Two-Step k-means Clustering Based Information Entropy for Detecting Environmental Barriers Using Wearable Sensor
Bibliographic Data
| ID | 15500554 |
|---|---|
| Authors | Bogyeong Lee (0000-0002-6620-7851, Dankook University), Hyunsoo Kim (0000-0002-9892-1080, Dankook University, corresponding author) |
| Year | 2022 |
| Volume | 19 |
| Issue | 2 |
| Pages | 704-704 |
| Publication date | 2022-01-08 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph19020704 |
| PMID | 35055526 |
| OpenAlex | W4205755812 |
| Language | EN |
| Citations received | 2 |
| References cited | 10 |
Walking is the most basic means of transportation. Therefore, continuous management of the walking environment is very important. In particular, the identification of environmental barriers that can impede walkability is the first step in improving the pedestrian experience. Current practices for identifying environmental barriers (e.g., expert investigation and survey) are time-consuming and require additional human resources. Hence, we have developed a method to identify environmental barriers based on information entropy considering that every individual behaves differently in the presence of external stimuli. The behavioral data of the gait process were recorded for 64 participants using a wearable sensor. Additionally, the data were classified into seven gait types using two-step k -means clustering. It was observed that the classified gaits create a probability distribution for each location to calculate information entropy. The values of calculated information entropy showed a high correlation in the presence or absence of environmental barriers. The results obtained facilitated the continuous monitoring of environmental barriers generated in a walking environment
Cluster analysis · Data mining · Entropy (arrow of time · Machine learning · Pedestrian · Transport engineering · Wearable computer · Advanced Chemical Sensor Technologies · Computer Science · Engineering · Human Mobility and Location-Based Analysis · Wildlife-Road Interactions and Conservation
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| Citations per year | 2 |
|---|---|
| Citation span | 2025 - 2026 (2) |
| Highly cited | No |