1. ABOUT THE DATASET -------------------- Title: Dataset for 'Development of a Body-Worn Textile-Based Strain Sensor: Application to Diabetic Foot Assessment Creator(s): Rory P. Turnbull, Peter Culmer Organisation(s): University of Leeds. Rights-holder(s):Unless otherwise stated, Copyright 2025 University of Leeds Publication Year: 2025 Description: This dataset contain the raw data associated with the development of a silver adheisive based strain sensor. The data contains the output of parametric testing covering the number of turns, sensor length and cure temperature of the strain gauge design, collected through quasi-static testing. The second set out data assess a series of robustness improvement made to the sensor, collected through quasi-static testing and some cyclic loading. The final set of data was used to assess sensor performance. The data takes the form of text files collected from the proposed sensor and csv files from the instron used to conduct testing. Cite as: Turnbull and Culmer (2025): Dataset for 'Development of a Body-Worn Textile-Based Strain Sensor: Application to Diabetic Foot Assessment. University of Leeds. [Dataset] [https://doi.org/10.5518/1649 ] Related publication: Turnbull, R. P.; Corser, J.; Orlando, G.; Venkatraman, P.; Yoldi, I.; Bradbury, K.; Reeves, N. D.; Culmer, P. Development of a Body-Worn Textile-Based Strain Sensor: Application to Diabetic Foot Assessment. Preprints 2025, 2025021321. https://doi.org/10.20944/preprints202502.1321.v1 (Submitted to MDPI Sensors) Contact: r.p.turnbull@leeds.ac.uk 2. TERMS OF USE --------------- Copyright 2025 University of Leeds. Unless otherwise stated, this dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/.] 3. PROJECT AND FUNDING INFORMATION ---------------------------------- Title: Digital Health: 'Socksess' - Smart Sensing Socks For Monitoring Diabetic Feet And Preventing Ulceration. Dates: 07/09/2022 - 30/08/2025 Funding organisation: EPSRC Grant no.: EP/X001059/1 4. CONTENTS ----------- File listing The data follows the linked papers structure and is numbered accordingly. All data is provided except the following sections: Data collected during the "Technology evaluation" section as while decisions were taken based on this data no direct conclusions can be drawns from it. The Quasi static loading regime in Fig. 6 was provided as a visualisation with sufficient information in the paper to reproduce the method. 1 Parametric Investigation (Fig. 7) 1 Number of Turns (3, 5, 7) S1-3 = Sample R1-5 = Repeat 2 Sensor Length (10, 20, 30mm) S1-3 = Sample R1-5 = Repeat 3 Cure temperature (75, 80, 90, 100c) S1-3 = Sample R1-5 = Repeat 2 Robustness improvements (Fig 8.d) 1 Sensor Form 1 Double width R1-5 2 Double height R1-5 3 Quad R1-5 4 Quad extended(Fig. 10) S1 - S5 R1-5 5 Cyclic initial(Fig. 11) S1 6 Cyclic temperature (Fig. 13) 50, 60, 70, 80C R1-5 7 Silicone reinforcement (Fig.15) 00-20, 00-30, 00-50 (number relating to silicone shore hardness) S1-3 R1-5 3 Final system evaluation (Fig. 17 - 19) S1-3 R1-3 5. METHODS ---------- See published paper for information relating to methods. Data Analysis was undertaken in Matlab2024 using the following packages: signal_toolbox statistics_toolbox Other functions used include Yair Altman (2025). export_fig (https://github.com/altmany/export_fig/releases/tag/v3.47), GitHub. Retrieved February 25, 2025. Stephen23 (2025). Natural-Order Filename Sort (https://www.mathworks.com/matlabcentral/fileexchange/47434-natural-order-filename-sort), MATLAB Central File Exchange. Retrieved February 25, 2025.