Current and Expected Trends for the Marine Chitin/Chitosan and Collagen Value Chains.

Chitin/chitosan and collagen are two of the most important bioactive compounds, with applications in the pharmaceutical, veterinary, nutraceutical, cosmetic, biomaterials, and other industries. When extracted from non-edible parts of fish and shellfish, by-catches, and invasive species, their use contributes to a more sustainable and circular economy. The present article reviews the scientific knowledge and publication trends along the marine chitin/chitosan and collagen value chains and assesses how researchers, industry players, and end-users can bridge the gap between scientific understanding and industrial applications. Overall, research on chitin/chitosan remains focused on the compound itself rather than its market applications. Still, chitin/chitosan use is expected to increase in food and biomedical applications, while that of collagen is expected to increase in biomedical, cosmetic, pharmaceutical, and nutritional applications. Sustainable practices, such as the reuse of waste materials, contribute to strengthen both value chains; the identified weaknesses include the lack of studies considering market trends, social sustainability, and profitability, as well as insufficient examination of intellectual property rights. Government regulations, market demand, consumer preferences, technological advancements, environmental challenges, and legal frameworks play significant roles in shaping both value chains. Addressing these factors is crucial for seizing opportunities, fostering sustainability, complying with regulations, and maintaining competitiveness in these constantly evolving value chains.

Remote Photoplethysmographic Assessment of the Peripheral Circulation in Critical Care Patients Recovering From Cardiac Surgery.

PURPOSE: Camera-based photoplethysmography (cbPPG) remotely detects the volume pulse of cardiac ejection in the peripheral circulation. The cbPPG signal is sourced from the cutaneous microcirculation, yields a 2-dimensional intensity map, and is therefore an interesting monitoring technique. In this study, we investigated whether cbPPG is in general sufficiently sensitive to discern hemodynamic conditions. METHODS: cbPPG recordings of 70 patients recovering from cardiac surgery were analyzed. Photoplethysmograms were processed offline and the optical pulse power (OPP) of cardiac ejection was calculated. Hemodynamic data, image intensity, and patient movements were recorded synchronously. The effects of hemodynamic parameters and measurement conditions on the patient's individual OPP variability and their actual OPP values were calculated in mixed-effects regression models. RESULTS: Mean arterial pressure (MAP), pulse pressure (PP), heart rate (HR), and central venous pressure (CVP) significantly explained the individual OPP variability. PP had the highest explanatory power (19.9%). Averaged OPP significantly increased with PP and MAP (P < 0.001, respectively) and decreased with higher HR (P = 0.024). CVP had a 2-directional, nonsignificant effect on averaged OPP. Image intensity and patient movements did significantly affect OPP. After adjustment for hemodynamic covariables and measurement conditions, the effect of PP and HR remained unchanged, whereas that of MAP vanished. CONCLUSION: cbPPG is sensitive to hemodynamic parameters in critical care patients. It is a potential application for monitoring the peripheral circulation. Its value in a clinical setting has to be determined.

Assessment of blind source separation techniques for video-based cardiac pulse extraction.

Blind source separation (BSS) aims at separating useful signal content from distortions. In the contactless acquisition of vital signs by means of the camera-based photoplethysmogram (cbPPG), BSS has evolved the most widely used approach to extract the cardiac pulse. Despite its frequent application, there is no consensus about the optimal usage of BSS and its general benefit. This contribution investigates the performance of BSS to enhance the cardiac pulse from cbPPGs in dependency to varying input data characteristics. The BSS input conditions are controlled by an automated spatial preselection routine of regions of interest. Input data of different characteristics (wavelength, dominant frequency, and signal quality) from 18 postoperative cardiovascular patients are processed with standard BSS techniques, namely principal component analysis (PCA) and independent component analysis (ICA). The effect of BSS is assessed by the spectral signal-to-noise ratio (SNR) of the cardiac pulse. The preselection of cbPPGs, appears beneficial providing higher SNR compared to standard cbPPGs. Both, PCA and ICA yielded better outcomes by using monochrome inputs (green wavelength) instead of inputs of different wavelengths. PCA outperforms ICA for more homogeneous input signals. Moreover, for high input SNR, the application of ICA using standard contrast is likely to decrease the SNR.