appliedsciences
ArticleEffect of Gait Speed on Recovery Motion from Tripping ona Treadmill
Yasuhiro Akiyama 1, * , Hazuki Miyata 1 , Shogo Okamoto 2
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Citation: Yasuhiro, A.; Hazuki, M.;

and Yoji Yamada 1

Department of Mechanical Systems Engineering, Nagoya University, Nagoya 464-8603, Japan;
miyata.hazuki@gmail.com (H.M.); yoji.yamada@mae.nagoya-u.ac.jp (Y.Y.)
Department of Computer Sciences, Tokyo Metropolitan University, Tokyo 191-0065, Japan;
okamotos@tmu.ac.jp
Correspondence: akiyama-yasuhiro@mech.nagoya-u.ac.jp

Abstract: The analysis of the mechanism of fall avoidance motion is required to prevent fall-related
injuries. To investigate the factors that affect fall avoidance motion, tripping was induced among
10 healthy male subjects during treadmill walking at gait speeds of 3.5 and 4.0 km/h. The posture of
the subjects and ground reaction force of the recovery steps were recorded using a motion capturesystem and force plate to analyze the effect of gait speed on recovery motion. The gait parameters of
the recovery steps were calculated and compared between gait speeds. Principal component analysis
was performed to identify the parameters that represent the recovery motion and the magnitudeof the first and second recovery steps, and the balance of recovery steps were extracted as defining
characteristics. Of the 18 gait parameters, such as step time, five differed depending on gait speeds.
However, the other gait parameters and all four principal components did not differ significantly withrespect to gait speeds. Furthermore, the distribution of principal components and gait parametersacross subjects and gait speeds suggested that the variability between trials was greater than theeffect of gait speed and individual characteristics on recovery motion.
Keywords: reaction motion; gait speed; tripping; treadmill; principal component analysis

Shogo, O.; Yoji, Y. Effect of Gait Speedon Recovery Motion from Tripping ona Treadmill. Appl. Sci. 2021, 11, 7908.
https://doi.org/10.3390/app11177908
Academic Editor: Zimi Sawacha
Received: 28 July 2021
Accepted: 25 August 2021
Published: 27 August 2021

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1. Introduction
Falls in the daily living environment and workplace are particularly hazardous forthe elderly and laborers [1]. The analysis of the mechanism of fall avoidance motion willcontribute to preventing fall-related injuries. Tripping when walking is a common cause offalls [2], and the recovery motions performed by an individual after tripping have been
investigated for many years. Eng et al. identified the “elevating” and “lowering” strategies
of recovering from tripping [3]. The elevating strategy is regarded as the motion where
humans overcome an obstacle by lifting the tripped leg. In contrast, the lowering strategy is
the motion where humans place the tripped leg behind the obstacle and move the opposite
leg forward. Furthermore, a “delayed lowering” strategy is a mixture of the recovery
strategies described above [4]. The selection of these strategies is largely determined by the
gait phase in progress when tripping occurs [4,5].
The factor that affects the performance of recovery and verification motion wasinvestigated. Owings et al. analyzed the difference between successful and failed recovery
steps [6,7]. In the first literature, the perturbations were applied among older adults bysuddenly accelerating the treadmill. In the second one, an obstacle was placed on the
walk lane. According to the experiment involving tripping young adults and the elderly,
a short step time and a long step length may lead to successful recovery. Akiyama et al.
investigated the effect of step length on fall speed by restricting the recovery step using arope following contact with the obstacle on the walk lane. They found that the descending
speed of the body increases when the recovery step length decreases [8]. In addition,
Pijnappels et al. performed the tripping experiment by placing an obstacle on the walk lane

Appl. Sci. 2021, 11, 7908. https://doi.org/10.3390/app11177908

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Appl. Sci. 2021, 11, 7908

2 of 13and reported the importance of the supporting leg [9]; they found that a relatively strong
supporting leg push-off increases the length of the recovery step. Wan et al. estimatedthe tripping risk from a gait experiment performed on a walk lane and concluded thatfast walking with a large step length and small cadence decreased the tripping risk [10].
Furthermore, it has been reported that the length of the first and second recovery steps
varies among trials and individuals, according to overground tripping experiments using
an exoskeleton [11]. Therefore, previous studies have identified several key factors for
successful recovery from tripping.
In gait experiments, the subject generally walks at a self-selected [4,7,9,11] or controlled
speed [8,12]. Previous research suggests that the self-selected speed does not significantly
affect the recovery response based on the probability of the subject recovering from trippingat various self-selected speeds [13]. However, some studies suggest an increased fall risk
at a higher comfortable speed [14,15]. Klemetti et al. examined the increase in the effectof tripping at a faster gait speed through gait simulation [16]. Based on kinematics, gaitstability can be analyzed using angular momentum [17]. Fall recovery is the process of
reducing the forward angular momentum converted from the walking speed by tripping [9].
Therefore, considering the fall as the kinematic phenomenon, the magnitude of walking
speed should be examined.
Based on dynamic analysis, the imbalance caused by tripping is expected to increase
as gait speed increases owing to the concurrent increase in kinetic energy. Treadmill experiments offer the ability to control gait speed and monitor recovery motion. Although theconditions of treadmill walking are kinematically equal to those of overground walking [18],the gait motions observed on the treadmill and overground exhibit certain differences.
Stolze et al. reported that cadence increased by 6% and stride length decreased by 4%during treadmill walking under the same gait speed [19]. Riley et al. evaluated the difference between the joint angles. In the sagittal plane, the peak angles of lower limb joints
were below 2◦ [20]. Despite the aforementioned differences, treadmill experiments canbe a valuable tool for comparing recovery motions to determine the effect of gait speed
on tripping recovery, because of their capacity to control the gait speed of the subject.
However, many studies use simulated tripping instead of the actual tripping caused by an
obstacle, which occurs overground, when performing treadmill experiments. To simulate
tripping on a treadmill, certain studies have used ropes to restrict the leg swing [4,12], whilesome have simulated tripping by suddenly accelerating and decelerating the belt [6,21,22].
Furthermore, recently, the treadmill motion has been combined with a 3D video that simulates the visual stimuli of gait motion [23]. In any case, actual tripping on the treadmill israrely considered.
In this study, we examined the effect of gait speed on recovery motion using a treadmill that could trip the subject using a moving bar. The differences in recovery step
characteristics in response to changes in gait speed were also analyzed. Recovery motion
parameters, such as joint angle, and ground reaction force (GRF) were used as the metrics
for statistical comparison.
2. Methods
The experiment was conducted with the permission of the Institutional Review Board of
Nagoya University (approval number 19–11) and with the informed consent of the subjects.
2.1. Subjects
The people with gait disorders or pain during walking were excluded from participating. Finally, 10 healthy male adults, who did not participate in previous treadmill
experiments, were recruited from among the university students. The mean ± standard deviation of the age, height, and weight of the subjects were 22.7 ± 2.2 years, 171.5 ± 1.6 cm,
and 63.7 ± 5.1 kg, respectively.

Appl. Sci. 2021, 11, 7908

3 of 132.2. Experimental Setup
The subjects were tripped on a double-belt treadmill (OHTAKE ROOT KOGYO CO.,LTD, Iwate, Japan) using a perturbation mechanism (e-Valley, Aichi, Japan).
The perturbation mechanism consisted of two aluminum tripping bars and actuatedlinear sliders that moved the tripping bar in a forward/backward motion. The trippingbars were fixed sideways to the linear sliders located on both the left and right sides of themechanism and moved at the same speed as the treadmill belts. Metal plates were fixed tothe tripping bars such that they were 15 cm above the belt surface and in contact with thesubjects’ feet. The height of the obstacle was within the range of obstacles typically used intripping experiments [24,25].
The configuration of the tripping and observation system is shown in Figure 1a. The
gait phase and position of the subject were estimated using a laser range finder (UST20LX, HOKUYO AUTOMATIC CO., LTD., Osaka, Japan) located in front of the belts andfour six-degrees of freedom mobile force plates (M3D-FP-U, Tec Gihan Co., Ltd., Kyoto,
Japan) fixed under the subject’s heels and toes as shown in Figure 1b. The four force plates
weighed approximately 150 g each. These laser range finder and force plates were used tomeasure the position of both legs and the timing of heel contact (HC). The gait phase wasestimated by averaging the gait period of the five most recent gait cycles. The position of
the subject was approximated using the center of both legs. The tripping bar was set tomove at a specific time as calculated by the estimated gait phase, position of the subject,and speed of the belts to trip the subject during the intended gait phase.

Figure 1. Experimental devices: (a) Schematic of tripping treadmill configuration. (b) Force plate attached under the sole.
(c) Locations of 22 motion capture markers.

To keep the subject at the center on the treadmill belt, a marker was placed in thecenter position in front of the treadmill. To prevent the subject from anticipating being
tripped, the subject wore half-covered goggles and headphones with noise. These devices
masked the view and sound of the approaching tripping bar. For the safety of the subject,a safety harness connected to the frame above the treadmill was used. The height of theharness was adjusted to protect the subject’s head, body, and arms from collision. Moreover,plastic protectors were fitted on the lower legs and feet of the subjects.
The motion of the subject was recorded using a seven-camera motion capture system(OptiTrack, Nobby Tech. Ltd., Tokyo, Japan) and 22 markers attached to the subject asshown in Figure 1c, based on a set of critical markers [26]. The cameras surrounded thetreadmill. The GRF was recorded using the mobile force plate described above. The local
coordinates of the force plates were determined in relation to the position of the toe, heel,
and ankle markers using a calibration board. The coordinates were then converted to
global coordinates in a time series.

Appl. Sci. 2021, 11, 7908

4 of 132.3. Protocol
The experimental procedure was explained to each subject, who then provided writtenconsent. The subjects wore well-fitting sportswear with reflective markers and shoes inwhich the force plates were installed. During the experiment, the subject looked at themarker placed in front of the treadmill to ensure they maintained the central position of
the treadmill. The experiment was conducted at two speeds: 3.5 and 4.0 km/h, which were
determined through preliminary experiments. In the preliminary experiment, the subjects
were startled by tripping at high speed such as 5.0 km/h. For ethical reasons, we could not
perform an experiment under such a condition. Therefore, we selected 4.0 km/h as the fast
speed to ensure that subjects were not frightened by tripping.
The subjects performed two practice trials prior to recording. First, the subject walked
on the treadmill for 5 min each at 3.5 and 4.0 km/h. Then, an additional 5-min practice
trial was conducted with the subject wearing the half-covered goggles and headphones.
Subsequently, several tripping trials were performed for practice and to test safety devices.
The recorded trials began with walking at each speed without tripping to determine thesubject’s normal gait parameters. Following this, the subjects’ recovery motions after
tripping were recorded at 3.5 km/h and 4.0 km/h. The subject was tripped once at a
random time while walking in the single tripping trial. Subjects were permitted to restoccasionally. Tripping was timed to occur in the early to middle swing phase to consistently
assess the recovery strategy between trials. Tripping during this phase of gait was expected
to result in the use of the elevating strategy [5]. We controlled the trip timing to focus on theeffect of gait speed on tripping recovery. When tripped, the subject moved the tripped leg
forward. The first and second steps after tripping were recorded and analyzed. Images of
the tripping and recovery motions were reproduced and are shown in Figure 2. The subject
was instructed to continue walking after being tripped. Therefore, the subject returned totheir normal gait several steps after being tripped. The treadmill stopped after the recovery
and a single trial was completed. Importantly, the treadmill speed and tripped leg wererandomized between trials to prevent anticipation and learning. In total, 22 tripping trials
were conducted for each subject.

Figure 2. Tripping on the treadmill. The subject wore light-colored clothes and the left bar was notcovered by black tape for better visibility: (a) Before tripping (b). Tripped timing (left foot). (c) First
recovery step. (d) Second recovery step.

Appl. Sci. 2021, 11, 7908

5 of 132.4. Data Processing
Both the motion and GRF data were recorded at 120 Hz, and the motion data weresmoothed using a 6 Hz Butterworth filter [23,27]. Trials in which tripping occurred during
the wrong gait phase, the reaction motion was off target, or the recorded parameters
included errors were not used in the analysis. The joint angle and posture of the subject
were calculated by fitting a human model to the position of the markers using the leastsquares method. The biomechanical analysis software, SIMM (MulsculoGraphics Inc.,
Evanston, IL, USA), was used for this process [26]. The timing of the HC and toe off (TO)of each foot was determined based on the GRF. The threshold force for a gait event was set
to 80 N of vertical force. This threshold value was tuned to neglect the detection of footcontact during the swing phase. The effects of contact side differences were disregarded.
Therefore, the recorded data of trials where the right leg was tripped was mirrored to the
motion of the left leg trip.
An elevating strategy was expected based on the gait phase during which tripping
occurred [3,5]. According to this expected recovery motion, three gait events and two
motion phases were defined. The hit time (HT) was defined as the time when tripping
occurred. Then, the first step (FS) was defined as the time when the subject stepped over
the tripping bar with the tripped leg. The subsequent step performed by the recovery leg
was defined as the second step (SS). The intervals between HT and FS, and between FS andSS, were determined to be the first and second recovery phases, respectively.
The stride time and step length of non-tripped strides were calculated and comparedto the normal gait parameters. The parameters used to evaluate the recovery motion are
shown in Table 1 and Figure 3. The outliers, which were higher or lower than the range of
1.5 times the range between the first and third interquartile range, were omitted from theanalysis. Then, the mean and standard deviation of each parameter were calculated. We
considered the p-value of 0.05 to be the threshold of statistical significance. To compensate
for individual differences, certain parameters were normalized by the height, weight, andwalking speed of each subject and trial. The margin of stability (MoS) is an index forevaluating the kinematic stability of motion which is based on the inverted pendulum
model [28]. The extrapolated center of mass (XCoM) was determined by extending thecenter of mass (CoM) position, considering the CoM velocity. The safety margin from thefall was quantified as the distance between XCoM and the edge of the support foot, which
was determined as the position of the toe marker [29].
Table 1. Definitions of the recovery motion parameters.
Parameter

Definition

Stlength

Distance covered by each step (heel–heel) normalized by the subject’s height

SttimeTime duration of each stepKang

Maximum knee flexion angle during each phase

Hang

Maximum hip flexion angle during each phase

CoMVt
CoMVv

Center of Mass (CoM) speed at the FS and SS
in the traveling (Vt) and vertical (Vv) directions

MoSt

Margin of stability (MoS) at FS and SS in the traveling direction normalized by the subject’s height

GRFt

Maximum deceleration force in the traveling direction exerted on the stepping foot after the FS and SS normalized
to the subject’s weight

GRFv

Maximum GRF of the stance leg in the vertical direction during each recovery phase normalized to thesubject’s weightAppl. Sci. 2021, 11, 7908

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Figure 3. Definition of parameters: (a) Joint angles. (b) Kinematic parameters.

The correlation coefficients of the reaction motion parameters were calculated toevaluate the relationship between parameters. All parameters were z-scored, following
which principal component analysis (PCA) [30] was performed to determine the factorsthat represent the reaction motion. The differences in reaction motion parameters and PCA
scores between conditions were assessed using a statistical test. After the Kolmogorov–
Smirnov test, multivariate analysis of variance was performed for gait parameters. Then, at-test [31] was used to compare each pair of gait parameters. The principal components
were compared using t-tests with Bonferroni’s method.
3. Results
3.1. Overview of Recorded Trials
In total, 220 trials were recorded, with 11 trials for each speed being recorded foreach subject’s leg. Of the 220 total trials, 20 trials, where the subject exhibited a lowering
recovery strategy, were excluded from analysis along with 16 trials where the trip occurredin the wrong gait phase and 20 trials where irregular events such as multiple trips occurred.
Furthermore, 15 trials were disregarded owing to the obstruction of a marker. Consequently,
20 trials were disregarded as they were outliers. Therefore, 129 trials where the subject
exhibited an elevating recovery strategy were analyzed. An example of the recovery motion
observed in this experiment is shown in Figure 4.

Figure 4. Stick picture of recovery steps. The horizontal position was adjusted considering thevelocity of treadmill belt.

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Tripping in the analyzed trials occurred between 65% and 80% of the gait cycle. The
average stride time of subjects walking normally, which was recorded prior to the tripping
trials, ranged from 1.11 to 1.42 s at 3.5 km/h and from 1.06 to 1.28 s at 4.0 km/h. The
average step length ranged from 0.47 to 0.59 m at 3.5 km/h and from 0.53 to 0.63 m at
4.0 km/h.
3.2. Effect of Gait Speed on Reaction Parameters
The mean value, standard deviation, p-value, and Hedge’s g of each parameter arepresented in Table 2. Certain parameters vary significantly at different gait speeds. In
addition, the correlation matrix of the reaction parameters is presented in Table 3. This
information was used to perform PCA to determine the parameters that effectively represent reaction patterns. In the correlation matrix and PCA, the results of the trials at bothspeeds are included. The factor loadings of the four major components are calculated asshown in Figure 5. The total contribution ratio of these components was 63.8%, which
consisted of the 4 components contributing 25.1%, 17.6%, 11.4%, and 9.6%. The results ofthe t-test showed that all four principal components did not differ significantly at different
gait speeds.
Table 2. Recovery motion parameters between different gait speeds, mean (SD).
Parameter

Unit

FS Stlength

p-Value (* p < 0.05)

Hedgis-g

Slow (3.5 km/h) n = 60

Fast (4.0 km/h) n = 69

0.22

0.22

0.44 (±0.08)

0.42 (±0.08)

FS Sttimes* 0.020.42

0.55 (±0.06)

0.53 (±0.05)

FS Kang

deg

0.45

0.13

99.7 (±9.2)

100.9 (±8.1)

FS Hang

deg

0.56

0.10

38.3 (±6.6)39.0 (±7.5)

FS CoMVt

m/s

0.30

0.18

1.26 (±0.10)

1.28 (±0.11)

FS CoMVv

m/s

0.15

0.25

−0.29 (± 0.16)−0.34 (±0.20)

FS MoSt* 0.010.49−0.06 (±0.07)−0.09 (±0.07)

FS GRFt

0.52

0.11

0.25 (±0.11)

0.25 (±0.09)

FS GRFv* 0.000.51

1.11 (±0.13)

1.19 (±0.17)

0.96

0.01

0.41 (±0.04)

0.41 (±0.05)

SS Sttimes* 0.01

0.48

0.54 (±0.05)

0.52 (±0.05)

SS Kang

deg

0.16

0.25

69.7 (±4.3)71.1 (±6.6)

SS Hang

deg

0.76

0.05

28.8 (±5.4)29.1 (±6.1)

SS CoMVt

m/s

0.15

0.26

1.24 (±0.08)

1.26 (±0.09)

SS CoMVvm/s* 0.010.46−0.14 (±0.05)−0.18 (±0.08)

SS MoSt

0.10

0.29

−0.02 (±0.07)−0.04 (±0.07)

SS GRFv

0.08

0.32

0.23 (±0.06)

0.25 (±0.07)

SS GRFd

0.10

0.29

1.37 (±0.35)

1.47 (±0.32)

SS Stlength

FS = first recovery step, SS = second recovery step.

Appl. Sci. 2021, 11, 7908

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Table 3. Correlations between recovery motion parameters.

FS Stlength
FS Sttime
FS Kang
FS Hang
FS CoMVt
FS CoMVv
FS MoStFS GRFt
FS GRFv
SS Stlength
SS Sttime
SS Kang
SS Hang
SS CoMVt
SS CoMVv
SS MoStSS GRFv

FS Sttime

FS Kang

FS Hang

FS CoMVt

FS CoMVv

FS MoStFS GRFt

FS GRFv

SS Stlength

SS Sttime

SS Kang

SS Hang

SS CoMVt

SS CoMVv

SS MoStSS GRFt

SS GRFv

0.34

0.23

0.25

0.87

−0.67

0.11

0.71

0.00

0.08

0.04

0.23

−0.10

−0.16

−0.19

0.38

0.00

0.55

0.50

0.03

0.36

−0.23

−0.01

0.31

0.02

0.00

−0.07

0.17

−0.07

−0.05

−0.18

0.07

−0.01

0.24

0.37

0.20

−0.16

0.01

0.27

0.10

−0.19

−0.31

0.16

0.17

−0.15

−0.10

0.12

0.09

0.31

0.19

−0.02

−0.17

0.21

0.09

0.07

−0.10

0.35

0.71

0.08

−0.20

−0.04

0.25

0.13

−0.66

−0.05

0.62

0.04

0.22

−0.06

0.36

−0.15

0.02

−0.34

0.28

0.06

0.45

0.10

−0.61

−0.19

0.07

0.21

−0.26

0.23

0.13

0.40

−0.16

0.12

−0.71

−0.09

−0.14

−0.28

0.15

−0.19

−0.24

−0.40

0.21

0.85

−0.07

−0.14

0.19

0.00

0.02

0.33

0.01

−0.03

−0.11

0.07

0.05

0.70

−0.15

−0.07

0.21

0.13

−0.08

−0.26

−0.17

0.22

0.34

0.22

0.09

0.83

−0.31

−0.06

0.51

−0.07

−0.01

−0.16

0.12

0.19

−0.11

−0.04

−0.23

0.42

0.23

−0.41

−0.05

0.25

0.30

0.17

−0.03

−0.16

0.23

−0.02

−0.39

−0.26

0.52

−0.06

0.01

−0.56

−0.32

0.10

0.09

0.33

0.19

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Figure 5. Factor loading. Factor loading vectors of tripping recovery steps at both gait speeds
weighted by the contribution of each principal component.

4. Discussion
4.1. Overview of Reaction Motion
In this experiment, tripping can be said to have occurred during the early to middle
swing phase [32]. Compared to the gait parameters of normal overground walking, thestride time and step length were slightly shorter [33]; however, this trend is consistent with
reported characteristics of treadmill walking [19].
The first and second principal components were characterized by relatively large andstrong steps. According to the factor loadings, the first principal component is related toFS, whereas the second principal component is related to SS. Along with the increase in
first and second principal components, Stlength increased for FS and SS. In addition, thefirst principal component was positively related to the Sttime of FS. These relationships
correspond to a relative increase for each step of the recovery phase. Furthermore, Kangand Hang also increase for both recovery steps, which means that the maximum knee andhip flexion of both steps increase. This trend corresponds to a larger stepping motion.
The positive CoMVt and GRFt, which are the components of the CoM velocity and
GRF in the direction of travel, weighting of the first and second principal components
suggested that the body moved forward rapidly and that the subject decelerated that
motion using the foot that made a step. The first principal component is also strongly
related to the CoMVv of both the FS and SS, which means that the downward speed of thesubject increased whereas the second principal component only related to the CoMVv of
SS. The increase in downward speed suggests that the body largely moves in the verticaldirection during the recovery steps. Furthermore, the second principal component isnegatively related to the MoSt of both FS and SS. Understandably, the increase in CoMVt isrelated to the decrease in MoSt on SS, according to the formula for calculating MoS [28].
The third principal component is negatively related to the Kang and Hang. Therefore,
the increase in this principal component increases the compactness of the recovery step.

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The fourth principal component is characterized by a large positive MoSt, which reflects
the margin by which a fall is avoided. The safety margin was considered to be unrelated
to the other gait parameter in this principal component. Therefore, based on PCA, theprincipal components that represent the magnitude of FS and SS were identified.
4.2. Reaction Motion Strategies
Recovery from perturbation continues for several steps after tripping before motion
gradually returns to a normal gait [12]. In this experiment, we examined the characteristicsof the first and second recovery steps after perturbation. According to the PCA results inthis study, the relationship between the first and second recovery steps is weak whereas it
was extracted in the overground experiment [11] as discussed in the subsection below.
According to the principal components identified in this study, the MoS was related to
the CoMVt in the second principal component. The difference in the MoS of the recovery
step at varying treadmill speeds was not significant in this study as shown in Table 2.
Conversely, a previous study suggested that the MoS is affected by gait speed during
normal walking [34]. Furthermore, the MoS was not correlated with the step length, which
is a parameter used to calculate the MoS. This suggests that the relationship between MoS
and gait parameters differs with respect to recovery motion and normal gait.
4.3. Effect of Gait Speed on Reaction Motion
Although certain parameters differed significantly with respect to gait speed, thedifferences were slight as shown in Table 2. Furthermore, the differences among theprincipal component scores at different gait speeds were not significant. Therefore, there
was no significant change in the reaction motion performed in response to tripping between
gait speeds of 3.5 km/h and 4.0 km/h.
The effect of gait speed on the recovery motion was possibly smaller than the variability in recovery motion observed in this experiment. The distribution of the first and second
principal component scores are plotted in Figure 6. The color and shape of the data points
correspond to gait speed and subject, respectively. From this distribution, classifying theeffect of individual characteristics as well as gait speed is difficult. This means that thevariability between trials was greater than the variation caused by individual characteristics
or gait speed. Therefore, the effect of gait speed on recovery motion may be masked by thevariability in recovery motions between trials.

Figure 6. Distribution of the principal component analysis scores of each subject. Markers of the same
shape denote a single subject. Colors stand for the slow (blue-filled) and fast (red hollow) speeds.

Appl. Sci. 2021, 11, 7908

11 of 134.4. Differences between Reaction Motion on a Treadmill and Overground Walking
Previous studies revealed the difference between the normal gait motion while walking on a treadmill and walking overground [19,20]. In addition, one of the main differences
between normal gait and recovery motion is the rapid acceleration of body speed in theanteroposterior direction. A recovery step decelerates the speed of the body while therecovery leg stops the forward trajectory of the body. Therefore, the subject rapidly moves
backward on the treadmill. However, our treadmill is capable of accommodating the
subject’s backward motion, so the subject can keep walking. For extensive recovery motion
or fall experiments, the length of the treadmill may limit the experiment. Nonetheless, thesubject can perform the recovery motion on the treadmill comparably to walking overground. Therefore, the moving treadmill belt possibly facilitated the forward movement of
the subject after tripping.
4.5. Limitations
In this study, 3.5 and 4.0 km/h were selected as the slow and fast speeds, respectively.
Although these speeds were selected by considering the safety and comfort of the subject
through a preliminary experiment, this range is narrow compared to the range of gait
speeds applied in daily living. A person’s comfortable walking speed decreases when
walking on a treadmill compared to overground walking [35]. This may be because thesubject feels the gait speed faster when walking on the treadmill. Furthermore, the fear oftripping may be amplified on a treadmill. Therefore, an improved experimental system isrequired to minimize the subjects’ fear of falling on the treadmill at increased gait speeds.
The capacity to observe the recovery motion by an actual trip on the treadmill was
suggested in this study. However, the difference in the gait and recovery motions on thetreadmill and overground walk lane persist.
The weight of the force plate may have affected the reaction motion of the subjects.
However, based on the comparison of the gait parameters and joint angles in our previous
study, the mass of the force plate likely did not significantly affect the natural gait of thesubject [36].
The attribution of subjects was limited to young healthy males in this study. Hence,the effects of age, gender, and gait disorder were excluded. The effect of gait speed andtripping on the treadmill may be different for such attributions.
Because of the experimental characteristic of applying repeated perturbations, thereaction motion of the subject may differ from the one in the daily living environment.
In this experiment, we randomized the side of the tripping and the time duration before
tripping to prevent the learning effect caused by anticipation. However, the experiment
was not devoid of nervousness of the subjects.
5. Conclusions
This study investigated the effect of gait speed on recovery and fall avoidance motion
parameters using a treadmill-based tripping experiment. The tripping bar caused the actual
tripping, implying that the swing foot hit the obstacle on the treadmill. PCA was used to
identify the factors that represent the characteristics of fall recovery motion.
The result suggested that the five out of eighteen gait parameters differed significantly
at the tested gait speeds. However, the magnitude of difference was minimal. Additionally,
the distribution of principal component scores suggests that the recovery motion of eachsubject varies widely at both tested gait speeds. As such, the variation of the recovery
motion was larger than the effect size of gait speed or individuality in this experiment.
The principal components revealed an effect of gait speed on the recovery motion andthe relationship between parameters that represent the recovery motion. The difference
between the characteristics of recovery motion on treadmill and overground experiments
partly suggested the need to simulate physical and psychological situations of overgroundwalking on the treadmill.

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Author Contributions: Conceptualization, Y.A.; methodology, Y.A. and H.M.; software, Y.A. and
H.M.; validation, Y.A., H.M. and S.O.; formal analysis, H.M.; investigation, Y.A., H.M., S.O. and
Y.Y.; resources, Y.A. and Y.Y.; data curation, H.M.; writing—original draft preparation, Y.A. and
H.M.; writing—review and editing, S.O. and Y.Y.; visualization, H.M.; supervision, Y.Y.; project
administration, Y.Y.; funding acquisition, Y.A. and Y.Y. All authors have read and agreed to the
published version of the manuscript.
Funding: This research was funded by Japan Society for the Promotion of Science (JSPS) KAKENHI
Grant Number 17K01293.
Institutional Review Board Statement: The study was conducted according to the guidelines of
the Declaration of Helsinki, and approved by the Institutional Review Board of Nagoya University(approval number 19–11, 9 August 2019).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study. Written informed consent has been obtained from the patient(s) to publish this paper.
Data Availability Statement: The data presented in this study are available within the article.
Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the designof the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; orin the decision to publish the results.

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