Monitoring plantar foot temperatures is essential for assessing foot health, particularly in individuals with diabetes at increased risk of complications. Traditional thermographic imaging measures foot temperatures in unshod individuals lying down, which may not reflect thermal characteristics of feet in shod, active, real-world conditions. These controlled settings limit understanding of dynamic foot temperatures during daily activities. Recent advancements in wearable technology, such as insole-based sensors, overcome these limitations by enabling continuous temperature monitoring. This study leverages a data-driven clustering approach, independent of pre-selected foot regions or models like the angiosome concept, to explore normative thermal patterns in shod feet with insole-based sensors. Data were collected from 27 healthy participants using insoles embedded with 21 temperature sensors. The data were analysed using clustering algorithms, including k-means, fuzzy c-means, OPTICS, and hierarchical clustering. The clustering algorithms showed a high degree of similarity, with variations primarily influenced by clustering granularity. Six primary thermal patterns were identified, with the “butterfly pattern” (elevated medial arch temperatures) predominant, representing 51.5% of the dataset, aligning with findings in thermographic studies. Other patterns, like the “medial arch + metatarsal area” pattern, were also observed, highlighting diverse yet consistent thermal distributions. This study shows that while normative thermal patterns observed in thermographic imaging are reflected in insole data, the temperature distribution within the shoe may better represent foot behaviour during everyday activities, particularly when enclosed in a shoe. Unlike thermal imaging, the proposed in-shoe system offers the potential to capture dynamic thermal variations during ambulatory activities, enabling richer insights into foot health in real-world conditions.

Several musicians suffer from musculoskeletal problems during their career. These injuries are referred to as performance-related musculoskeletal disorders (PRMDs). Through the use of exercise programs, PRMDs can be prevented. Exercise programs aim to strengthen musicians' upper limbs and supporting muscles, which can correct and improve postural control during performance and thereby prevent PRMDs. In this study, a musician-specific exercise program was carried out by guitarists. Thermal imaging was used to observe and monitor the effect of the program. Thermal data was collected from 14 guitarists who played their instrument for at least 7 hours a week. Data was gathered from the trapezius, shoulder, upper arm, forearm, wrist, and digits for a period of 20 minutes whilst the guitarists were playing. The participants followed the exercise program throughout a period of 6 weeks, after which the process of thermal data collection was performed again. While existing studies that evaluate musicians through thermal imaging mostly observe thermal asymmetries, in this work we also looked at absolute and relative temperature changes over time, both before and after the exercise program. The results show that one of the main and most consistent effects of the musician-specific exercise program was the reduction of thermal asymmetries within the shoulder region. This is indicative that the musician-specific exercise might be beneficial to avoid or reduce the effect of PRMDs in guitarists. Keywords: infrared thermography, musculoskeletal, instrumentalist, guitarists, thermal patterns, exercise program

This study aimed to establish normative in-shoe plantar foot temperature patterns across three static postures—lying, sitting, and standing—in healthy individuals, providing a clinically relevant baseline for interpreting in-shoe thermograms in diabetic or peripheral arterial disease (PAD) populations. A single-center prospective study included 20 healthy adults (40 limbs; 22–74 years) who underwent vascular and neurological screening prior to data collection. Plantar temperature was continuously recorded using Tarsos^® Smart Insoles with 21 embedded sensors per foot during three consecutive 10 min phases: supine, sitting, and standing. Data were analyzed for regional differences across the toes, metatarsals, arch, and heel using statistical and visual methods. Distinct posture-related temperature patterns were observed. The arch consistently exhibited the highest temperatures, while the toes remained cooler across all phases. Supine positioning resulted in relatively uniform temperature increases, whereas sitting and standing demonstrated more-stable but region-specific patterns, with slower rates of temperature change and more pronounced regional variation. Compared with barefoot thermography, the in-shoe condition showed greater heat retention and reduced evaporative cooling, highlighting the importance of context-specific baseline data. These findings demonstrate the influence of posture on plantar thermal distribution in the in-shoe environment and support the use of embedded monitoring systems for continuous assessment where surface thermography is not feasible.