dc.contributor.author | Sczuka, Kim | |
dc.contributor.author | Schneider, Marc | |
dc.contributor.author | Bourke, Alan | |
dc.contributor.author | Mellone, Sabato | |
dc.contributor.author | Kerse, Ngaire | |
dc.contributor.author | Helbostad, Jorunn L. | |
dc.contributor.author | Becker, Clemens | |
dc.contributor.author | Klenk, Jochen | |
dc.date.accessioned | 2022-10-17T11:50:22Z | |
dc.date.available | 2022-10-17T11:50:22Z | |
dc.date.created | 2021-09-07T14:27:33Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Sensors. 2021, 21 (8), 1-13. | en_US |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | https://hdl.handle.net/11250/3026395 | |
dc.description.abstract | 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. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | MDPI | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Template-Based Recognition of Human Locomotion in IMU Sensor Data Using Dynamic Time Warping | en_US |
dc.title.alternative | Template-Based Recognition of Human Locomotion in IMU Sensor Data Using Dynamic Time Warping | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.pagenumber | 1-13 | en_US |
dc.source.volume | 21 | en_US |
dc.source.journal | Sensors | en_US |
dc.source.issue | 8 | en_US |
dc.identifier.doi | 10.3390/s21082601 | |
dc.identifier.cristin | 1932099 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |