Haemorheology has been long identified as an early biomarker of a wide range of diseases, especially cardiovascular diseases. This study investigates for the first time the suitability of Photoplethysmography (PPG) as a non-invasive diagnostic method for haemorheological changes. The sensitivity of both PPG components (AC and DC) to changes in haemorheology were rigorously investigated in an in vitro experimental setup that mimics the human circulation. A custom-made reflectance PPG sensor, a pressure transducer and an ultrasonic Doppler flowmeter were used to map changes in flow dynamics and optical responses in an arterial model. The study investigated the effect of shear rates by varying fluid pumping frequencies using 4 set-points and the effect of clot formation using a chemical trigger. Both PPGAC amplitudes and PPGDC levels showed significant (p < 0.001) changes during the increase in shear rates and an immediate change after thromboplastin activation. The findings highlight that PPG has the potential to be used as a simple non-invasive method for the detection of blood characteristics, including disaggregation, radial migration and cross-linking fibrin formations. Such capability will enable the assessment of the effects of clotting-activators and anticoagulants (including non-pharmacological methods) and might aid in the early non-invasive assessment of cardiovascular pathologies.
Noninvasive continuous blood pressure measurements are desirable for patients and clinicians. This work proposes and validates a method for transmural pressure measurement using photoplethysmography (PPG) in an in vitro setup that allows control of pressure and flow conditions. The optimum pulsatile volume measure is obtained by comparing parameters extracted from the photoplethysmographic signal (AC amplitude, normalized pulse volume (NPV) and adjusted pulse volume (APV)). Pulsatile volume can then provide pressure measurements using the exponential pressurevolume (P-V) relationship and validated using the gold standard catheter pressure measurement. Pressure, red (R) and infrared (IR) PPG signals were recorded continuously in two arterial models with different cross-sectional areas (Model 1 and Model 2) utilising a pulsatile pump. Flow rates were controlled by varying pumping frequencies at low and high stroke volumes. The optimum method for estimation of the pulsatile volume is through APV, which had a highly significant correlation (r 2 = 0.99, p < 0.001) for Model 1 and (r 2 = 0.98, p < 0.001) for Model 2. APV obtained a significantly better fit when compared to NPV IR (r 2 = 0.73, z = 25.85, p < 0.001), NPV R (r 2 = 0.95, z = 12.26, p < 0.001), IR AC (r 2 = 0.52, z = 28.29, p < 0.0001) and R AC (r 2 = 0.92, z = 15.27, p < 0.0001) in Model 1, and when compared to NPV IR (r 2 = 0.92, z = 10.23, p < 0.0001), NPV R (r 2 = 0.96, z = 5.08, p < 0.001) IR AC (r 2 = 0.63, z = 22.47, p < 0.0001) and R AC (r 2 = 0.92, z = 17.70, p < 0.0001) in Model 2. These preliminary findings suggest that APV could be used as a potential non-invasive continuous method of blood pressure measurement at different flow conditions.
Problems with fatigue and sleep are highly prevalent in patients with chronic diseases and often rated among the most disabling symptoms, impairing their activities of daily living and the health-related quality of life (HRQoL). Currently, they are evaluated primarily via Patient Reported Outcomes (PROs), which can suffer from recall biases and have limited sensitivity to temporal variations. Objective measurements from wearable sensors allow to reliably quantify disease state, changes in the HRQoL, and evaluate therapeutic outcomes. This work investigates the feasibility of capturing continuous physiological signals from an electrocardiography-based wearable device for remote monitoring of fatigue and sleep and quantifies the relationship of objective digital measures to self-reported fatigue and sleep disturbances. 136 individuals were followed for a total of 1,297 recording days in a longitudinal multi-site study conducted in free-living settings and registered with the German Clinical Trial Registry (DRKS00021693). Participants comprised healthy individuals (N = 39) and patients with neurodegenerative disorders (NDD, N = 31) and immune mediated inflammatory diseases (IMID, N = 66). Objective physiological measures correlated with fatigue and sleep PROs, while demonstrating reasonable signal quality. Furthermore, analysis of heart rate recovery estimated during activities of daily living showed significant differences between healthy and patient groups. This work underscores the promise and sensitivity of novel digital measures from multimodal sensor time-series to differentiate chronic patients from healthy individuals and monitor their HRQoL. The presented work provides clinicians with realistic insights of continuous at home patient monitoring and its practical value in quantitative assessment of fatigue and sleep, an area of unmet need.
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