Abstract / Description of output
This work presents a novel feature extraction technique for human activity recognition using inertial and magnetic sensors. The proposed method estimates the orientation of the person with respect to the earth frame by using quaternion representation. This estimation is performed automatically without any extra information about where the sensor is placed on the body of the person. Furthermore, the method is also robust to displacements of the sensor with respect to the body. This novel feature extraction technique is used to feed a classification algorithm showing excellent results that outperform those obtained by an existing state-of-the-art feature extraction technique.
Original language | English |
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Title of host publication | 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014 |
Publisher | IEEE Computer Society |
Pages | 177-180 |
Number of pages | 4 |
ISBN (Print) | 9781479949755 |
DOIs | |
Publication status | Published - 1 Jan 2014 |
Event | 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014 - Gold Coast, QLD, Australia Duration: 29 Jun 2014 → 2 Jul 2014 |
Conference
Conference | 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014 |
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Country/Territory | Australia |
City | Gold Coast, QLD |
Period | 29/06/14 → 2/07/14 |
Keywords / Materials (for Non-textual outputs)
- Activity Classification
- Ambulatory Monitoring
- Features Extraction
- Inertial Sensors
- Magnetic Sensors
- Orientation Estimation
- Quaternions