Transdisciplinary collaboration in wound care research

The highly complex disorder of chronic wounds is a significant problem. Information is often lacking, dynamically changing, or contradictory and thus acts to impede the progression of research and its translation into clinical care. Transdisciplinary collaboration may play an important role in chronic wound research, permitting key stakeholders with a single, central goal to take a unified approach towards addressing the problem. While transdisciplinary collaboration is not a new concept, its implementation within chronic wound research is relatively new. This is because the research area is still largely dominated by single-discipline researchers or by multiple disciplines working in isolation. Transdisciplinary research is a transcending approach, requiring a greater level of understanding between disciplines and may represent the next leap forward in wound care research. This approach necessitates a deeper understanding by all team members of the co-disciplines involved; where key stakeholders are better equipped to respond to dynamic changes and problems that arise in chronic wound research. In this paper, we illustrate what a transdisciplinary approach in wound care research may entail, with the ultimate goal of such an undertaking to improve understanding of the complexities of wound care, which could lead to potential benefits in wound management.

The envelope-based cyclic periodogram

Cyclostationary analysis has proven effective in identifying signal components for diagnostic purposes. A key descriptor in this framework is the cyclic power spectrum, traditionally estimated by the averaged cyclic periodogram and the smoothed cyclic periodogram. A lengthy debate about the best estimator finally found a solution in a cornerstone work by Antoni, who proposed a unified form for the two families, thus allowing a detailed statistical study of their properties. Since then, the focus of cyclostationary research has shifted towards algorithms, in terms of computational efficiency and simplicity of implementation. Traditional algorithms have proven computationally inefficient and the sophisticated "cyclostationary" definition of these estimators slowed their spread in the industry. The only attempt to increase the computational efficiency of cyclostationary estimators is represented by the cyclic modulation spectrum. This indicator exploits the relationship between cyclostationarity and envelope analysis. The link with envelope analysis allows a leap in computational efficiency and provides a "way in" for the understanding by industrial engineers. However, the new estimator lies outside the unified form described above and an unbiased version of the indicator has not been proposed. This paper will therefore extend the analysis of envelope-based estimators of the cyclic spectrum, proposing a new approach to include them in the unified form of cyclostationary estimators. This will enable the definition of a new envelope-based algorithm and the detailed analysis of the properties of the cyclic modulation spectrum. The computational efficiency of envelope-based algorithms will be also discussed quantitatively for the first time in comparison with the averaged cyclic periodogram. Finally, the algorithms will be validated with numerical and experimental examples.