RESEARCH ARTICLE

Technique to reduce the minimum toe
clearance of young adults during walking tosimulate the risk of tripping of the elderly
Jessica Beltran Ullauri ID☯, Yasuhiro Akiyama ID☯*, Shogo Okamoto☯, Yoji Yamada☯
Dept. of Mechanical Systems Engineering, Mechano-Informatics and Systems, Nagoya University, Nagoya,Japan☯ These authors contributed equally to this work.
* akiyama-yasuhiro@mech.nagoya-u.ac.jp

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OPEN ACCESS
Citation: Ullauri JB, Akiyama Y, Okamoto S,
Yamada Y (2019) Technique to reduce theminimum toe clearance of young adults during
walking to simulate the risk of tripping of theelderly. PLoS ONE 14(6): e0217336. https://doi.
org/10.1371/journal.pone.0217336
Editor: Kei Masani, Toronto Rehabilitation Institute- UHN, CANADA
Received: March 13, 2018
Accepted: January 22, 2019
Published: June 12, 2019

Abstract
The elderly gait encompasses several disorders, including a lower minimum toe clearance(MTC) to the ground, which is a potential cause of tripping and falling while walking. Devices
that assist in the MTC could reduce such risks. However, the development of effective assistive methods and their evaluation in the elderly might jeopardize their safety. To address
this, young adults could take the place of the elderly. We present Muscle Activity Restriction
Taping Technique (MARTT) that was devised to simulate the healthy-elderly gait characteristics in the young adults, particularly the lower MTC, by restricting the activity of lower-limb
muscles. Two different restriction approaches, one that restricts muscles at the shank andthe other at the shank and thigh, simultaneously, were tested at different walking speeds.
Both approaches achieved a reduction in the MTC, regardless of the walking speed. The
MTC was reduced to a median value lower than 10.1 mm, which is within the range of the
MTC values reported for the elderly. The reduction of the MTC significantly increased toe
contact to the ground. With the restriction of the shank muscles, the toe-contact frequency
was more than twice as that in normal walking, and with the restriction of both the shank andthigh muscles, more than five times. In addition, MARTT reproduced the lower step length,
the lower single support phase, and the joint motion compensation characteristic of theelderly gait, in the youth.

Copyright: © 2019 Ullauri et al. This is an open
access article distributed under the terms of theCreative Commons Attribution License, which
permits unrestricted use, distribution, andreproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data arewithin the manuscript and its Supporting
Information files.
Funding: This work was supported JSPS KAKENHI[grant number 26750121] https://www.jsps.go.jp/
english/index.html.
Competing interests: The authors have declaredthat no competing interests exist.

Introduction
The elderly population in the world has considerably increased; thus, several needs must be
met to ensure a good quality of life for the elderly. In particular, reducing the risk of falling isa major priority because considerable evidence establishes that a fall is detrimental to theirhealth [1–4].
Various studies have agreed that the major causes of falls in the elderly are tripping andslipping [1, 4–6]. In a three-year study of 130 individuals, Robinovitch et al. [1] reported thatthe main cause of fall, considering every daily activity, was incorrect weight shifting, which

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Technique to simulate the gait motion of the elderly

accounted for 48% of the total falls, followed by tripping with 21%, and slipping with 3%. The
combination of the cause of fall and the activity performed immediately before falling, with thegreatest number of falls, was tripping or stumbling while walking forward, accounting for 11%
of falls.
Considering the trips while walking, Mills [5] suggested that the critical walking factor for
fall prevention is the minimum toe clearance (MTC), defined as the minimum vertical distance between the lowest point of the toes of the swinging leg and the ground surface, during
the swing phase of the gait cycle [7]. In healthy adults, at the MTC instant, the foot passes
within 10 to 20 mm over the ground, in healthy adults, and travels at its maximum horizontal
velocity, which is approximately three times the walking speed [7, 8]. Thus, failure to clear the
ground, especially at the MTC instant, would most probably result in a fall [5].
The elderly exhibit a lower MTC with higher variability than young adults [5]. Karst et al.
[9] reported an MTC of 12.9 mm in a group aged approximately 70, and Begg et al. [10]reported an MTC of 7.1 mm in a group aged approximately 72. Thus, the MTC for theelderly is likely within this range. This gait deviation in the elderly is compensated by otherjoints in the kinematic chain [5]. For instance, in a review article on the gait of the elderly,
Prince et al. [11] reported higher hip and knee range of motion (ROM), higher knee flexion
at the end of the swing phase, lower ankle ROM, and a lower ankle plantar flexion peak.
Additionally, at the MTC time, Mills et al. [12] reported a higher hip and knee flexion, andlower ankle dorsal flexion. Moreover, the gait disorders in the elderly also include a decreasein walking speed, cadence, step length, and single support phase, which are adaptations forsafer walking [11].
Evidence of impaired MTC in the elderly, and the subsequent high risk of falling, establish
the need for studying the effect of MTC on their safety while walking, to device solutions forcompensating this impairment. However, the involvement of the elderly in experimental studies on their falling risk, under several walking conditions, and the testing of assistive devices inbarrier-free environments may expose the elderly to considerable danger, against the Declaration of Helsinki.
To avoid such danger, still involving humans in the study, and test assistive devices, young
people can be utilized instead of the elderly, if the characteristics of the elderly to be studied
can be simulated in the youth. Approaches, such as the “Aging Game” [13], the study of Wood
[14] and the “Aging Suit” [15] have been introduced, which attempted to simulate the limited
joint ROM, reduced dexterity, and sensory impairments of the elderly in the youth, providing
insights on the challenges faced by the elderly. Moreover, in our previous study [16], we introduced Muscle Activity Restriction Taping Technique (MARTT), that could reduce the MTCof the youth, while keeping the natural motion patterns of the joints. However, insight on thefeasibility of reducing the ankle ROM for reproducing the MTC characteristics of the elderlyin the youth is unavailable till date.
The reproduction of the lower MTC observed in the elderly in the youth can be challenging
because the central nervous system (CNS) controls the MTC with a higher priority over theother gait parameters, for high-risk tasks such as tripping [17]. For instance, in a high-risk
trip activity, such as dual-task walking in the elderly [18] and chronic low back pain (CLBP)
patients [17], changes on the stride length and stride time, but none in the variability of MTC,
were reported, indicating that a higher priority is given to MTC control. However, in studies
about single-task walking (lower risk to fall) in the elderly, a lower MTC mean value [10, 19,20] and higher MTC variability [12, 21] have been reported. Similarly, in single-task walking
in CLBP patients, a higher variability of the MTC in normal and visual-impaired walking wasreported [22]. This suggests that in situations where the CNS does not detect a potential fallrisk, the MTC can be reduced.

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Technique to simulate the gait motion of the elderly

MARTT limits the transversal area of the leg muscle belly during contraction to reduce
ankle flexion and lower the MTC. It is important to note that MARTT implies a blood flow
reduction in the restricted muscles. Blood flow occlussion in moderation has no negative
impact in the human body, in terms of blood coagulation and endothelial function [23], andcan be advantageous in improving endurance [24] and increasing functional ability [23]. Dueto this positive effect on the body, MARTT can reduce the MTC without triggering a controlprioritization of the MTC in the CNS.
Thus, we hypothesized that by means of MARTT, the MTC of youth can be reduced to thevalues observed in the elderly. In addition, the present study aimed at determining if the spatial
temporal parameters and joint kinematics of the youth with MARTT correspond to those of
the elderly. To assess the effects of MARTT in young adults, MARTT was applied to the shankand thigh, and evaluated at two different walking speeds. By reproducing the elderly gait characteristics in the youth, especially the lower MTC, MARTT can facilitate studies on the fall riskin the elderly and can be useful for testing ankle-assistive devices when the participation of theelderly is restricted.

Methods
Subjects
Ten male subjects with an average age of 22 years participated in this study. The average andstandard deviation of their weight and height were 63.9 ± 8.9 kg and 1.72 ± 0.05 m, respectively. The dominant leg of all participants was the right.
Subjects were recruited from the student population of Nagoya University, in October
2015. As applicant screening did not reveal any gait disorders, all were selected. Each participant received detailed explanation on the study, in a verbal and written manner, and signed aconsent form.
The Institutional Review Board of Nagoya University, Japan, approved the study and registered it under approval Number, 14-4.

Apparatus
Gait measurement system. The gait motion was recorded at a frequency of 100 Hz using
a motion capture system (MAC 3D system, Motion Analysis Corporation, U.S.). A set ofreflective markers was attached to the body of the subject, as recommended by the motion
module of the software for interactive musculoskeletal modeling (SIMM, Musculographics
Inc., U.S.), used for calculating the joint angles.
Fig 1 shows that to record the toe clearance from the ground, a marker was placed rightnext to each hallux, centered at the tip of the distal phalanx. To record the heel clearances fromthe ground, a marker was placed at the back of each calcaneus. A treadmill with a 1.4 × 0.5 m2
walking surface (OMEGA3, Johnson Health Tech Co., Taiwan) was used.
A non-rhythmic noise was played from an earphone during all the trials to prevent the
subjects from getting distracted by the noise generated by the toe or heel contact (HC) to theground.
In addition, four force sensors, each embedded at the shoe tip and shoe sole, respectively, of
comfortable sport shoes, were installed for detecting the HC and toe off (TO) events of the gaitof the subjects, without altering their natural walking patterns. Flexible force-sensing resistors(FSR-400, Interlink Electronics, U.S.) were employed for this purpose.
MARTT. During muscle contraction, MARTT limits the increment of the tranversal areaof the muscle belly, which in turn limits the changes in the muscle length. Thereby, MARTT
aims to limit the joint ROM that depends on the activity of the restricted muscles, especially at

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Technique to simulate the gait motion of the elderlyFig 1. MARTT apparatus. (a) Muscles at the shank and thigh that MARTT target to restrict and (b) Position of the belts used in MARTT to restrict thetransversal area of the muscle belly during contraction.
https://doi.org/10.1371/journal.pone.0217336.g001

the MTC time. To decrease ankle flexion and reduce the MTC, MARTT was implemented torestrict the tibialis anterior and gastrocnemius muscles located at the shank. Additionally, toreinforce the reduction in the MTC with a lower hip and knee joint flexion, and avoid compensation in these joints, the activity of the rectus femoris and vastus lateralis muscles locatedat the thigh were restricted. Thus, in this study, two distinct restriction conditions were
investigated.
The range of expansion of the aforementioned muscles was restricted using two pairs of
MARTT belts composed of non-stretchable fabric to guarantee uniform and constant

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Technique to simulate the gait motion of the elderly

restriction, similar to our previous study [16]. Fig 1 shows that a pair of MARTT belts wasplaced at the end of the gastrocnemius muscle heads to restrict the shank muscles, and anotherpair was placed at the beginning of the rectus femoris muscle to restrict the thigh muscles. The
belts were equally placed on each leg.
MARTT belts incorporate force sensors for measuring the restriction force applied to themuscles to guarantee the same force magnitude on both legs, prevent asymmetric walking, andmaintain the natural gait patterns. The force was set such that it corresponds to a pressure of
approximately 180 mmHg because a pressure of 160-230 mmHg [25, 26] was suggested forsafely restricting the blood flow. We selected a pressure below 200 mmHg because in a study
on restricted leg blood flow in older adults [23], significant muscle fatigue at such pressure wasindicated.

ProtocolSix walking trials were recorded for each subject. To avoid exhaustion, the duration of eachtrial was set to 6 min. Two walking speeds (regular and slow) and two muscle restriction conditions were investigated. Four trials included a combination of walking speeds and restriction
conditions, whereas the other two trials included non-restricted walking at both walking
speeds. A speed of 1.11 m/s (4 km/h), regarded as the natural walking speed of young adults[10], was selected as the regular walking speed, and a speed of 0.97 m/s (3.5 km/h), close tothat reported in the elderly [27], was selected as the slow speed. One of the restriction conditions consisted in the application of MARTT belts at the calf only, referred to here as the Crestriction, whereas the other condition, referred to as the CT-restriction, consisted in theapplication of MARTT belts at both calf and thigh.
In the first two walking trials, the normal walking of the subject at each walking speed wasrecorded in a random order. MARTT belts then were used to implement the restriction cases(C- and CT-restriction); the implementation was randomized. For each restriction case, twowalking trials corresponding to each walking speed were recorded in a random order.
The restriction forces applied to the muscles were monitored online to ensure the same
magnitude in both legs, throughout the two trials, under the respective restriction cases andbetween cases.

Data processing
The first minute of all gait motions in each trial, which was mostly an adaptation time to theexperimental condition, was excluded from the processing. All the data were smoothed using a
6-Hz Butterworth filter. The markers-position data during each walking trial were fit to thehuman model, based on which the joint motions were calculated.
The HC and TO time were determined by detecting the increase and drop in the normal
force on the shoe sole and shoe tip, respectively. The gait cycles were determined as the period
between an HC and the next HC of the same leg, and all gait motions (clearances and joint
motions) were normalized for each gait cycle. In addition, the number of toe ground contacts
was manually quantified during the trials.
The toe and heel clearances from the ground were calculated as the vertical distances fromthe treadmill walking path to the shoe markers located immediately next to the hallux and calcaneus, respectively. From the toe clearance data, the MTC was calculated as the clearance at
the instant where the toe of the swinging leg was closest to the walking surface, during the
middle-swing phase. Moreover, because the MTC distribution was positively skewed and leptokurtic, as previously reported [10], the median and interquartile range (IQR) values were calculated, for each subject, as a measure of their MTC central tendency and variability.

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Technique to simulate the gait motion of the elderly

The statistical significance of the MTC reduction in each subject was examined by the
Mann-Whitney-Wilcoxon test. In addition, to determine the general tendency of the MTC(MTC between subjects), the MTC median value of each subject was normalized by the bodyheight, and the mean, SD, median and IQR between subjects were calculated. The statisticalsignificance of the differences of the between-subjects MTC, among conditions, was assessedusing the one-tailed paired t-test.
To determine the significance of the gait changes because of MARTT, certain gait timing
and joint motion parameters were evaluated using the one-tailed paired t-test, for each subject.
To observe the general tendency of these parameters among the subjects, the median and IQRvalues between subjects were computed, and the significance of the differences was assessed by
the Mann-Whitney-Wilcoxon test.
To visualize the general tendency of the toe clearance between the normal and restrictedwalking, the mean toe clearance pattern during the swing phase of each subject was normalized by the body height and averaged over all the subjects.

Results
Gait timing
The subjects’ walking symmetry was maintained during restricted walking (the gait percentage
from one HC to the next of the other leg was 50.0% on an average, at 3.5 and 4 km/h during
normal and restricted walking). Table 1 shows the median and IQR values for the cadence,
step length and single-support phase between subjects. The step length was normalized to thesubject height. According to Table 1, a lower walking speed corresponds to a lower cadence
and step length. No significant differences in the cadence and step length, between normal andrestricted walking, was observed. Eight subjects experienced a significantly (p < 0.05) lower
single-support phase at C-restriction, and nine at CT-restriction, for both walking speeds.

Joint motion
In order to observe the motion changes in the ankle, knee and hip joints, the average of thejoint ROM, maximum ankle plantar flexion, and knee flexion at the end of the swing phasewere calculated, for each subject. The joint ROM, during C- and CT-restriction, werenormalized to the respective ROM during normal walking. Fig 2 shows the between-subject
Table 1. Gait timing between subjects.
Parameter

Walking
Speed [km/h]

Normal walking

Cadence[steps/min]

3.5

102.7; 95.3–107.6

101.4; 97–103.4

100.4; 96.8–105.7

4108; 102–109.7

104.2; 101.9–109.3

105.5; 103.3–111.1

Step Length
[m]

3.5

0.57; 0.56–0.59

0.57; 0.55–0.6 (5�� )0.57; 0.55–0.59 (4�� )0.6; 0.59–0.62��0.6; 0.59–0.64 (5�� )��64.1; 61.8–65.2 (8�� )��

64.6; 63–66.1� (9�� )Single Support Phase[% stance]

4
3.5
4

64.2; 62–67.4
66.4; 63.9–68.1

C-restriction

CT-restriction

0.61; 0.6–0.63 (3 )�63.5; 61.6–64.7 (8 )�63.9; 62.7–67 (8 )Median; IQR among subjects. The step length was normalized to the subject’s height. The information in parentheses indicates the number of subjects that experienced
a significant reduction in the respective gait parameter.
p < 0.1, and���

p < 0.15 indicate a significant reduction as compared to normal walking.

https://doi.org/10.1371/journal.pone.0217336.t001

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Technique to simulate the gait motion of the elderlyFig 2. Joint motion between subjects. (Upper row) Joint ROM during C-restriction (C) and CT-restriction (C+T), at 3.5 km/h and 4 km/h walking
speeds, expressed as a percentage of the ROM during normal walking. (Lower row) Difference between restricted (C, C+T) and normal walking (N) in
the maximum ankle plantar flexion and knee flexion at the end of the swing phase. A negative value indicates that the respective parameter decreases
during restricted walking. ��� p < 0.01, �� p < 0.05, and � p < 0.1 indicate significant differences with normal walking. The edges of the box plotcorrespond to the 25-th and 75-th percentiles, and the single points (outliers) correspond to the respective parameter values that were distant from thegeneral tendency.
https://doi.org/10.1371/journal.pone.0217336.g002

distribution of the joint ROM during restricted walking, at walking speeds of 3.5 km/h and 4
km/h, expressed in percentage of the joint ROM during normal walking.
The ankle ROM increased significantly during C-restriction (p < 0.01), and less significantly during CT-restriction (p < 0.05). The knee ROM increased significantly during Crestriction (p < 0.05), and tended to be lower than that in normal walking during CT-restriction, but this was not significant. The hip ROM increased significantly during C-restriction(p < 0.1); during CT-restriction, it reduced, but was higher than that during normal walking(not significantly). The ankle maximum plantar flexion reduced significantly for both Crestriction (p < 0.13 at 3.5 km/h) and CT-restriction (p < 0.05). The knee flexion at the end of
the swing phase tended to be higher for both C- and CT-restrictions at 4 km/h; it was significant during CT-restriction (p < 0.05).
Considering each subject independently at both walking speeds, the following number ofsubjects exhibited the following, at C- and CT-restriction, respectively: Three and seven subjects exhibited lower ankle ROM, six and ten subjects exhibited lower knee ROM, nine andseven subjects exhibited higher hip ROM, nine and six exhibited a lower plantar flexion peak,
and ten and nine subjects exhibited higher knee flexion at the end of the swing phase.

MTC reduction
Table 2 lists the mean, SD, median and IQR of the MTC central tendency between subjects, foreach leg, during normal and restricted walking, at both walking speeds. The MTC central tendency is displayed as a percentage of the body height, and its value corresponding to the average height (1.72 m) of the subjects is listed. In agreement with the reported MTC range inyoung adults [7], the clearance during normal walking corresponded to a range of 10-20 mm.
The MTC median value in the restricted cases was within the MTC range of the elderly

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Technique to simulate the gait motion of the elderly

Table 2. MTC central tendency (median) between subjects.
Walking speed [km/h]
3.5

4

Leg

Normal walking

C-restriction

CT-restriction% o.b.h.

Average subject [mm]% o.b.h.

Average subject [mm]% o.b.h.

Average subject [mm]Left0.64±0.26(0.62; 0.5–0.86)

11.1±4.4

0.40±0.31���(0.38; 0.13–0.54)

6.9±5.4

0.47±0.41�
(0.35; 0.15–0.77)

8.2±6.9

Right

0.71±0.25(0.68; 0.52–0.88)

12.3±4.3

0.59±0.18���
(0.59; 0.51–0.74)

10.1±3.1

0.59±0.29�
(0.57; 0.35–0.76)

10.1±4.9

Left0.60±0.30(0.64; 0.34–0.86)

10.3±5.1

0.44±0.30��
(0.34; 0.22–0.56)

7.5±5.2

0.41±0.30��
(0.36; 0.15–0.69)

7.0±5.1

Right

0.65±0.18(0.63; 0.51–0.72)

11.1±3.1

0.56±0.16��
(0.58; 0.49–0.68)

9.6±2.80.47±0.17���
(0.42; 0.33–0.65)

8.0±2.9

Mean ± SD (Median; IQR) Central tendency of the subjects’ MTC expressed in percentage of the body height (% o.b.h.), and in that corresponding to the average
subject’s height, 1.72 m.
p < 0.01,

���
��
�

p < 0.05, andp < 0.1 indicate the significant differences compared to normal walking.

https://doi.org/10.1371/journal.pone.0217336.t002

reported by previous studies (e.g., 7.1 mm [10] and 12.9 mm [9]). The MTC in restricted walking was statistically proven to be lower than that in normal walking, which agrees with the relationship between the elderly and the youth [10, 12, 20].
The average pattern of the mean toe clearance of all the subjects is shown in Fig 3. The
MTC, which is the lowest point observed in the middle-swing phase, was located between 4050% of the swing phase, in agreement with the study of Mills et al. [5]. For each subject, thelocation of the MTC, during restricted walking, did not differ from that in normal walking. At

Fig 3. Average toe clearance during the swing phase. The MTC is the lowest point observed in the middle-swing
phase, and is located between 40-50% of the swing phase. The MTC in restricted walking (C- and CT-restriction cases)
is lower than that in normal walking for the right (R) and left (L) legs, at both 3.5 km/h and 4 km/h walking speeds.
https://doi.org/10.1371/journal.pone.0217336.g003

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Technique to simulate the gait motion of the elderly

Table 3. Frequency of toe contacts on the ground during middle-swing phase.
Subject

Walking Speed [km/h]

Normal walking [%]C-restriction [%]CT-restriction [%]

Left

Right

Left

Right

Left

Right

3.5

2.06

3.44

6.60

10.76

10.53

10.18

4

0.66

3.31

3.83

6.39

9.68

9.35

3.5

2.72

4.08

>90

>90

>90

>90

4

1.15

2.29

>90

>90

>90

>90

C

3.5

0

16.78

10.84

34.97

39.66

64.14

4

2.85

16.14

10.65

33.14

20.65

37.10

D

3.5

0

1.26

>90

>90

>90

>90

4

0

2.24

>90

>90

>90

>90

3.5

1.92

9.29

>90

>90

>90

>90

4

1.87

6.85

>90

>90

>90

>90

3.5

0

1.20

0.86

3.45

0.77

6.51

4

0

0

0

0.63

18.93

11.24

A
B

E
F
G
H
I
J

3.5

1.04

6.92

1.69

1.69

8.06

9.52

4

2.32

2.98

4.89

4.23

>90

>90

3.5

0.76

1.90

1.10

5.86

3.70

5.56

4

0

0.66

0.95

7.94

6.51

12.70

3.5

0

0

0

8.94

2.27

19.42

4

0

0.61

0.91

17.93

9.57

36.23

3.5

1.86

4.83

2.41

10.69

1.98

6.93

4

0

0.66

0.65

7.14

2.68

11.74

The number of contacts is expressed as a percentage of the total gait cycles.
https://doi.org/10.1371/journal.pone.0217336.t003

the MTC instant, the swing leg and the trunk were located ahead of the support leg. The MTC,
under the C- and CT-restriction cases, was lower than that during normal walking for bothlegs and walking speeds.
Another measure of the reduction in MTC is the number of toe contacts with the ground in
the middle-swing phase. Table 3 lists the number of toe-contact events of each subject in termsof the percentage of the total gait cycles. Although toe contacts occurred even during normal
walking, the occurrences under the C-restriction case were higher than those during normal
walking, and even higher, under the CT-restriction case, for all subjects. The number of toe
contacts with the ground was more than twice in the C-restriction case, and more than fivetimes in the CT-restriction case, in comparison with normal walking. The ease of reducing the
MTC is subject dependent, and as shown in Table 3, three subjects (B, D and E) experienced
toe-contacts in almost every stride for both restriction conditions, and subject-G experienced
the same frequency of toe-contacts in the strongest restriction condition, which is the CTrestriction at the walking speed of 4 km/h.
Additionally, we observed that the dominant leg of the subjects (right leg) tended to contact
the ground less frequently than the other leg, and that the number of contacts tended to behigher at a higher speed (4 km/h).

MTC distribution
The distribution of the MTC was not Gaussian in all the walking conditions (normal andrestricted) and walking speeds. As previously reported [10], the MTC is positively skewed andleptokurtic.

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Technique to simulate the gait motion of the elderlyFig 4. MTC median and variability (IQR) of a representative subject. The general tendency of the MTC of the subjects during restricted walking(C = C-restriction case, C + T = CT-restriction case) included a lower MTC median and IQR, compared to normal walking (N), for both right (R) andleft (L) legs. � p < 0.01 indicates a significant lower MTC median compared to normal walking. The edges of the box plot correspond to the 25-th and75-th percentiles, and the single points (outliers) correspond to the MTC values that were distant from the general tendency.
https://doi.org/10.1371/journal.pone.0217336.g004

Fig 4 shows the main characteristics of the MTC distribution of a representative subject,because a similar tendency was observed in all the subjects. In addition to the lower MTC
median, we observed that the variability (IQR) of the MTC in restricted walking tended to belower than that in normal walking.
Table 4 shows the IQR of the MTC averaged among the subjects. The IQR corresponding
to CT-restriction was lower than that in the C-restriction, and the IQR is higher at a speed of
4 km/h. The MTC IQR tends to be higher in the dominant leg, during normal and restrictedwalking.

Discussion
Effect of MARTT restriction in MTC reduction
The reduction in MTC can be described by the changes in the joint angles, resulting from therestriction of the expansion range of the muscles. From the point of view of the MTC instant,the subjects exhibited the following: when the muscles at the calf alone were restricted, theMTC was reduced due to a lower dorsal flexion of the ankle (the maximum flexion decreasedby 1.7˚ at 3.5 km/h and by 0.6˚ at 4 km/h, on an average). Some subjects additionally exhibited
lower hip flexion, which enhanced MTC reduction. When the muscles at both the calf andthigh were restricted, the MTC was mainly reduced by the lower hip flexion (the maximum
flexion decreased by 2.6˚ at 3.5 km/h and by 3.0˚ at 4 km/h, on an average). In few subjects,
Table 4. MTC variability (IQR) among subjects.
Walking Speed [km/h]

Leg

Normal walking [mm]C-restriction [mm]CT-restriction [mm]

3.5

Left

5.16 ± 1.35

4.98 ± 1.75

4.43 ± 1.33�

Right

6.04 ± 1.31

5.01 ± 1.81�

4.75 ± 2.01�

Left

5.84 ± 2.49

5.37 ± 1.63

4.48 ± 1.27�

Right

6.13 ± 1.90

4.94 ± 1.44�

4.92 ± 2.21�

4�

p < 0.1 indicate a significant reduction in the IQR in comparison with normal walking.

https://doi.org/10.1371/journal.pone.0217336.t004

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Technique to simulate the gait motion of the elderly

the restriction at the thigh also caused a reduction in the knee flexion. Thus, the principal
restriction effect of the C-restriction was the reduction in the ankle flexion, and that of the CTrestriction was the reduction in the hip flexion at the MTC instant.

Effect of the walking speed
MARTT reduced the MTC in both the C- and CT-restriction approaches, regardless of thewalking speed. However, the combination of CT-restriction and a walking speed of 4 km/h
(faster speed) achieved the highest reduction in MTC, as shown in Table 2.
Moreover, as it is natural for the human body to compensate restricted motions, certain
subjects exhibited higher hip and knee flexion during the swing phase, when the ankle flexion
was reduced by C-restriction. For these subjects, this compensation was reduced or eliminatedat a walking speed of 4 km/h or when the thigh was restricted.

Similarities and differences between MARTT-restricted youth and theelderly
MARTT can simulate a higher number of MTC values near zero clearance, as observed in theelderly, which can potentially lead to a fall. This increment in the occurrence frequency of low
MTC values was reflected in a considerable number of toe contacts with the ground, for all
the subjects, as listed in Table 3. Therefore, reproducing the higher ground-contact risk of theelderly is feasible using MARTT.
The difference in the gait motion between the elderly and the young adults restricted by
MARTT was observed in the MTC variability. During restricted walking, the variability of the
MTC of the subjects was lower than that in normal walking due to the limitation of the fullrange of flexion of the hip and ankle joints by applying MARTT, which prevented the exceeding of a certain maximum flexion value, in the subjects. As a result, the sporadic occurrencesof high MTC values commonly observed in the elderly during walking [10] due to their loss ofcontrol of muscle contraction, were not simulated.
When both restriction cases are compared, the number of toe ground contacts was higher
when both the calf and thigh muscles were restricted. Thus, the restriction at the thigh canbe mainly useful for reducing the MTC of subjects, who are skillful enough to overcome therestriction at the calf muscles.
Furthermore, considering the complete gait cycle, can MARTT simulate the changes injoint motion that account for the compensation of the lower MTC, and simulate the gait characteristics caused by muscle weakness, reported in elderly walking? As mentioned in the studyof Prince et al. [11], considering the complete gait cycle, the elderly exhibit the followingchanges in the joint motion: higher hip ROM, higher knee ROM, and higher knee flexion at
the end of the swing phase, which are actions for safer walking. Additionally, lower ankle
ROM, and a lower ankle plantar flexion peak were also reported, which are signs of muscle
weakness in the elderly. These changes, other than a reduced ankle ROM, were also found in
most subjects, when MARTT was implemented, as indicated in the Results section and Fig 2.
The ankle ROM was higher after MARTT was applied because of the higher ankle dorsal flexion at terminal stance, which is due to the weakness of the gastrocnemius muscle that cannot
deaccelerate the ankle dorsal flexion after mid-stance. In addition, MARTT could also reproduce the reduction of the single support phase, in the majority of subjects.
In future, we intend to assess MARTT in environmental conditions, including slopes andobstacles, to determine the effectiveness of the technique in reducing the MTC under suchconditions. As suggested in the study of Khandoker et al. [8], the elderly exhibit a lower MTC
median while walking on positive slope surfaces than on flat ones. Additionally, as found in

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Technique to simulate the gait motion of the elderly

the study of Hill et al. [28], falls in the elderly are likely to occur, when tripping over an obstacle. Therefore, the assessment of the relationship between the MTC and tripping in such typesof challenging paths is required, and MARTT can be used as a method to further these studies.

Conclusion
MARTT, a technique devised for reproducing the healthy-elderly gait characteristics inyouth, particularly the lower Minimum Toe Clearance (MTC), was investigated in this study.
This technique was implemented in the shank and thigh to limit the transversal area ofmuscle’ belly during muscle contraction, thereby limiting the range of motion in joints. As
hypothesized, by using MARTT, the MTC median was significantly reduced to values lower
than 10.1 mm, which agree with the MTC values found in the elderly, while reproducing
other gait characteristics of the elderly, including lower single support phase and specificjoint motion characteristics. Due to MTC reduction, the toe-contacts increased by at least
double, when the shank muscles were restricted, and by five times, when both the shank andthigh muscles were restricted. The restriction of the shank muscles reduced principally thedorsal flexion of the ankle, while that of the thigh muscles reduced the hip flexion, without
gait impairment.
Thus, we believe that the implementation of MARTT can broaden research on the walkingof the elderly, and aid the development and evaluation of assistive devices for the MTC, by utilizing youth, in certain studies, where ethical principles restrict the participation of the elderly.

Supporting information
S1 Table.
(XLSX)

Author Contributions
Conceptualization: Yasuhiro Akiyama, Shogo Okamoto, Yoji Yamada.
Data curation: Jessica Beltran Ullauri.
Formal analysis: Jessica Beltran Ullauri.
Funding acquisition: Yoji Yamada.
Investigation: Yasuhiro Akiyama, Shogo Okamoto.
Methodology: Jessica Beltran Ullauri, Yasuhiro Akiyama, Shogo Okamoto, Yoji Yamada.
Project administration: Yoji Yamada.
Resources: Yasuhiro Akiyama, Yoji Yamada.
Software: Yasuhiro Akiyama, Yoji Yamada.
Supervision: Shogo Okamoto.
Validation: Jessica Beltran Ullauri, Yasuhiro Akiyama, Shogo Okamoto, Yoji Yamada.
Visualization: Jessica Beltran Ullauri, Yasuhiro Akiyama.
Writing – original draft: Jessica Beltran Ullauri.
Writing – review & editing: Yasuhiro Akiyama, Shogo Okamoto.

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Technique to simulate the gait motion of the elderly

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