Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion
Coaches and athletes are constantly seeking novel training methodologies in an attempt to improve athletic performance. This paper proposes a method of rowing sport capture and analysis based on Inertial Measurement Units (IMUs). A canoeist’s motion was collected by multiple miniature inertial senso...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-04-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/7/2110 |
| _version_ | 1797571097946750976 |
|---|---|
| author | Long Liu Sen Qiu ZheLong Wang Jie Li JiaXin Wang |
| author_facet | Long Liu Sen Qiu ZheLong Wang Jie Li JiaXin Wang |
| author_sort | Long Liu |
| collection | DOAJ |
| description | Coaches and athletes are constantly seeking novel training methodologies in an attempt to improve athletic performance. This paper proposes a method of rowing sport capture and analysis based on Inertial Measurement Units (IMUs). A canoeist’s motion was collected by multiple miniature inertial sensor nodes. The gradient descent method was used to fuse data and obtain the canoeist’s attitude information after sensor calibration, and then the motions of canoeist’s actions were reconstructed. Stroke quality was performed based on the estimated joint angles. Machine learning algorithm was used as the classification method to divide the stroke cycle into different phases, including propulsion-phase and recovery-phase, a quantitative kinematic analysis was carried out. Experiments conducted in this paper demonstrated that our method possesses the capacity to reveal the similarities and differences between novice and coach, the whole process of canoeist’s motions can be analyzed with satisfactory accuracy validated by videography method. It can provide quantitative data for coaches or athletes, which can be used to improve the skills of rowers. |
| first_indexed | 2024-03-10T20:35:40Z |
| format | Article |
| id | doaj.art-3f267d9d1b4d4aeaadabe264326d4a0e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T20:35:40Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-3f267d9d1b4d4aeaadabe264326d4a0e2023-11-19T21:03:39ZengMDPI AGSensors1424-82202020-04-01207211010.3390/s20072110Canoeing Motion Tracking and Analysis via Multi-Sensors FusionLong Liu0Sen Qiu1ZheLong Wang2Jie Li3JiaXin Wang4The Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, ChinaThe Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, ChinaThe Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, ChinaThe Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, ChinaThe Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, ChinaCoaches and athletes are constantly seeking novel training methodologies in an attempt to improve athletic performance. This paper proposes a method of rowing sport capture and analysis based on Inertial Measurement Units (IMUs). A canoeist’s motion was collected by multiple miniature inertial sensor nodes. The gradient descent method was used to fuse data and obtain the canoeist’s attitude information after sensor calibration, and then the motions of canoeist’s actions were reconstructed. Stroke quality was performed based on the estimated joint angles. Machine learning algorithm was used as the classification method to divide the stroke cycle into different phases, including propulsion-phase and recovery-phase, a quantitative kinematic analysis was carried out. Experiments conducted in this paper demonstrated that our method possesses the capacity to reveal the similarities and differences between novice and coach, the whole process of canoeist’s motions can be analyzed with satisfactory accuracy validated by videography method. It can provide quantitative data for coaches or athletes, which can be used to improve the skills of rowers.https://www.mdpi.com/1424-8220/20/7/2110rowing sportmotion reconstructioninertial sensordata fusion |
| spellingShingle | Long Liu Sen Qiu ZheLong Wang Jie Li JiaXin Wang Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion Sensors rowing sport motion reconstruction inertial sensor data fusion |
| title | Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion |
| title_full | Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion |
| title_fullStr | Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion |
| title_full_unstemmed | Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion |
| title_short | Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion |
| title_sort | canoeing motion tracking and analysis via multi sensors fusion |
| topic | rowing sport motion reconstruction inertial sensor data fusion |
| url | https://www.mdpi.com/1424-8220/20/7/2110 |
| work_keys_str_mv | AT longliu canoeingmotiontrackingandanalysisviamultisensorsfusion AT senqiu canoeingmotiontrackingandanalysisviamultisensorsfusion AT zhelongwang canoeingmotiontrackingandanalysisviamultisensorsfusion AT jieli canoeingmotiontrackingandanalysisviamultisensorsfusion AT jiaxinwang canoeingmotiontrackingandanalysisviamultisensorsfusion |