On the Functional and Extra-Functional Properties of IMU Fusion Algorithms for Body-Worn Smart Sensors
2. Related Work
3. Background and Methods
3.1. Used Algorithms
- Complementary Filter
- Mahony Filter
- Madgwick filter
- Kalman Filter
3.2. Quaternion Representation
3.3. Data Formats
3.3.1. Single Precision Floating-Point
3.3.2. Fixed-Point Numbers
3.4. Used Hardware
- The SAM D20 contains a single cycle hardware multiplier for 32-bit integer numbers, which means that addition and multiplication take the same time.
- The SAM D20 does not have hardware support for floating-point numbers. All floating-point operations have to be emulated in software resulting in higher execution time and power consumption.
3.5. Analysis of Extra-Functional Properties
3.5.1. Code Size
3.5.2. Computational Effort
3.6. Analysis of Functional Properties
Filter and Measurement Parameters
3.7. Statistical Analysis
4. Results: Extra-Functional Properties
4.1. Code Size
Explanation of the Size Differences
4.2. Execution Time
4.3. Summary for the Extra-Functional Properties
5. Results: Functional Properties
5.1. General Comparison of the Fusion Results
5.1.1. Quantization Errors
5.2. Statistical Analysis
5.2.1. Results Grouped by Data Format
5.2.2. Results Grouped by Movement Speed
5.3. Analysis of External Influences
5.3.1. Movement Speed
5.3.2. User Interaction
5.3.3. Other Factors
- Precision of the image analysis. This factor is influenced by the resolution of the camera, the frame rate of the camera, and the precision of the used image analysis algorithm.
- Cross correlation of the data from reference and sensor fusion. When the timestamps of the data do not fit precisely, there will be an error added to the whole measurement.
Conflicts of Interest
|AHRS||Attitude and Heading Reference System|
|BLE||Bluetooth Low Energy|
|IMU||Inertial Measurement Unit|
|SiP||System in Package|
|ROM||Read Only Memory|
|SRAM||Static Random-Access Memory|
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|32-bit Floating-Point||3.963 ms||1.142 ms||0.758 ms||0.782 ms|
|32-bit Fixed-Point||1.923 ms||0.560 ms||0.350 ms||0.382 ms|
|16-bit Fixed-Point||0.621 ms||0.166 ms||0.121 ms||0.123 ms|
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Büscher, N.; Gis, D.; Kühn, V.; Haubelt, C. On the Functional and Extra-Functional Properties of IMU Fusion Algorithms for Body-Worn Smart Sensors. Sensors 2021, 21, 2747. https://doi.org/10.3390/s21082747
Büscher N, Gis D, Kühn V, Haubelt C. On the Functional and Extra-Functional Properties of IMU Fusion Algorithms for Body-Worn Smart Sensors. Sensors. 2021; 21(8):2747. https://doi.org/10.3390/s21082747Chicago/Turabian Style
Büscher, Nils, Daniel Gis, Volker Kühn, and Christian Haubelt. 2021. "On the Functional and Extra-Functional Properties of IMU Fusion Algorithms for Body-Worn Smart Sensors" Sensors 21, no. 8: 2747. https://doi.org/10.3390/s21082747