Stroke Patients’ Balance Ability Test Dataset Utilizing Array Pressure Acquisition System

The dataset includes raw pressure data and heatmap images, which support quantitative analysis and visualization of pressure patterns. Raw pressure data are stored in .csv files, which include pressure data presented in hexadecimal format, whereas the heatmap data are saved as .png files. All data are arranged into corresponding subdirectories based on five experimental movements: sit-to-stand, in-place stepping, static balance with eyes open, static balance with eyes closed, and stepping on a soft mat with eyes closed.
Each participant's data is stored separately in a folder. For example, the folder "3_RawData" contains the data for Participant 3. Inside the "3_RawData" folder, there are two subfolders: "3_PressureData" and "3_HeatmapData," which hold the raw pressure data and the generated heatmap data, respectively. Each subdirectory contains multiple .csv files and .png files that represent specific experimental records.
Relevant participant information is included in the "Participant_Information.csv" file, including age, height, weight, gender, health status (whether they are stroke patients), and balance ability levels. All participants' private information related to the test has been fully de-identified, and the recorded dataset in this study has obtained the participants' informed consent and authorization for publication.
Each pressure data frame includes a frame header, frame type, length, packet type, data field, and checksum. The frame header data type is uint16_t, with a specific value of 0xA55A. The frame type data type is uint8_t, with a particular value of 0x01. The length of the data type is uint16_t, with a particular value equal to the size of the packet minus 2. The packet type data type is uint8_t, with a particular value of 0x01.
Researchers can process raw pressure data to generate the heatmaps they need. For the plantar pressure sensor data, after removing the frame header, frame type, length, packet type, and checksum from a raw pressure data frame. Tthe remaining data is the pressure data in the data field. This pressure data from one data field is then converted into a 32×64 data matrix for analysis.For the flexible seat cushion pressure sensor data, similarly, after removing the frame header, frame type, length, packet type, and checksum from a frame of raw pressure data, the remaining data is the pressure data in the data field. This pressure data from one data field is adjusted into a 16×16 data matrix, which can then be analysed.