DESCRIPTION:
This dataset contains experimental measurements obtained using a flexible hexagonal force-sensing resistor (FSR) matrix developed for distributed pressure sensing and spatial pressure distribution mapping. The dataset is intended to support the evaluation of sensor response repeatability, measurement variability, and spatial response characteristics under different loading conditions.
Two experimental datasets are provided, corresponding to two loading scenarios:
- Scenario 1 - Multipoint Loading (s1_dataset.csv): measurements acquired under simultaneous multi-point loading (points: R1C1, R2C2, R1C3 - see Fig. C). The dataset contains three measurement matrices identified by the FSR column, with sample indices ranging from 1 to 1000 for each matrix.
- Scenario 2 - Sequential Loading (s2_dataset.csv): measurements acquired during sequential excitation of different sensing locations. The dataset contains three measurement matrices identified by the FSR column, with sample indices ranging from 1 to 3000 for each matrix.
Both files share the same general data structure, allowing the sensor responses recorded under the two loading scenarios to be compared. Each row contains measurement identifiers and response values associated with individual sensing elements arranged in a hexagonal matrix consisting of up to 24 sensing points (Fig. C).
The datasets can be used to investigate the repeatability of the sensing system, variability between sensing points, and spatial relationships between sensor responses. They also provide input data for reconstructing and visualizing spatial pressure distributions.
The hexagonal sensing topology offers an alternative to conventional square sensor arrangements and can be investigated in terms of spatial coverage and the number of sensing elements required for a given sensing area.
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LICENSE:
The data are under Creative Commons License CC BY. It is though recommended to manipulate along with the author to fully understand the outcomes. If you have any questions do not hesitate to contact: marcin.bialek@put.poznan.pl
For further information about the experimental setup, measurement methodology, data processing, and interpretation of the results, please refer to the associated scientific publication.
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FILES:
s1_dataset.csv – measurement data obtained during Scenario 1 (Multipoint Loading), containing sample indices from 1 to 1000 for each of the three FSR groups.
s2_dataset.csv – measurement data obtained during Scenario 2 (Sequential Loading), containing sample indices from 1 to 3000 for each of the three FSR groups.
Both files contain measurement identifiers and sensor response values recorded by the individual sensing elements of the matrix.
For proper interpretation, please refer to the sensor layout (Fig. C) and experimental procedure with additional figures provided in the associated scientific publication.
COLUMNS IN s1_dataset.csv AND s2_dataset.csv:
FSR [-] – identifier of the prototype matrix. The dataset contains three distinct values: 1, 2, and 3.
sample [-] – sample index within each FSR matrix, ranging from 1 to 1000 in Scenario 1 (Multipoint Loading) and from 1 to 3000 in Scenario 2 (Sequential Loading).
R0C0–R3C5 [-] – raw analog-to-digital converter (ADC) readings recorded from the individual sensing elements of the hexagonal FSR matrix. The row and column indices identify the nominal positions of the sensing elements within the matrix (Fig. C). The values are dimensionless digital readings and have not been converted into calibrated pressure values.
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DATA INTERPRETATION NOTES:
The sensor response values provided in the datasets are raw ADC readings rather than calibrated pressure measurements. Consequently, they should not be interpreted directly as physical pressure values. Conversion to pressure requires an appropriate calibration procedure.
The raw readings can be used to evaluate sensor response repeatability, compare responses between sensing elements, and reconstruct relative spatial response distributions. Pressure distribution maps generated from these readings should be interpreted as visualizations of the spatial distribution of the recorded sensor response unless the data have first been converted into calibrated pressure values.
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The "Related Publication" section will be updated upon completion of the article publishing process.
