Gait Variability and Spatiotemporal Parameters During Emotion-Induced Walking: Assessment with Inertial Measurement Units

TL;DR

This study shows that emotions affect walking patterns and that wearable sensors can detect these changes in real-world settings.

Contribution

The study demonstrates the feasibility of using IMUs to detect emotion-related gait changes outside of lab environments.

Findings

Stride length, time, velocity, and cadence significantly differ across emotional states.

Anger and joy increase stride length and velocity, while sadness decreases walking speed and cadence.

Gait variability remains consistent across different emotional states.

Abstract

Emotion alters the way humans walk, yet most prior studies have relied on laboratory-based 3D motion capture systems. While accurate, these approaches limit translation to real-world settings and have largely focused on spatiotemporal parameters and joint motions. This study evaluated the feasibility of using inertial measurement units (IMUs) to detect emotion-related changes in gait variability as well as spatiotemporal gait parameters. Fourteen healthy young adults completed overground gait trials while wearing two ankle-mounted IMUs. Five target emotions, anger, sadness, neutral emotion, joy, and fear, were elicited using an autobiographical memory paradigm. The IMUs measured stride length, stride time, stride velocity, cadence, and gait variability. The results showed that stride length, stride time, stride velocity, and cadence significantly differed across emotions. Anger and joy were associated with longer strides and faster velocities, while sadness produced slower walking with longer stride times and reduced cadence. Interestingly, gait variability did not differ significantly across emotional states. These findings demonstrate that IMUs can capture emotion specific gait changes previously documented with motion capture, supporting their feasibility for use in natural and clinical contexts. This work advances understanding of how emotions shape gait and highlights the potential of wearable technology for unobtrusive emotion and mobility research.

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