期刊
JOURNAL OF QUALITY TECHNOLOGY
卷 53, 期 1, 页码 47-71出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/00224065.2019.1640097
关键词
clustering; internet of people; median filter; nonparametric multivariate inference; signal processing
By studying fatigue-related questions and analyzing sensor data using various methods, we can gain a deeper understanding of fatigue development and discover differences in gait patterns and fatigue ratings among different individuals.
The goal of this case study is to answer four research questions related to fatigue through features derived from wearable sensors to measure patterns in steps: (1) How do important gait parameters change over time? (2) How do these sensor-based changes relate to the participant's subjective fatigue ratings over time? (3) Are there consistent patterns in performance across different individuals over time? and (4) Do these patterns vary systematically based on specific demographic characteristics? To answer these questions, we have combined multivariate changepoint methods with hierarchical time-series clustering and exploratory data analysis. The results improve our understanding of fatigue development.
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