A study of eye movement during dual-task walking in elderly individuals

Abstract

[Purpose] Older adults are at higher risk of falling during dual-task walking; however, their eye movements during such time are unclear. Our previous studies measured eye movements during pseudo-walking (walking in place), with and without calculation tasks, to investigate the mechanisms of falls experienced by elderly individuals during dual-task walking. This study aimed to clarify whether eye movement during actual walking are similar to those during pseudo-walking obtained previously and examine the mechanism of falls during actual dual-task walking in elderly people. [Participants and Methods] Participants were 15 healthy older adults (four men, 11 women, mean age; 85.3 ± 5.8 years). A wireless eye movement-measuring device was used to measure eye movements during single-task walking without calculations, dual-task walking with calculations, and walking while consciously looking ahead. [Results] Eye movements during walking were similar to those observed during pseudo-walking. [Conclusion] During actual dual-task walking, the eyes move but are not focused on the forward visual field, increasing the risk of stumbling, a major cause of falls, and makes individuals more susceptible to falls.

INTRODUCTION

Humans obtain about 80% of the necessary information from vision¹⁾. In general, reduced vision impairs balance function and increases the risk of falls²⁾. When walking, by paying attention to the forward vision, necessary visual information can be selected by choice, environmental information can be grasped in advance, and danger can be quickly detected to prevent falls. Visual information is important in fall prevention, and we believe that not only visual acuity, but also eye movements are necessary in moving the eyeballs to search the visual field.

Humans often walk while doing various tasks, such as doing calculations, talking loudly, or doing other work. This type of multi-tasking is called “dual-task walking” because the walker concurrently walks and performs another activity. Dual-task walking is strongly associated with an increased incidence of falls^3,4,5) and has been reported to slow down walking speed and increase trunk sway^6,7,8,9). One reason for this is that the amount of available attentional resources decreases with age, which makes it difficult for the prefrontal cortex to allocate attentional resources effectively¹⁰⁾. Hence, older adults are at higher risk of falling during dual-task walking, but the eye movements at that time are unclear.

Our previous studies have focused on visual factors, which are distinct from the physical and cognitive factors associated with falls, and have measured eye movements during walking in place with a calculation task (dual-task pseudo-walking) and walking in place without a calculation task (single-task pseudo-walking) to investigate the mechanism of falls experienced by elderly people during dual-task walking^11,12,13). The results showed that eye movements during dual-task pseudo-walking were larger than those during single-task pseudo-walking and were also different from eye movements during conscious forward-looking walking. Furthermore, it was found that during dual task pseudo-walking, the feet were not raised and stumbled more easily than during single task pseudo-walking. However, this is only the result of pseudo-walking and may not reflect actual walking. In our previous studies, the device used to measure eye movements was also wired, which limited the measurement distance and resulted in the use of pseudo-walking, or walking in place.

Therefore, the purpose of this study was to clarify whether eye movement during actual walking are similar to those during pseudo-walking obtained in our previous studies, since eye movement data can be collected wirelessly in recent years, and to examine the mechanism of falls during actual dual-task walking in elderly people.

PARTICIPANTS AND METHODS

The participants in this study were 15 healthy elderly people (4 men, 11 women; mean age, 85.3 ± 5.8 years). The inclusion criteria required that all participants had unimpaired vision in daily life and a binocular visual acuity of 0.7 or better (the static visual acuity required to hold or renew a driver’s license), either naked or with corrective aids. All participants were informed of the purpose of this study, both in writing and verbally, and written consent was obtained from each participant. This study was approved by the Seijoh University Research Ethics Committee (2016 C0024).

The testing environment was a hallway 2.0 m wide, 2.4 m high, and 15 m long, and the walking distance was 10 m. The measurement tasks were as follows: (1) single-task walking (walking while looking ahead); (2) dual-task walking (walking while calculating 2 digits × 1 digit); and (3) control-task walking (walking while consciously looking ahead). The purpose of the control task was to ascertain the eye movements of the participants when they were consciously controlling their vision.

To eliminate the influence of the vestibulo-ocular reflex¹⁴⁾, participants were instructed to walk at their normal walking speed without moving their face. In addition to eye movements, the time and the number of steps required to walk 10 m were also measured and compared to confirm the influence of the calculation task on walking. Measurements were taken once each and in the following order: single-task walking, dual-task walking, and control-task walking to prevent the participants from noticing that they were consciously looking. A rest period of approximately 5 minutes was provided between each task.

The task that was performed during the dual-task walking involved “2-digit × 1-digit multiplication”, which has been described as a working memory task. This calculation task requires working memory to temporarily store the necessary information and perform the calculation processing. At the start of the walk, participants were asked to continue solving the problem until they correctly answered an orally presented question. The examiner was positioned diagonally behind the participants to avoid disturbing their walking pace or blocking their view.

Eye movements were measured at a sampling rate of 30 Hz using a goggle-type eye movement measurement system (TalkEye Lite; Takei Kiki Co., Ltd., Niigata, Japan). The detected light wavelength was 870 nm, and the detection ranges were 50° to the left, 50° to the right, 20° up, and 20° down. The detection resolutions were 0.1° (≤ ± 20°) and 0.5° over the entire area. The detection errors were less than 1° (≤ ± 20°), 2° (≤ ± 40°), and 3° over the entire area. For each task, we assessed the binocular synthetic motion angle during 10 m walking and calculated the vertical and horizontal eye movement angles per unit time (unit: degrees/second). The 10 m walking time was measured with a stopwatch (seconds), and the number of steps taken was measured with a counter (steps).

All values were presented as mean ± standard deviation. One-way repeated-measures analysis of variance and Bonferroni’s multiple comparison test between tasks were used to compare the vertical and horizontal eye movement angles, 10 m walking time, and number of steps per unit time during the three tasks. Before analyzing the data, a Q-Q plot was created to confirm that the data followed a normal distribution. The effect size (η2) was also calculated due to the small sample size. SPSS (version 24.0; IBM Corporation, Chicago, IL, USA) was used to analyze the data, and statistical significance was set at p<0.05.

RESULTS

The vertical and horizontal eye movement angles during the three walking tasks are presented in Table 1. The vertical eye movement angle was significantly larger in dual-task walking than in single-task and control-task walking (p=0.046 and p=0.051, respectively, η2=0.11). The horizontal eye movement angle also tended to be larger in dual-task walking than in single-task or control-task walking (both p=0.082, η2=0.09). There were no significant differences in either vertical and horizontal eye movement angles between the single- and control-task walking movements.

Table 1. Comparison of the vertical or horizontal eye movement angles between the single, dual and control tasks.

	Control task	Single task	Dual task	p-value	Effect size (η2)
VEM-angle (deg/s)	34.5 ± 25.6	36.8 ± 25.7	61.1 ± 47.4	†	0.11
HEM-angle (deg/s)	37.4 ± 26.2	38.4 ± 27.5	57.7 ± 42.8		0.09

Values are mean ± standard deviation.

One-way repeated ANOVA to compare the three walking tasks, followed by Bonferroni tests for multiple comparisons.

*p<0.05. Control task significantly different from single task.

^#p<0.05. Control task significantly different from dual task.

^†p<0.05. Single task significantly different from dual task.

VEM-angle: vertical eye movement angle; HEM-angle: horizontal eye movement angle; ANOVA: analysis of variance.

The walking conditions during the three walking tasks are presented in Table 2. The 10 m walking time was significantly slower in dual-task walking than in single-task or control-task walking (p=0.004 and p=0.002, respectively, η2=0.04). There was no significant difference in 10 m walking time between single- and control-task. The number of steps taken was significantly higher in dual-task walking than in single-task or control-task walking (p=0.002 and p=0.001, respectively, η2=0.05). There was no significant differences in the number of steps between single- and control-task.

Table 2. Comparison of the 10 m walking time and the number of steps between the single, dual and control tasks.

	Control task	Single task	Dual task	p-value	Effect size (η2)
10 m walking time (s)	12.1 ± 4.1	12.6 ± 4.2	14.2 ± 5.5	##, ††	0.04
Number of steps (steps)	21.0 ± 4.8	21.4 ± 5.0	23.6 ± 5.9	###, ††	0.05

Values are mean ± standard deviation.

One-way repeated ANOVA to compare the three walking tasks, followed by Bonferroni tests for multiple comparisons.

*p<0.05, **p<0.01, ***p<0.001. Control task significantly different from single task.

^#p<0.05, ^##p<0.01, ^###p<0.001. Control task significantly different from dual task.

^†p<0.05, ^††p<0.01, ^†††p<0.001. Single task significantly different from dual task.

ANOVA: analysis of variance.

DISCUSSION

In the present study, the eye movements during dual-task walking while performing calculations were larger than those during single-task walking. Furthermore, eye movements during dual-task walking differed from those during the control task, in which participants were instructed to consciously look ahead. These results were similar to those obtained in our previous study on pseudo-walking.

Humans tend to unconsciously move their eyes upward when they are thinking^{15, 16)}. This may be related to the influx of information received from the eyes. In this study, despite the visual environment being the same, differences were observed in eye movements during dual-task walking and single-task walking. This could be attributed to the performance of the calculations task. When thinking, a lot of information needs to be processed. To reduce the load of information processing, we try to block out information from our eyes by looking away from our gaze and looking at an empty landscape (a landscape with little or no information)^{16,17,18,19,20)}. In particular, the movement of the eyes upward appears to have increased vertical eye movements during dual-task walking.

The increase in eye movement does not imply that the participants were searching for the visual field; rather, it can be interpreted as a movement that occurs to reduce the amount of visual information obtained (i.e., they are not looking ahead). In addition, the eye movements during dual-task walking were different from those during walking when the participants were consciously looking at their front field of view, which suggests that they were not looking at the forward visual field.

Regarding to walking, previous studies on dual-task walking in elderly individuals have reported slower walking speed and trunk swaying during walking^6,7,8,9). The calculation task affected walking in the present study, with slower walking speed and more steps taken during dual-task walking than during single-task walking. The increased number of steps implies a narrower step length. The decline in walking speed is caused by a decrease in step length²¹⁾. Narrower step-length weakens push-off at the feet when walking, and decreases the propulsive force^{22, 23)}. A narrow step-length also results in less center of gravity shift from side to side, and the feet do not rise. There were thought to increase the likelihood of “stumbling”, which is also a cause of falls²⁴⁾.

In conclusion, during actual dual-task walking, the eyes move but do not look properly at the forward field of vision, and the stride length becomes narrower, which may delay the perception of danger and increase the risk of stumbling, suggesting factors that contribute to the risk of falls during dual-task walking among the elderly. These factors increased the risk of stumbling, the main cause of falls, and dual-task walking was thought to be more likely to cause falls.

The strength of this study is that it focused on visual function rather than conventional motor or cognitive function and confirmed the risk of falling based on eye movements during actual dual-task walking. Based on the results of this study, we would next like to investigate eye movements while stepping forward with one foot, which is one of the reactions used to recover balance after stumbling, and consider fall prevention measures from the perspective of visual information.

However, this study has several limitations and issues. The number of participants in this study was small, and the results cannot be generalized to the elderly community-dwelling population. Therefore, the number of participants needs to be further increased. In addition, the device used in this study does not have the ability to distinguish between saccadic and smooth-pursuit eye movements. Since the present study was limited to a comparison of the magnitude of eye movements during single-task and dual-task walking, it is necessary to consider research methods for analyzing the characteristics of eye movements during each type of walking. Furthermore, factors such as height, leg length, and body mass index^{25, 26)}, which are thought to influence walking ability, were not collected, and these factors should also be considered when conducting future research on walking.

Funding

This work was supported by the Japan Society for the Promotion of Science program for KAKENHI (grant numbers JP16K01481, 20K11035, and 24K14073).

Conflict of interest

The authors declare no conflict of interest related to this study or its publication.