Name
Title | ||
|---|---|---|
A Study on High Accuracy Stride Estimation on Smartphone Combining Acceleration Sensor and Gyro Sensor. |
Abstract | ||
|---|---|---|
The stride is an important parameter in human motion analysis and has been extensively studied by many researchers. This paper focuses on smartphones that are popular in the world, regardless of the measurement environment. In previous research, the stride estimation using the acceleration sensor or the gyro sensor mounted on the smartphone had been studied. However, the stride estimation accuracy has an error rate of about over 10 %. In this paper, we propose a highly accurate stride estimation method using stride correction parameter obtained from cross section movement in addition to conventional sagittal surface stride using acceleration sensor and gyro sensor mounted on a smartphone. Based on the testing results, the error rate of our proposed method with the stride estimated by the Kinect sensor (RGB-D sensor) as the true value was about 6%. It makes possible to estimate the stride with high accuracy. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.2991/jrnal.2018.5.2.2 | JOURNAL OF ROBOTICS NETWORKING AND ARTIFICIAL LIFE |
Keywords | Field | DocType |
Locomotive Syndrome,Acceleration sensor,Gyro Sensor,Stride Estimation Method,Smartphone | STRIDE,Simulation,Computer science,Acceleration | Journal |
Volume | Issue | ISSN |
5 | 2 | 2352-6386 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hiroki Tamura | 1 | 72 | 21.29 |
| Keiki Sakurai | 2 | 0 | 0.34 |
| Koichi Tanno | 3 | 57 | 22.05 |