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Template-Based Recognition of Human Locomotion in IMU Sensor Data Using Dynamic Time Warping
| Content Provider | MDPI |
|---|---|
| Author | Sczuka, Kim Schneider, Marc Bourke, Alan Mellone, Sabato Kerse, Ngaire Helbostad, Jorunn Becker, Clemens Klenk, Jochen |
| Copyright Year | 2021 |
| Description | Increased levels of light, moderate and vigorous physical activity (PA) are positively associated with health benefits. Therefore, sensor-based human activity recognition can identify different types and levels of PA. In this paper, we propose a two-layer locomotion recognition method using dynamic time warping applied to inertial sensor data. Based on a video-validated dataset (ADAPT), which included inertial sensor data recorded at the lower back (L5 position) during an unsupervised task-based free-living protocol, the recognition algorithm was developed, validated and tested. As a first step, we focused on the identification of locomotion activities walking, ascending and descending stairs. These activities are difficult to differentiate due to a high similarity. The results showed that walking could be recognized with a sensitivity of 88% and a specificity of 89%. Specificity for stair climbing was higher compared to walking, but sensitivity was noticeably decreased. In most cases of misclassification, stair climbing was falsely detected as walking, with only 0.2–5% not assigned to any of the chosen types of locomotion. Our results demonstrate a promising approach to recognize and differentiate human locomotion within a variety of daily activities. |
| Starting Page | 2601 |
| e-ISSN | 14248220 |
| DOI | 10.3390/s21082601 |
| Journal | Sensors |
| Issue Number | 8 |
| Volume Number | 21 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-04-07 |
| Access Restriction | Open |
| Subject Keyword | Sensors Industrial Engineering Transportation Science and Technology Physical Activity Recognition Locomotion Wearable Sensors Dynamic Time Warping |
| Content Type | Text |
| Resource Type | Article |
