Department of Human Factors EngineeringWalking is an important element of various daily life activities. Walking can be the simplest indicator that can quantitatively characterize an individual's condition. To predict information about people based on their walk, multiple factors that influence walking have been researched. The factors could be divided into cognitive state and physical state. Therefore, this study selected emotional state and body composition as the main factors affecting walking to determine each of the two influences.
In previous studies, the effect of emotional state and body composition was measured using a motion capture analysis or a force plate. However, identifying emotions and body composition through motion capture analysis requires sensors to be attached to a person and cannot be done in a noisy environment. As a result, it is impossible to find out the state of emotions and body composition through motion capture analysis in public places such as streets or shopping malls. Therefore, research into how a pressure platform can predict emotional state and body composition because a pressure platform does not need any sensors attached to the body and can be installed hidden.
Forty-seven participants (24 men, mean 21.8 years, SD 2.3 years23 women, mean 22.2 years, SD 3.3 years) were recruited for this study. Before the main experiment, their body composition was measured in the morning by Inbody 570, which uses direct segmental multi-frequency bioelectrical impedance analysis. In the main experiment, the participants performed four walking tasks. One was a natural walking task, and the others were the emotional walking tasks (sadness, neutral, and joy). Two-minute video clip-based stimuli were used to induce emotions. During the tasks, the participants walked barefoot on the 10 m walkway with an installed pressure platform back and forth. While walking, the gait patterns described by spatiotemporal parameters, diagram of the center of pressure (CoP), and force and pressure of foot were measured. After the tasks, the intensity of valence, arousal, and physical activity were measured by the two questionnaires.
The analyses were conducted separately into men and women. Repeated ANOVA with Tukey post-hoc analyses was performed to examine the effect of emotions on gait patterns measured during the emotional walking tasks. Pearson correlation and multiple linear regression analyses were performed to determine the effect of body composition on the gait patterns measured during the natural walking task.
According to the intensity of valence, gait patterns were changed. Walking feeling joy increased stride length, cadence, and velocity and decreased step time. With increased walking speed, the percentage of stance phase and double support phase were reduced, and the swing phase was longer during a whole gait cycle. The length of the CoP path during the single support phase was increased. The first peak force and the second peak force during 100% of the gait cycle increased, and time to the first peak reduced. In the only men, less mediolateral displacement of the CoP intersection point was presented.
In the men, height and right leg fat-free mass had a commonly positive correlation with stride length, walking speed, and length of the CoP path during the stance phase and the single support phase. They had a negative correlation with the anteroposterior of the CoP intersection point. Weight presented a strong correlation with a maximum force of forefoot and heel and was moderately correlated with midfoot. As the total and segmental fat mass increased, the maximum force of forefoot, midfoot, and heel increased similar to weight. The body mass index (BMI) was correlated with a maximum force of forefoot and midfoot. In the regression prediction model, total and segmental fat mass (right arm, trunk, and right leg fat mass) were indirectly predicted by decrease in two CoP variables, mediolateral displacement of CoP intersection point and length of CoP path during stance phase with a direct effect of increased maximum force of right forefoot and right midfoot. Total and segmental fat-free mass (right arm, trunk, and right leg fat mass) were indirectly predicted by the length of the CoP path during the stance phase and maximum force with the direct effect of decreased contact time of right heel.
Contrary to the men, height and total fat-free mass were correlated with weight in the women. Weight was correlated with the maximum force of forefoot and heel. The maximum force of midfoot did not show the correlation with body composition. Weight, BMI, and total and segmental fat mass, which were intercorrelated with each other, were correlated with the contact time of forefoot and midfoot. In the regression prediction model, the direct effect predicted most of the fat mass and fat-free mass. Total and segmental fat mass were predicted by a decrease in length of CoP during the right single support phase and an increase in the maximum force of forefoot, while total and segmental fat-free mass were predicted by an increase in the maximum force of forefoot.
This study will help to understand the relationship between emotion and body composition on gait patterns. It will be the basis for developing models to predict an individual's emotional state and body composition using a pressure platform, and further to provide personal information that can be used in marketing.clos
