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<p>Emotional state is correlated with walking information such as walking speed; monitoring emotional states and walking information is useful for employee health management as a countermeasure against depression. We combined daily subjective mood assessments with daily objective gait data to monitor particularly anxious mood states among 60 healthy employees. To this end, we developed a smartphone app, named KOKORO scale, which allows participants to record their emotional states instantaneously, generating time-series data that can be analyzed to show changes in emotional states over time. We used the KOKORO scale in combination with a daily walking speed app, which measured gait information in daily life settings using a global positioning system. We conducted the test during workdays over a four-week period. The apps were used to obtain the mean walking speed and mean ease–anxiety scores. The correlation between the mean anxiety score and walking speed revealed remarkable regressivity (p ≦ 0.01) between the mean walking speed and the overall mean ease of mind for participants before starting work. The results demonstrated that measuring subjective mood in combination with objective gait information improved mood measurement objectivity. This system has potential for identifying or predicting risk of depressive mood when combined with walking parameter analysis.</p>

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Using smartphone apps to compare characteristics of subjective ease/anxiety and daily walking in healthy employees

  • 期刊论文

  • 发表日期：

    2025年2月10日

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  • Shuichi Tsuchiya,
  • Takeshi Koizumi,
  • Koji Yamamoto,
  • Mamoru Misono,
  • Yosky Kataoka

摘要

Emotional state is correlated with walking information such as walking speed; monitoring emotional states and walking information is useful for employee health management as a countermeasure against depression. We combined daily subjective mood assessments with daily objective gait data to monitor particularly anxious mood states among 60 healthy employees. To this end, we developed a smartphone app, named KOKORO scale, which allows participants to record their emotional states instantaneously, generating time-series data that can be analyzed to show changes in emotional states over time. We used the KOKORO scale in combination with a daily walking speed app, which measured gait information in daily life settings using a global positioning system. We conducted the test during workdays over a four-week period. The apps were used to obtain the mean walking speed and mean ease–anxiety scores. The correlation between the mean anxiety score and walking speed revealed remarkable regressivity (p ≦ 0.01) between the mean walking speed and the overall mean ease of mind for participants before starting work. The results demonstrated that measuring subjective mood in combination with objective gait information improved mood measurement objectivity. This system has potential for identifying or predicting risk of depressive mood when combined with walking parameter analysis.