## 4 Discussion
### Limitations and Future Research Lines  
Since its initial identification, the diabetic foot has been acknowledged for its intrinsic complexity, which presents a considerable clinical challenge. One of the primary challenges is the clinical heterogeneity among patients, which hinders the ability to generalise clinical decisions. Furthermore, this issue is compounded in the domain of prevention [41]. In recent years, machine learning has emerged as a key tool in the field of personalised medicine [42].  
In the specific context of the diabetic foot, [PERSON] et al. [43] published a recent narrative review to explore the transformative impact of machine learning on managing diabetic foot complications. The authors evaluated the application of machine learning in the analysis of thermographic images, biomarkers and gait biomechanics. The review highlights that the application of infrared thermography could help detect an increase in plantar temperature before the onset of DFUs. The authors show that the distribution of plantar temperature can be heterogeneous, which complicates its quantification and use to predict results. The creation of a comprehensive thermographic image database could facilitate the development of thermographic standards and enhance the comparability of results.  
It is also notable that there is a paucity of research examining the utilisation of machine learning in the analysis of gait biomechanics and its associated outcomes [43]. The integration of thermal imaging with physical activity data has the potential to enhance clinical recommendations and to provide a more extensive database for future telemedicine applications.  
In this way, the identification of studies that relate thermography, pressure and physical activity not only provides useful information for current healthcare practice but also identifies the data sources that are necessary for inclusion in future computer applications.  
It is essential to take into account the constraints of this review when analysing the results. One of the principal limitations is the methodological diversity observed in the design of the studies. A further challenge is the difficulty in identifying potential relevant unpublished research. In conclusion, the majority of the estimated results are based on observational studies, which may be subject to bias. To ascertain the optimal level of physical activity for the management of diabetes without the risk of developing diabetic foot ulcers, longitudinal studies are required. Nevertheless, a detailed analysis of these studies enabled the establishment of relationships with significant implications for clinical practice, which may provide guidance for future research.  
To date, no studies have been identified that examine the relationship between physical activity and the inflammatory response of plantar tissues, as assessed by thermography and pressure distribution, in patients with diabetes. It is thus evident that further research is required in this area in order to predict plantar skin lesions and prevent the development of pressure ulcers (UPD). The current recommendations for the prevention of UPD are based on limiting or eliminating physical activity. It is therefore evident that further research is required in order to explore the potential for a more personalised approach to the prevention of UPD.