The difference of gait characteristic according to the variety of dual tasks in young healthy adults

Abstract

BACKGROUND:

Walking in daily life is often accompanied by an attention-demanding task, which requires a different attentional load and external environments. Therefore, various gaits require complex and systematic interactions between several nervous systems, such as sensory association, cognitive functions, and the musculoskeletal system.

OBJECTIVE:

Dual-task conditions during gait can affect the interaction between cognitive processing and motor behavior. This study investigated the effect of two types of cognitive dual tasks and one type of manual dual task (MDT) on kinematic and spatiotemporal parameters of gait in young healthy adults.

METHODS:

We recruited 30 healthy young adults in this study. All participants performed normal gait, and two types of cognitive tasks (subtraction dual task, SDT; and working memory dual task, WMDT) and MDT (carrying a cup filled with water) during gait. This study assessed kinematic data during the stance and swing phases and spatiotemporal parameters.

RESULTS:

MDT gait showed a significant decrement of hip-joint movement during the stance phase compared to the normal gait (p < 0.05). Stride velocity significantly decreased during SDT and WMDT gait compared with the normal gait (p < 0.05). MDT gait showed significant decrement of all spatiotemporal parameters of gait compared with normal gait (p < 0.05).

CONCLUSION:

We reported that MDT gait can induce decreased hip-joint motion during the stance phase and reduced all spatiotemporal parameters to maintain balance and reduce the risk of falling. Therefore, motor dual tasks while walking would be useful as an intervention strategy to rehabilitate or train people at risk for falling.

Keywords

Dual task attention demanding task manual dual task gait analysis

1 Introduction

Walking is defined as the main gait of locomotion and one of the most common activities of human daily living. It moves the body forward and maintainsposture stability by using the repeated sequence of limb motion [1 –3]. Walking is considered to be a relatively simple physical activity; however, it is more complex than it seems to be [4, 5]. Unlike the laboratory environment, walking in daily life is often accompanied by an attention-demanding task, which requires a different attentional load [6, 7]. External environments are also known to influence the gait function. Therefore, various gaits require complex and systematic interactions between several nervous systems, such as sensory association, cognitive functions, and the musculoskeletal system [5].

Many studies have investigated the interference of cognitive and motor dual tasks with changes of temporal and spatial gait parameters, and the relationship with balance ability in old adults or patients with brain injury [8, 9]. Dual tasks while walking can determine the interaction between cognitive processing and motor behavior. It is well known that the cognitive dual-task gait can decrease gait velocity and increase gait variability in normal healthy adults as well as patients with balance problems [10, 11]. The cognitive dual-task condition has been more often used than MDT (manual dual task) in many studies [12], however, there are more situations that require MDT than cognitive dual task in daily living [9]. In addition, there is not sufficient evidence to demonstrate the influence of MDT on changes of kinematic and spatiotemporal parameters of the gait, because the standardized evaluation method for the MDT is not structured systematically and its performance cannot be easily quantified.

Many studies have reported on the decrement of gait-related variables during walking with attention-demanding dual tasks or motor dual tasks [8, 13–15 , 8, 13–15]. They suggested that simple manual tasks did not affect spatiotemporal parameters or the variability of gait in both young adults and children. On the other hand, a complex manual task influenced the gait parameters negatively, especially in school-aged children, who were more influenced by a complex manual task.

Therefore, the aim of this study was to investigate the effect of two types of cognitive dual tasks and one type of MDT on the kinematic and spatiotemporal parameters of gait in young healthy adults.

2 Methods

2.1 Subjects

Thirty young, healthy adults (20–29 years of age, male; 16, female; 14) participated in this study. Inclusion criteria for this study were as follows: (1) no history of musculoskeletal and neurologic problems, (2) independently performing the activities of daily living (ADL) and walking, (3) no cognitive problems like dementia (mini mental state examination; MMSE > 23 score). All participants provided informed consent, and the study was approved by the institutional review board in Dankook University.

2.2 Measurements

2.2.1 Gait measurement

The kinematic and spatiotemporal parameters of the gait were collected using a LEGSys + wearable device (BioSensics, Cambridge, MA, USA). Five wearable sensors (5.0 cm×4.2 cm×1.2 cm) were connected to a computer by Bluetooth and contained tri-axial gyroscopes, accelerometers, and magnetometers [16 –18]. Each sensor was attached by Velcro straps to the anterior surface of both shins 3 cm above the ankle, anterior surface of both thigh 3 cm above the knee, and the low rear center of the posterior superior iliac spine (PSIS). The sampling frequency of the sensors used in this study was 100 Hz. The subjects were instructed to walk a 7 m walkway [19], which required five or more strides. The experiment measured each stride’s characteristics as they emerged during the gait task. This study obtained kinematic data (e.g., joint angle) and spatiotemporal data (e.g., step length, stride length, velocity, et al.) from the middle three strides and excluded the first and last strides [20]. We measured the ROM of knee and hip joints during stance and swing phases, respectively, and stride length, stride velocity, step length, and cadence during the walking task. We also measured the coefficient of variation (CV % = 100*(Std/Mean)) for participants’ stride time, stride length, and stride velocity [21].

2.2.2 Dual task

This study used two different dual tasks for the attention-demanding task and manual task during the gait. The two attention-demanding tasks and manual tasks were as follows. First, in a subtraction dual task (SDT), participants performed arithmetic (such as serial subtraction) when they were walking (22). Participants were instructed to serially subtract seven or nine from a given number between 100 and 200 to prevent learning effects. Second, in a working-memory dual task (WMDT), subjects were instructed to speak the reverse of a date randomly offered by the experimenter, while walking (e.g., 08 June 2017 ⟶ 2017 June 08) [23]. Finally, participants were instructed to carry a cup filled with water without spilling it while walking [24, 25]. Participants were instructed to go back to starting line and retest when they spilled water. All subjects performed two different dual tasks during gait and one normal gait at a self-selected comfortable speed. Each walking task was repeated three times [26, 27].

2.3 Experimental procedure

Subjects were asked to begin in a standing position at the starting line and then walk at a given signal, like “start”. This study measured three trials for every condition. Subjects were instructed to stop when they arrived at the finish line regardless of signal and remain in a standing position like the starting position. They were asked to continually perform the dual-cognitive task and stop when they arrived at the finish line. If they gave up the task or stopped walking during the experiment, it was excluded. Subjects went back to the starting line and were retested.

2.4 Statistical analysis

Data analysis was performed using SPSS software (ver. 20.0; SPSS, Inc., Chicago, IL, USA). One-way repeated analysis of variance (ANOVA) with Bonferroni post-hoc was used to compare the differences between each of the four conditions in the group. Statistical significance was set at 0.05.

3 Results

3.1 Demographic data

Characteristics of the study participants are shown in Table 1. The mean age of participants age comprised sixteen male and fourteen female was 21.47±1.70 years (range 20–29 years). The mean height and weight were respectively 168.32±9.38 cm and 63.20±11.50 kg. The score of MMSE was 27.50±1.05 score (range > 23 score).

Table 1
Demographic data of participants

Age (years) 21.47 (1.70)

Gender

Male 16

Female 14

Height (cm) 168.32 (9.38)

Weight (kg) 63.20 (11.50)

MMSE (score) 27.50 (1.05)

Values represent mean (±standard deviation).

3.2 Kinematic parameters

Kinematic analysis of knee and hip joints while walking is shown in Table 2. MDT gait showed a significant decrement of the hip joint movement during the stance phase, compared to the normal gait (p < 0.05), however, knee-joint movement did not differ between the MDT gait and normal gait (p > 0.05) (Fig. 1). In contrast, SDT and WMDT gait did not showed significant differences of knee and hip joint movements during the stance and swing phases, compared with those of normal gait (p > 0.05) (Fig. 1).

Fig.1

Knee and hip-joint angles of normalized gait cycle for participants in young adult groups according to two types of attention-demanding tasks (subtraction dual task (SDT), working memory dual task (WMDT)) and one type of manual dual task (MDT). Positive values indicate joint flexion, negative values indicate joint extension.

Table 2

Comparison of kinematic parameters between normal gait and dual task gait

	Swing knee (deg)	Swing hip (deg)	Stance knee (deg)	Stance hip (deg)
Normal	39.82 (6.88)	20.73 (7.64)	10.68 (4.84)	20.32 (6.86)
SDT	38.64 (7.11)	19.65 (8.09)	9.64 (4.55)	18.36 (5.47)
WMDT	38.73 (6.92)	20.45 (8.35)	9.95 (4.71)	17.78 (5.43)
MDT	37.08 (6.70)	19.58 (7.65)	10.49 (4.76)	17.36^* (5.80)

Values represent mean (±standard deviation). SDT: subtraction dual task; WMDT: working memory dual task; MDT: manual dual task. One-way ANOVA with Bonferroni post hoc test was used to compare the difference of kinematic parameters between normal gait and each dual task gait. ^*p < 0.05.

3.3 Spatiotemporal parameters

The spatiotemporal parameters and gait variability comparisons between SDT, WMDT, MDT, and normal gait are shown in Table 3. In the SDT gait, stride velocity and cadence were significantly decreased compared with normal gait (p < 0.05). In addition, there was significant decrement of stride velocity during WMDT gait compared with normal gait (p < 0.05); however, other gait parameters were not significantly different between the cognitive dual-task gait and the normal gait (p > 0.05). In contrast, the MDT gait showed significant decrement of all spatiotemporal parameters of the gait compared with the normal gait (p < 0.05). In comparing gait variability, there was no significant difference between the SDT, WMDT, MDT, and normal gaits (p > 0.05).

Table 3
Comparison of spatio-temporal parameters and gait variability normal gait and dual task gait

Step length (m) Stride Stride Cadence Gait variability

Left Right length (m) velocity (m/s) Stride time Stride length Stride velocity

Normal 0.72 (0.06) 0.70 (0.09) 1.42 (0.14) 1.38 (0.15) 116.90 (6.29) 3.47 (1.38) 5.45 (3.88) 7.59 (3.66)

SDT 0.69 (0.06) 0.65 (0.08) 1.33 (0.13) 1.23^* (0.18) 110.36^* (10.06) 4.61 (4.04) 6.64 (4.54) 9.57 (5.98)

WMDT 0.68 (0.05) 0.65 (0.08) 1.33 (0.12) 1.23^* (0.14) 110.96 (7.90) 6.74 (11.49) 6.02 (3.71) 9.51 (5.63)

MDT 0.61^* (0.07) 0.57^* (0.07) 1.18^* (0.12) 0.99^* (0.16) 100.80^* (10.68) 4.99 (2.18) 6.87 (4.71) 9.36 (4.86)

	Step length (m)	Stride	Stride	Cadence	Gait variability
Normal	0.72 (0.06)	0.70 (0.09)	1.42 (0.14)	1.38 (0.15)	116.90 (6.29)	3.47 (1.38)	5.45 (3.88)	7.59 (3.66)
SDT	0.69 (0.06)	0.65 (0.08)	1.33 (0.13)	1.23^* (0.18)	110.36^* (10.06)	4.61 (4.04)	6.64 (4.54)	9.57 (5.98)
WMDT	0.68 (0.05)	0.65 (0.08)	1.33 (0.12)	1.23^* (0.14)	110.96 (7.90)	6.74 (11.49)	6.02 (3.71)	9.51 (5.63)
MDT	0.61^* (0.07)	0.57^* (0.07)	1.18^* (0.12)	0.99^* (0.16)	100.80^* (10.68)	4.99 (2.18)	6.87 (4.71)	9.36 (4.86)

Values represent mean (±standard deviation). SDT: subtraction dual task; WMDT: working memory dual task; MDT: manual dual task. One-way ANOVA with Bonferroni post hoc test was used to compare the difference of gait parameters between normal gait and each dual task gait. ^*p < 0.05.

4 Discussion

The purpose of this study was to investigate the effects of two types of cognitive dual tasks and MDT on the characteristics of gait in normal healthy adults. In terms of the kinematic parameters of gait, the SDT gait and WMDT gait did not significantly influence the movements of hip and knee joints during gait compared with the normal gait. On the other hand, the MDT gait decreased the movement of the hip joint during the stance phase compared to the normal gait. In the spatiotemporal parameters of gait, the SDT gait showed a significant decrement of stride velocity and cadence, but the WMDT gait showed only decrement of stride velocity compared with the normal gait. In addition, the MDT gait had a significant decrement of step and stride length, stride time, and cadence. By contrast, there was no significant difference in gait variability during the dual task conditions compared with the normal gait.

Many previous studies have reported that the interference between gait-related variables and cognitive dual tasks are more severe in elderly adults than in young adults. However, even in young adults, interference with gait performance can occur with cognitive or motor dual tasks because of the limited information processing capacity. In 2009, Armieri et al. reported that articulated responses for a working memory task influences the gait velocity, step time, swing time. and stance time in young, healthy adults [15]. In 2014, Abbruzzese et al. reported on the effects of MDT gait in healthy, young adults (21–37 years old) and school-aged children (7–10 years old) [28]. On the other hand, In 2016, Rinaldi and Moraes reported that the older adults with histories of falling showed decreased step velocity and increased step width and time during MDT gait, compared with older adults with no history of falls [8]. Consequently, we think that both cognitive dual tasks and MDT should significantly influence the spatiotemporal changes of walking, and these results were consistent with this study. However, there was not sufficient evidence of a change of kinematic parameters by the cognitive and motor dual tasks during gait. Given our results, we assume that the decreased hip-joint movement during the stance phase could derive from s strategy for maintaining balance while doing motor dual tasks when walking. By contrast, the cognitive dual tasks might not influence the kinematic parameters of hip and knee-joint movement during walking.

In terms of gait variability, it is well known that increased gait variability is closely associated with increased fall risk in older adults. Dual task conditions during gait are commonly reported to increase gait variability [6, 29–31 , 6, 29–31]; however, several studies also reported a decrement or no changes ofgait variability during dual tasks in young adults. In 2008, Laessoe et al. reported on the increasedstride-to-stride variability with cognitive and motor dual tasks in elderly adults, in contrast, young adults did not show significantly more gait variability with dual tasks [32]. In 2005, Grabiner and Troy reported on the effects of attention-demanding task on walking in 15 young adults. The step-width variability significantly decreased while walking with a Stroop test than with a normal gait; in contrast, step width was not significantly different between the two conditions [33]. Subsequently, Wrightson et al. (2015) also suggested that the stride time variability could be reduced by cognitive dual tasks while walking in young adults [34]. In this study, similarly, variability of stride time, length, and velocity were not influenced by cognitive and motor dual tasks while walking. Consequently, we think that the changes of gait variability could be smaller in young adults while doing cognitive or motor dual tasks than in elderly adults.

However, several limitations of this study should be considered. First, we could not acquire ankle-joint angles that affected the gait. Second, carrying a cup filled with water used as a manual task for this study could not be quantized, because the level of difficulty of the manual task was reduced when participants spilled water. Third, the age group of the participants was narrow, so it might be difficult to generalize this study. In future research, different age groups should be studied.

In conclusion, we reported that MDT gait decreased hip-joint motion during the stance phase and reduced all spatiotemporal parameters except for gait variability. In contrast, kinematic parameters were not affected by attention-demanding tasks during walking. Therefore, the results of the kinematic and spatiotemporal parameters under MDT gait in this study would be helpful for intervention strategies to rehabilitate or train people who are at risk for falling. We believe that our results would support return to more complex activities of daily living for people who are at risk of falling.

Conflict of interest

The authors state that there are no conflicts of interest which might have influenced the preparation of this manuscript.

Footnotes

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF), funded by the Ministry of Education, Science and Technology (NRF-2018 R1D1A1B07049510).

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Age (years)	21.47 (1.70)
Gender
Male	16
Female	14
Height (cm)	168.32 (9.38)
Weight (kg)	63.20 (11.50)
MMSE (score)	27.50 (1.05)