Plantar Pressure and TCA Dataset for Valgus and Rectus Rearfoot Classification

Dataset Description The dataset titled "Plantar Pressure and TCA Dataset for Valgus and Rectus Rearfoot Classification" consists of 100 CSV files that present plantar pressure measurements obtained using a 32 × 32 FSR sensor matrix. These measurements were collected from 100 participants based on the categorizations of their left and right rearfoot types (specifically rectus or valgus). This categorization was determined through the angular measurement of the Tibial-Calcaneal Angle (TCA) utilizing an anthropometric vision system. The plantar pressure data collected from the 32 × 32 FSR sensor matrix are utilized to train a convolutional neural network (CNN), allowing for the classification of the rearfoot alignment as either rectus or valgus, based on the distribution of plantar pressures. Additionally, the dataset contains 128 × 128 plantar pressure matrices generated through sequential bicubic interpolation. The components of the dataset are outlined below for enhanced clarity and usability: Dataset: “2. FSR_DATASET_FV.zip” . The compressed folder “2. FSR_DATASET_FV.zip” contains 100 CSV files, each formatted as follows: Row 1, Column B (Cell B1): Contains the identifier MAP__date DD_MM_YYYY__time HH_MM_SS (12-hour format). Row 2, Column A (Cell A2): Includes the TCA measurement (in degrees °) for the left rearfoot, obtained through the anthropometric vision system. Row 2, Column B (Cell B2): Contains the label associated with the TCA measurement (either Rectus or Valgus) for the left rearfoot. Row 2, Column C (Cell C2): Displays the TCA measurement (in degrees °) for the right rearfoot, obtained through the anthropometric vision system. Row 2, Column D (Cell D2): Provides the corresponding label for the TCA measurement (Rectus or Valgus) for the right rearfoot. Row 3, Column A (Cell A3): Indicates “INTERPOLATIONS,” showing that the subsequent rows contain interpolated plantar pressure data. Rows 4–131, Columns A–DX (Cells A4:DX131): Contain 128 × 128 plantar pressure data generated through sequential bicubic interpolation, totaling 16,384 data points. Row 132, Column A (Cell A132): Indicates "MEASUREMENTS," showing that the following rows pertain to raw pressure measurements. Rows 133–164, Columns A–AF (Cells A133:AF164): Contain raw plantar pressure data collected from the 32 × 32 FSR sensor matrix, containing 1,024 pressure values. These values are utilized for the training of a CNN for rearfoot classification as Rectus or Valgus. In order to illustrate the results achieved, the following material has been included: Video: “1. P1_CTA.mp4”: This video shows the process of measuring plantar pressures and TCA. The left frontal panel displays real-time TCA measurements as the participant enters the scene and conducts the TCA mesurements utilizing centroid detection of four blue landmarks for each rearfoot. Indicators for both feet present real-time TCA angular measurements and their respective categorizations. In this instance, the participant is identified as exhibiting a left valgus rearfoot (TCA ≈ 13.8°) and a right valgus rearfoot (TCA ≈ 12.6°). Concurrently, on the right frontal panel an intensity map illustrates the plantar pressure through sequential bicubic interpolation, revealing variations in plantar pressure across foot regions based on posture. Video: “3. P2_CTA.mp4”: This video shows the process of measuring plantar pressures and TCA. The left frontal panel displays real-time TCA measurements as the participant enters the scene and conducts the TCA measurement utilizing centroid detection of blue landmarks. Indicators for both feet present real-time TCA angular measurements and their respective categorizations. In this instance, the participant is identified as exhibiting a left rectus rearfoot (TCA ≈ 0.6°) and a right valgus rearfoot (TCA ≈ 7.1°). Concurrently, on the right frontal panel an intensity map illustrates the plantar pressure through sequential bicubic interpolation, revealing variations in plantar pressure across foot regions based on posture. Video: “4. P1_VV.mp4”: This video illustrates the intensity map and the classification results generated by the CNN, featuring real-time indicators for each rearfoot. The participant stands on the FSR sensor matrix while sequential bicubic interpolation is applied and visualized through the intensity map. In this instance, the participant is classified as presenting left valgus rearfoot and right valgus rearfoot. Video: “5. P2_RV.mp4”: This video illustrates the intensity map and the classification results generated by the CNN, featuring real-time indicators for each rearfoot. The participant stands on the FSR sensor matrix while sequential bicubic interpolation is applied and visualized through the intensity map. In this instance, the participant is classified as having left rectus rearfoot and right valgus rearfoot. Image: “6. MEASUREMENTS_32x32.png”: This image visualizes an intensity map representing the plantar pressures applied to the 32 × 32 FSR sensor matrix. The accompanying color intensity bar labeled “Amplitude” corresponds to a pressure range from 0 kg to 1.7 kg. Image: “7. BICUBIC INTERP_128x128.png”: This image presents an intensity map visualizing the 128 × 128 plantar pressure data generated from sequential bicubic interpolation, with the “Amplitude” color bar indicating a pressure range from 0 kg to 1.7 kg. Image: “8. CTA_LANDMARKS.png”: This image illustrates a posterior view of the feet used for TCA measurements through the anthropometric vision system, based on centroid detection on four blue landmarks positionated from bottom to top for each leg: Lower part of the calcaneal tuberosity, upper part of the calcaneal tuberosity, the Achilles tendon and the middle part of the tibia. Users of this database are encouraged to cite the following manuscript: Rodríguez-Quiñonez, J. C., Ortiz-Villaseñor, D., Trujillo-Hernández, G., Ontiveros-Reyes, E., Sanchez-Castro, J. J., Hernández-Balbuena, D., Flores-Fuentes, W., Castro-Toscano, M. J., & González-Uribe, L. A. (2025). Method and system for the classification of tibial‐calcaneal angle using FSR sensors and convolutional neural networks. IET Image Processing, 19(1). https://doi.org/10.1049/ipr2.70244