Effects of Mental Fatigue on Gait Performance and Variability
Article information
Abstract
OBJECTIVES
Mental fatigue has been shown to negatively impact physical performance, including motor skills and neuromuscular function. This study aimed to investigate the effects of mental fatigue on gait performance and variability in healthy young male adults.
METHODS
Eighteen participants walked over-ground at their preferred speed before and after completing a mentally fatiguing Stroop task. Kinematic data were recorded to assess gait variables such as speed, step length, step time, and step width, along with their coefficients of variation (CV). Subjective ratings of mental fatigue were also collected.
RESULTS
While subjective ratings of mental fatigue significantly increased following the Stroop task, no significant changes were observed in gait performance or CV variables at the group level. However, singlesubject analyses revealed that some participants experienced significant increases or decreases in gait speed, suggesting gait performance responses to mental fatigue are individual-specific.
CONCLUSIONS
These findings indicate that although mental fatigue increases perceptibly, it may not uniformly affect gait performance in simple walking tasks. Factors such as the duration and intensity of the fatigue-inducing task, individual coping strategies, and the nature of the gait task, particularly the participant's preferred speed, likely influenced these results. Future research should explore more complex gait tasks and varied mental fatigue protocols to better understand this relationship.
Introduction
Mental fatigue is a psychobiological state resulting from prolonged periods of demanding cognitive activity [1]. Traditionally, research on the impact of fatigue on physical performance has primarily focused on physiological aspects [2]. However, recent studies have increasingly highlighted the significant role of mental fatigue in impairing various aspects of motor performance. This growing body of evidence underscores the need to consider mental fatigue as a critical factor influencing physical performance.
Mental fatigue has been shown to negatively affect physical performance across different domains. For example, it may contribute to physical fatigue during mentally demanding tasks by reducing oxygenated hemoglobin levels in the prefrontal cortex, potentially due to the redistribution of cortical resources to maintain muscle output [3]. This suggests that mental fatigue not only impacts cognitive functions but also has a direct physiological effect on the body’s ability to perform physical tasks. Additionally, mental fatigue has been found to impair neuromuscular function in women, reducing their ability to produce maximal force and increasing cortical inhibition, further demonstrating its detrimental effects [4].
In sports, mental fatigue can significantly hinder athletes’ motor skills, such as shooting accuracy in soccer, and affect crucial decision-making processes, such as evaluating ball trajectories [2]. It also impairs cognitive tasks with a motor component, like visuomotor tasks in badminton players, which require precise coordination between mental and physical actions [5].
Mental fatigue’s impact extends to exercise performance, where it increases the perception of effort, often quantified as a higher rating of perceived exertion (RPE). This heightened perception limits exercise tolerance and reduces short-term endurance performance [6]. For instance, mental fatigue has been shown to decrease running velocity in low-intensity activities and reduce oxygen consumption, indicating a clear link between mental state and physical capacity [7].
Moreover, mental fatigue poses a safety risk, increasing the likelihood of falls and slips even in healthy young individuals. It heightens the chances of slip initiation, reduces the ability to detect slips, and impairs reactive recovery responses [8]. In populations such as stroke survivors and older adults, mental fatigue exacerbates postural sway, particularly in challenging dual-task conditions, making it a critical factor in maintaining balance [9]. These findings suggest that mental fatigue can be a significant contributory factor to balance issues, even in healthy individuals who do not have pre-existing balance disorders.
Gait is a complex motor task requiring the coordination of multiple body systems, and impairments in gait performance can lead to instability and an increased risk of falls. Mental fatigue has been shown to significantly affect gait [10-12]. In young adults, it can increase step width, decrease step width variability, and increase variability in stride and stance times, potentially disrupting gait control and contributing to instability [10]. However, previous research has primarily used treadmill-based walking, which may not fully capture the subtleties of gait changes seen in real-world conditions. Overground walking, which more closely mimics everyday environments, engages different motor control mechanisms and may reveal more subtle effects of mental fatigue than treadmill walking.
In older adults, mental fatigue has been found to increase gait variability during dual-task walking, where individuals must manage both cognitive and physical tasks simultaneously [11]. It is important to distinguish between the effects of dual-task walking and mental fatigue, as they may impact gait differently. Dual-task walking splits attentional resources between two tasks, requiring the brain to allocate attention in real-time. In contrast, mental fatigue represents a more generalized depletion of cognitive function [12]. While both conditions reduce available attentional resources, the mechanisms by which they affect gait are distinct, suggesting that the effects of mental fatigue and dual-task conditions are not interchangeable. Each imposes unique demands on motor control and cognitive processing.
Significant gaps remain in the current literature regarding the implications of mental fatigue on gait, particularly as it pertains to overground gait. Gait is essential for independent living, and understanding how mental fatigue affects gait could have important implications for injury prevention, rehabilitation, and performance enhancement. Therefore, the purpose of this study was to investigate the effects of mental fatigue on gait performance and variability in healthy young male adults. By addressing these gaps, this study aims to contribute to a more comprehensive understanding of how mental fatigue impacts daily motor functions, which could inform strategies to mitigate its negative effects in various populations. It was hypothesized that engaging in a mentally fatiguing task would negatively affect gait performance in healthy young males, resulting in measurable changes in the magnitude and variability of gait speed, step length, step time, and step width.
Methods
Participants
Eighteen healthy male participants (age: 20.9 ± 1.6 years, height: 1.79 ± 0.07 m, mass: 82.9 ± 9.3 kg) were included in the study. Participants were required to have been resistance trained 2-3 times a week for the past 6 months and to have a body mass index of less than 30 kg/m2. Participants with major musculoskeletal injuries and neurological disorders that could interfere with gait performance were excluded from the study. Before conducting the research and data collection process, all participants signed informed consent forms. The study was approved by the Institutional Review Board of the University of South Dakota (IRB: 22-54).
Procedures and Data Collection
Anthropometric measurements, including height, weight, bilateral leg lengths, knee widths, and ankle widths, were recorded to scale the kinematic data for each participant. Specifically, knee and ankle widths were used to define joint centers and segment dimensions based on standard motion analysis protocols. Participants then had an opportunity to engage in a brief warm-up consisting of two minutes of running and stretching. Following the warm-up, participants walked over-ground at their preferred speed without any specific instructions or feedback regarding their walking technique. Walking trials were conducted both before and after a mentally fatiguing Stroop task. Each trial involved walking six meters, with participants completing three round trips, resulting in six total trials per condition. During each trial, data from an average of 4.13 bilateral steps (ranging from two to six) were recorded for analysis, resulting in an average of 25.17 ± 3.46 steps (range: 20 to 36) per condition across all trials. This average number of steps per condition was deemed sufficient to represent individual gait variability based on the consistency observed in the kinematic data and methodologies reported in similar studies [13,14].
Kinematic data were recorded in three dimensions using a seven-camera motion capture system with the sampling frequency of 100 Hz (Vicon, 2.13, Denver, CO). Sixteen reflective markers were placed on the participants following Vicon’s Lower Body Plug-in-Gait marker set, which included markers on the anterior and posterior superior iliac spines, lateral thighs, femoral epicondyles, lateral legs, lateral malleoli, heels, and the second metatarsal heads.
Visual Analog Scale (VAS) and Stroop Task
Participants’ subjective mental fatigue levels were assessed using a 100-mm Visual Analog Scale (VAS) both immediately before and after completing the Stroop task. The VAS is a reliable and valid tool for evaluating subjective fatigue levels [15]. The scale ranged from “none at all” on one end to “maximal” on the other, with participants marking their perceived fatigue level on the line. The distance in millimeters from the left end of the scale to the participant’s mark was recorded for analysis.
The Stroop task required participants to name the ink color of words, except when the ink was red. In such cases, participants were instructed to say the word itself rather than the ink color. For example, if the word “yellow” was printed in red ink, the correct response was “yellow.” The task was presented across five sheets of paper, each containing 45 randomly arranged words (red, blue, green, and yellow). Participants had 30 minutes to complete as many words as possible, and researchers monitored the process. Incorrect responses required participants to restart the task from the beginning. Although the number of words completed was not measured, participants were unaware of this and were encouraged to complete as many as possible within the time limit. This ensured the task remained cognitively demanding and effectively induced mental fatigue.
Data Analysis
Kinematic data processing and analysis were performed using Matlab (The Mathworks, Inc., Natick, MA). The data were filtered using a fourth-order Butterworth low-pass filter with a 6 Hz cutoff frequency. Gait performance variables, including gait speed, step length, step time, and step width, were calculated for each bilateral step within each trial and then averaged across the six trials per condition (pre- and post-Stroop). This averaging approach was used to reduce variability across trials and provide a more stable representation of each participant’s gait performance. While it is acknowledged that averaging across trials may have minimized potential fatigue-related changes occurring over time, the short duration of data collection (approximately six trials over a few minutes) likely limited the extent of fatigue dissipation. Additionally, coefficients of variation (CV = standard deviation × mean-1 × 100) were calculated for normalized gait speed (gait speed × height-1), step length (step length × height-1), and step time were calculated. The normalized CVs have been associated with fall prediction [11].
Statistical Analysis
Paired t-tests (α = 0.05) were conducted to investigate changes in gait performance and variability between two conditions (pre- and post-Stroop). The normality of data distribution was assessed using Shapiro-Wilk tests and quantile-quantile (Q-Q) plots. If parametric assumptions were violated, Wilcoxon Signed Ranks tests (α = 0.05) were used as a non-parametric alternative. All statistical analyses were performed using Jamovi software (version 2.3.28.0, Sydney, Australia).
To explore the relationship between subjective mental fatigue and gait performance changes, a correlation analysis was conducted between the magnitude of change in VAS ratings (pre-Stroop VAS minus post-Stroop VAS) and the magnitude of change in gait performance variables (pre-Stroop gait speed minus post-Stroop gait speed).
In addition to group-level analyses, simple single-subject analyses were performed to examine individual changes in gait speed between pre- and post-Stroop conditions. A scatter plot was used to visually represent each participant’s gait speed change relative to 95% confidence intervals (CIs) of the group mean. Positive values indicated a decrease in gait speed, while negative values reflected an increase. This visual representation facilitated the assessment of individual variability in gait speed changes across conditions. Gait speed was the only variable analyzed beyond group-level analyses because it is considered a key indicator of overall walking performance.
Results
The Shapiro-Wilk test and Q-Q plot analysis revealed that step time was not normally distributed (p < 0.05), whereas all other gait performance and variability measures met the assumptions of normality. Consequently, the Wilcoxon Signed Ranks test was used for step time analysis, and paired t-tests were applied to all other normally distributed variables.
The ratings of mental fatigue significantly increased following the mentally fatiguing task (pre-Stroop: 20.9 ± 18.3 mm, post-Stroop: 67.6 ± 19.6 mm, Cohen’s d: ‑2.131, p < 0.001). The average gait speed remained consistent between the conditions, with a mean difference of 0.004 m/s (95% CI: ‑0.031, 0.039, p = 0.813; <Table 1>). Similarly, step length did not change after the Stroop task, with a mean difference of ‑0.006 m (95% CI: ‑0.018, 0.007, p = 0.380). Step time also remained unchanged, with a mean difference of 0.008 s (95% CI: ‑0.017, 0.001, p = 0.060). Step width remained consistent between the conditions, with a mean difference of 0.002 m (95% CI: ‑0.009, 0.001, p = 0.473).
Gait performance values (mean ± standard deviation).
Regarding gait variability, gait speed CV was stable between the pre-Stroop and post-Stroop conditions with a mean difference of 0.54% (95% CI: ‑0.034, 1.123, p = 0.063; <Table 2>). Similarly, step length CV did not exhibit any significant difference, with a mean difference of 0.20% (95% CI: ‑0.328, 0.738, p = 0.429). Step time CV also remained unchanged, with a mean difference of -0.06% (95% CI: ‑0.388, 0.271, p = 0.711).
Gait performance coefficient of variation (CV) values (mean ± standard deviation).
There was no significant correlation between the magnitude of change in subjective mental fatigue (VAS ratings) and gait speed (Pearson’s r = ‑0.364, p = 0.138, 95% CI: ‑0.710 to 0.124).
According to the scatter plot data, individual participants exhibited varied responses between conditions <Figure 1>. Notably, participants 4, 5, 12, 15, and 17 exhibited a significant decrease in gait speed after the Stroop task, while participants 6, 10, 11, 16, and 18 demonstrated a significant increase (their values fell outside the 95% CI). However, the gait speed of the remaining participants did not change, with their values staying within the 95% CI.
Gait speed differences between conditions across individual participants.
In the x-axis each participant is represented from p1 to p18, and the y-axis represents the difference in gait speed (pre-Stroop minus post-Stroop).
The individual data points show the difference in gait speed for each participant, where positive values indicate slower gait speed after the Stroop task, while negative values indicate faster gait speed.
The solid horizontal line indicates the average difference in gait speed across participants.
The dotted lines represent the variability around this mean (95% confidence intervals), helping to assess the extent of differences.
Discussion
The purpose of the present study was to investigate the effects of mental fatigue on gait performance and variability in healthy young male adults. The main findings indicate that while subjective ratings of mental fatigue significantly increased following a 30-minute Stroop task, this increase did not translate to significant group-level changes in gait performance and variability variables, such as gait speed, step length, step time, step width, and their coefficients of variation (CVs). However, a closer examination of individual gait speed data using scatter plot analysis revealed notable variability in participants’ responses. Although the group-level analysis did not exhibit significant changes in gait speed, individual participants exhibited different responses, with some showing increases, others showing decreases, and a few displaying no change at all. This variability suggests that the impact of mental fatigue on gait speed is not uniform, with some individuals more susceptible than others, indicating the presence of “responders” and “non-responders.” These findings warrant further investigation into individual factors contributing to this variability.
The Visual Analog Scale (VAS) results confirmed a significant increase in perceived mental fatigue following the Stroop task, indicating the task effectively induced cognitive fatigue. Despite this, the lack of corresponding changes in gait performance at the group level suggests that subjective fatigue may not always translate directly to observable motor impairments. A correlation analysis revealed no significant relationship between the magnitude of change in VAS ratings and gait speed changes, further highlighting the complexity of this interaction. While some individuals experienced noticeable changes in gait speed, these changes did not align consistently with their changes in subjective fatigue ratings, suggesting other factors beyond perceived mental fatigue may influence gait performance.
Several factors could explain the lack of significant group-level differences in gait performance despite the substantial increase in perceived mental fatigue. One possibility is that the duration or intensity of the Stroop task may not have been sufficient to induce detectable changes in gait. Previous research suggests that the effects of mental fatigue on physical performance can vary significantly depending on the cognitive task used, with some tasks being more effective than others at disrupting motor function [6,7]. It is plausible that a longer or more cognitively demanding task could have resulted in more pronounced changes in gait performance.
Individual differences in coping strategies and resilience to mental fatigue may also have contributed to the variability in responses. Participants may have employed different mechanisms to mitigate the effects of mental fatigue on their gait. For instance, some participants may have consciously adjusted their walking pace or adopted more deliberate, controlled movements to maintain their performance despite feeling fatigued. Others might have relied on cognitive strategies, such as focusing their attention on the task or mentally rehearsing their gait, to counteract the effects of fatigue. These strategies align with findings from other studies showing that susceptibility to mental fatigue can vary based on factors such as cognitive capacity, fitness levels, and regular engagement in cognitively demanding tasks [4,9].
Interestingly, the findings of this study contrast with previous literature that examined mental fatigue effects on treadmill walking gait. Earlier research reported significant alterations in gait following mental fatigue when participants walked on a treadmill, while the present study observed no such group-level changes in over-ground walking [10]. This discrepancy suggests that mental fatigue effects on gait may be task- or context-specific. Treadmill walking, which imposes a constant, externally regulated pace, may reveal gait impairments more readily compared to over-ground walking, which allows for natural adjustments. These differences highlight the importance of studying gait in real-world conditions, as over-ground walking may engage different motor control mechanisms that mask the impact of cognitive fatigue.
Additionally, the nature of the gait task itself may have contributed to the absence of significant findings. Walking at a preferred speed on a flat, unobstructed path may not have been challenging enough to reveal subtle impairments in gait performance caused by mental fatigue. Previous studies have shown that gait differences are more pronounced under dual-task conditions or when distractions are introduced during walking, as these tasks impose additional cognitive demands and challenge attentional resources [10,11]. While a systematic review found that muscle fatigue frequently leads to gait alterations, with six out of nine studies reporting changes in performance, mental fatigue effects were minimal in single-task walking and primarily evident during dual-task conditions [16]. Evidence also indicates that mental fatigue affects perceived effort rather than physical performance, with no measurable decline in cardiorespiratory or neuromuscular functions during subsequent physical tasks [17]. The simplicity of the over-ground walking task in the present study may have allowed participants to maintain performance despite experiencing mental fatigue, further emphasizing the need for more cognitively demanding tasks to detect subtle gait impairments.
Differences in participant populations could also explain the variability in results across studies. Research focusing on older adults, for example, tends to report greater effects of mental fatigue due to age-related declines in both physical and cognitive functions, while younger, healthier individuals may be more resilient to its effects [4,11]. Studies on postural sway in older adults and stroke patients have also shown that neurological conditions can exacerbate the effects of fatigue [9]. These studies highlight how variations in participants, tasks, and fatigue assessment methods can lead to differing outcomes in terms of mental fatigue’s impact on physical and cognitive performance.
Future studies should consider using more diverse and prolonged mental fatigue protocols, examining a wider range of populations, and incorporating more complex motor tasks, such as dual-task walking or navigating challenging environments like obstacle courses. These tasks would provide a better understanding of how mental fatigue affects both cognitive and motor functions in more demanding scenarios. Additionally, focusing on populations more susceptible to the effects of mental fatigue, such as older adults, individuals with neurological impairments, or athletes facing high cognitive demands, would offer further insights. Gaining a deeper understanding of these relationships is crucial for optimizing both performance and well-being, particularly in environments where cognitive and physical demands are high, such as in sports and occupational settings.
Conclusions
In conclusion, while no significant changes in gait performance were observed at the group level, the single-subject analysis highlighted varied individual responses to mental fatigue. These findings suggest that the impact of mental fatigue on gait may be more individualized than previously recognized, with some individuals being more susceptible to its effects than others. Future studies should account for these individual differences by exploring the factors contributing to such variability and tailoring interventions accordingly. This approach could offer more nuanced insights into the relationship between mental fatigue and motor performance, with important implications for both safety and performance optimization across various settings.
Notes
The authors declare no conflict of interest.