Proof-of-Concept Evaluation of a Sock-Based Plantar Strain Sensing System for Diabetic Foot Monitoring.

Authors

Rory P Turnbull, Rachel Mason, Francesca Sairally, Jenny Corser, Giorgio Orlando, Prabhuraj D Venkatraman, Irantzu Yoldi, Katherine Bradbury, Neil D Reeves, Peter Culmer

Published in

Sensors (Basel, Switzerland). Volume 26. Issue 20. Oct 17, 2026. Epub Oct 17, 2026.

Abstract

Diabetic Foot Ulcers (DFUs) pose a serious health risk to people with diabetes, with a high risk of recurrence following the first DFU and a risk of foot amputation or death. It greatly impacts patient quality of life and costs the NHS up to 0.7% of its annual budget. Over the last 20 years, work has highlighted the link between DFU formation and normal forces. More recently, work has highlighted the importance of strain/shear forces, which are inherently coupled with normal forces. While limited lab-based in-shoe systems have been produced to detect shear, they alter the shoe-foot interface and are not commercially available. Additionally, consultation with people with diabetes highlighted that they may not wear shoes around the house, leaving long periods where in-shoe solutions cannot track forces. We, therefore, present the development of a novel plantar shear measuring system, the Shear Tracking for Enhanced Prevention Sock (STEPS), an instrumented garment to provide an accessible tool for people at risk of DFUs. Integrating sensors within the sock provides a solution that seamlessly integrates within the foot-shoe environment, is suitable for shoeless use, and helps mitigate adherence issues. A prototype STEPS was produced, successfully integrating printed resistive strain sensors (proxy for shear) within custom-designed socks with flexible connectivity to a welt-mounted data acquisition unit. Proof-of-concept testing characterised the system's ability to measure plantar strain. A single-participant pilot study demonstrated that STEPS captures repeatable, gait-synchronised strain signals during walking, with a stationary noise floor below 10% of the typical per-cycle resistance response and between-repeat correlations of R = 0.41 and 0.78 for Sensor 1 and 2 respectively, supporting its potential to detect strain (as proxy for shear) during daily activity.

PMID:
42944460
Bibliographic data and abstract were imported from PubMed on 27 Oct 2026.

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