Foot Temperature and Diabetic Foot Ulcer Risk: Using the FeetSee Device to Generate a Unique Foot Temperature Dataset.

This is a prospective observational study with a single cohort of approximately 100 adults with type 1 or type 2 diabetes and a recently healed plantar DFU, conducted at hospital sites in the United Kingdom and at Vilnius University Hospital Santaros Klinikos in Lithuania. Eligibility requires peripheral neuropathy (defined by abnormal 10 g monofilament and/or vibration perception threshold testing) and at least one palpable foot pulse. Key exclusions include active DFU, active Charcot neuro-osteoarthropathy, severe peripheral arterial disease (no palpable foot pulses), major lower-limb amputation above the metatarsophalangeal joints, and medical or cognitive conditions that would prevent safe use of the device.

After informed consent and baseline assessments, participants are trained to use the FeetSee thermal camera, stand, and smartphone/tablet app at home. They are asked to remove footwear and socks and keep their feet non-weight-bearing for about 10 minutes before each measurement, then acquire at least one bilateral plantar image per day. Study staff provide intensive technical support during the first week and then schedule telephone check-ins approximately every three weeks, with additional troubleshooting as needed. Adherence is monitored via device-logged usage; failure to use the device for 21 consecutive days is considered loss to follow-up.

Thermal images are pseudo-anonymised and transferred securely to cloud infrastructure, where the FeetSee algorithm uses an active-shape model to detect foot contours and compares mirrored plantar regions for temperature differences above a predefined threshold (e.g.,>2.2 °C), indicative of local inflammation. The analyses performed by the device manufacturer (Diabetis JSC) will use the resulting temperature maps and clinical outcomes to estimate the sensitivity and specificity of the current algorithm for predicting incident DFUs and to develop refined algorithms. All other clinical and questionnaire data are analysed by the academic research team.

Feasibility outcomes include recruitment rate, retention, frequency of device use, and the number and nature of technical support contacts. Acceptance of the technology by both patients and healthcare professionals is assessed with questionnaires based on the Unified Theory of Acceptance and Use of Technology (UTAUT), covering performance expectancy, effort expectancy, social influence, facilitating conditions, self-efficacy, attitudes toward FeetSee, technology anxiety, and perceptions of personal DFU risk. Safety outcomes include the collection and classification of any adverse events and the identification of any device-related problems.