Statistical analysis and improvement of the repeatability and reproducibility of an evaluation method for IMUs on a smartphone

Büscher, Nils; Middendorf, Lars; Haubelt, Christian; Dorsch, Rainer G.; Wegelin, F.

doi:10.1145/2933242.2933255

Cited by 2 publications

(3 citation statements)

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“…Another possible factor is the interaction with the human who conducted the measurements. The used measurement method from [ 31 ] uses a graphical user interface to instruct the probationer on what movements have to be done and displays in real time how well the probationer follows these movements. This should ensure that the measurements all depict the same movements to be comparable.…”

Section: Results: Functional Propertiesmentioning

confidence: 99%

“…The evaluation of the quality of the output of the four orientation filters was done using an external reference as ground truth against which the result of the sensor fusion was compared. The external reference was gathered using the method described in [ 30 , 31 ]. Said method records a pattern via a camera and uses the captured images to calculate the relative orientation between camera and pattern via image analysis using the OpenCV library [ 32 ].…”

Section: Background and Methodsmentioning

confidence: 99%

“…Said method records a pattern via a camera and uses the captured images to calculate the relative orientation between camera and pattern via image analysis using the OpenCV library [ 32 ]. A smartphone with a user interface was used to instruct the user about the desired movement and record the pattern similar to [ 31 ]. For the investigation, the smart sensor was rigidly attached to the pattern and was then moved in front of the static camera, which recorded the pattern during the measurement.…”

Section: Background and Methodsmentioning

confidence: 99%

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On the Functional and Extra-Functional Properties of IMU Fusion Algorithms for Body-Worn Smart Sensors

Büscher

Gis

Kühn

et al. 2021

Sensors

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In this work, four sensor fusion algorithms for inertial measurement unit data to determine the orientation of a device are assessed regarding their usability in a hardware restricted environment such as body-worn sensor nodes. The assessment is done for both the functional and the extra-functional properties in the context of human operated devices. The four algorithms are implemented in three data formats: 32-bit floating-point, 32-bit fixed-point and 16-bit fixed-point and compared regarding code size, computational effort, and fusion quality. Code size and computational effort are evaluated on an ARM Cortex M0+. For the assessment of the functional properties, the sensor fusion output is compared to a camera generated reference and analyzed in an extensive statistical analysis to determine how data format, algorithm, and human interaction influence the quality of the sensor fusion. Our experiments show that using fixed-point arithmetic can significantly decrease the computational complexity while still maintaining a high fusion quality and all four algorithms are applicable for applications with human interaction.

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Section: Results: Functional Propertiesmentioning

confidence: 99%

Section: Background and Methodsmentioning

confidence: 99%

Section: Background and Methodsmentioning

confidence: 99%

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