/​00222​895.​2016.​11914​18.
17. Kawato M, Gomi H. A computational model of four regions of the cerebellum based on feedback-error learning. Biol Cybern. 1992;68:95–103.
https://​doi.​org/​10.​1007/​bf002​01431.
18. Wolpert DM, Ghahramani Z, Flanagan JR. Perspectives and problems inmotor learning. Trends Cogn Sci. 2001;5(11):487–94. https://​doi.​org/​10.​1016/​s1364-​6613(00)​01773-3.

Abbreviations
MMSE: Mini-Mental State Examination; TUG​: Timed Up and Go test; ANOVA:
Analysis of variance.
Acknowledgements
This study was funded by the Japan Society for the Promotion of Science(25350913).
Authors’ contributions
TH, DM, KK, and TH, conception and design of the study, acquisition of data,
analysis and interpretation of data, and drafting and revising the article. YK,
conception and design of the study. All authors critically revised the manuscript and have approved the final manuscript.
Availability of data and materials
The datasets during and/or analyzed during the current study are available
from the corresponding author upon reasonable request.

Declarations
Ethics approval and consent to participate
Testing was approved by the Ethics Committee of Tokyo Metropolitan
University, Japan (H29-8). Written informed consent was obtained from allparticipants in accordance with the Ethics Committee of Tokyo Metropolitan
University and the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Department of Health Promotion Science, Tokyo Metropolitan University,
Tokyo, Japan. 2 Department of Rehabilitation, Kasai Central Hospital, Tokyo,
Japan. 3 Chiba Prefectural University of Health Sciences, Chiba, Japan.

5

University Education Center, Tokyo Metropolitan University, Tokyo, Japan.
Tokushima Bunri University, Tokushima, Japan.

Received: 8 September 2022 Accepted: 1 December 2022

Hakamata et al. Journal of Physiological Anthropology(2022) 41:41

Page 9 of 9

19. Fajen BR. Perceiving possibilities for action: on the necessity of calibrationand perceptual learning for the visual guidance of action. Perception.
2005;34(6):717–40. https://​doi.​org/​10.​1068/​p5405.
20. Higuchi T, Cinelli ME, Greig MA, Patla AE. Locomotion through apertures
when wider space for locomotion is necessary: adaptation to artificiallyaltered bodily states. Exp Brain Res. 2006;175(1):50–9. https://​doi.​org/​10.​
1007/​s00221-​006-​0525-4.
21. Higuchi T, Hatano N, Soma K, Imanaka K. Perception of spatial requirements for wheelchair locomotion in experienced users with tetraplegia. J
Physiol Anthropol. 2009;28(1):15–21. https://​doi.​org/​10.​2114/​jpa2.​28.​15.
22. Suda Y, Fukuhara K, Sato K, Higuchi T. Improved walking through an aperture in avirtual environment transfers to a real environment: introductionof enriched feedbackand gradual increase in task difficulty. Front Sports
Act Living. 2022;4(4):844436. https://​doi.​org/​10.​3389/​fspor.​2022.​844436.
23. Muroi D, Higuchi T. Walking through an aperture with visual information
obtained at a distance. Exp Brain Res. 2017;235(1):219–30. https://​doi.​org/​
10.​1007/​s00221-​016-​4781-7.
24. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state.” A practicalmethod for grading the cognitive state of patients for the clinician. J
Psychiatr Res. 1975;12(3):189–98. https://​doi.​org/​10.​1016/​0022-​3956(75)​90026-6.
25. Podsiadlo D, Richardson S. The timed “Up & Go”: a test of basic functional
mobility for frail elderly persons. J Am Geriatr Soc. 1991;39:142–8.
https://​doi.​org/​10.​1111/j.​1532-​5415.​1991.​tb016​16.x.
26. Imamizu H, Miyauchi S, Tamada T, Sasaki Y, Takino R, Putz B, et al. Human
cerebellar activity reflecting an acquired internal model of a new tool.
Nature. 2000;403(6766):192–5. https://​doi.​org/​10.​1038/​35003​194.
27. Laureshyn A, Svensson A, Hyden C. Evaluation of traffic safety, based on
micro-level behavioural data: theoretical framework and first implementation. Accid Anal Prev. 2010;42(6):1637–46. https://​doi.​org/​10.​1016/j.​aap.​
2010.​03.​021.
28. Yoshioka T, Craig JC, Beck GC, Hsiao SS. Perceptual constancy of texture
roughness in the tactile system. J Neurosci. 2011;31(48):17603–11.
https://​doi.​org/​10.​1523/​JNEUR​OSCI.​3907-​11.​2011.
29. Higuchi T, Seya Y, Imanaka K. Rule for scaling shoulder rotation angles
while walking through apertures. PLoS One. 2012;7(10):e48123.
https://​doi.​org/​10.​1371/​journ​al.​pone.​00481​23.

Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Ready to submit your research ? Choose BMC and benefit from:• fast, convenient online submission• thorough peer review by experienced researchers in your field• rapid publication on acceptance• support for research data, including large and complex data types• gold Open Access which fosters wider collaboration and increased citations• maximum visibility for your research: over 100M website views per year
At BMC, research is always in progress.
Learn more biomedcentral.com/submissions