Personalized intermittent pneumatic calf compression frequency for augmenting foot blood perfusion: The optimized effect and a personalized mode predicting method.

Intermittent pneumatic compression (IPC) therapy has been adopted in prevention and treatment of ischemic-related peripheral vascular diseases. The aim of this study is to provide an approach to personalize the compression strategy of IPC therapy for maximizing foot skin blood flow. In this study, we presented a method to predict the optimized compression mode (OCM) for each subject based on biomechanical features extracted from experimental data tested with multiple IPC modes. First, to demonstrate the blood flow enhancing effect by applying the personalized OCM, four IPC modes of different frequency settings were tested on a total of 24 subjects. The frequency settings were adjusted by deflating-waiting time, which was defined as the total time length from the start of cuff deflation to the start of next compression. The foot skin blood perfusion and IPC air cuff pressure were monitored during the experiments. The personalized OCM was defined as the certain IPC mode that has the highest blood perfusion augmentation (BPA). Compared with the rest stage blood perfusion, the personalized OCM settings resulted in >50% of augmentation for 75% of healthy subjects (maximum augmentation at 244%) and >20% augmentation for 75% of patients with diabetes (maximum augmentation at 180%). Second, for predicting the OCM, we establish a random forest model based on the features extracted from the experimental data. The binary classification resulted in acceptable prediction performance (AUC > 0.7). This study might inspire new IPC strategies for improving foot microcirculation.

Multiple blood flow surges during intermittent pneumatic compression: The origins and their implications.

Intermittent pneumatic compression (IPC) therapy has been used to enhance peripheral blood flow for prevention and rehabilitation of ischemic-related vascular diseases. A novel phenomenon has been reported that multiple blood flow surges appeared in the skin blood flow signal during each compression, but its mechanism has not been fully revealed. This study aimed to gain insights into the origins of these blood flow surges through experiment and biomechanical modeling methods. Foot skin blood flow (SBF) signals of 13 healthy adults (23.8 ± 0.5 yr old, 7 males) and air cuff pressure signals were recorded during IPC. Lumped parameter modeling and wavelet analysis were adopted to investigate the multiple blood flow surges (named as Peak1, Peak2 and Peak3). The results of the simulated Peak1 and Peak2 were in good agreements with the experiment results, suggesting that IPC could enhance foot SBF not only by deflation, but also by inflation. Statistical analysis demonstrated that high frequency compression with more frequent occurrence of Peak1 and Peak2 lead to significantly higher (Friedman test, p < 0.001) time-averaged SBF enhancement than the traditional mode. In addition, wavelet analysis showed that the major frequency component of the Peak3 (0.059 Hz) was within the range of the vascular myogenic activity, suggesting a vascular regulation process triggered by intravascular pressure changes. Our study provide new insights into the mechanism of how IPC enhance foot SBF.

Variations of human cerebral and ocular blood flow during exposure to multi-axial accelerations : A mathematical modeling study.

Human hemodynamic responses during exposure to multi-axial acceleration was a relatively new topic in the fields of acceleration physiology. This study aimed to focus on these responses, especially variations of blood perfusion to brain and eyes, through mathematical modeling. A mathematical model was established using lumped parameter methods, containing compartments of four heart chambers, systemic arteries and veins, circulation of typical systemic organs, and some compartments for pulmonary circulation, together with autonomic regulation considered. This model was firstly validated by using experimental data from experiment of posture change and centrifuge tests of +Gz accelerations, and then applied to analyze human hemodynamic responses to typical multi-axial accelerations. Validation results demonstrated the mathematical model could generate reasonable responses of human cardiovascular system during posture change and exposure to +Gz accelerations. Simulation results of hemodynamic responses to multi-axial accelerations depicted Gy induced significant differences of blood flow to the left and right eyes. And some contour maps were generated based on these results, which provided a quick way to estimate blood flow variations in brain and eyes during exposure to different accelerations. Graphical Abstract This study aimed to focus on variations of blood perfusion to brain and eyes during exposure to typical multi-axial accelerations through mathematical modeling. This model was firstly validated by using experimental data from experiment of posture change and centrifuge tests of +Gz accelerations, and then applied to analyze human hemodynamic responses to typical multi-axial accelerations. Simulation results of hemodynamic responses to multi-axial accelerations depicted Gy induced significant differences of blood flow to the left and right eyes. And contour maps that generated based on these results provided a quick way to estimate blood flow variations in brain and eyes during exposure to different accelerations.

Alterations in the coupling functions between cerebral oxyhaemoglobin and arterial blood pressure signals in post-stroke subjects.

Cerebral autoregulation (CA) is the complex homeostatic regulatory relationship between blood pressure (BP) and cerebral blood flow (CBF). This study aimed to analyze the frequency-specific coupling function between cerebral oxyhemoglobin concentrations (delta [HbO2]) and mean arterial pressure (MAP) signals based on a model of coupled phase oscillators and dynamical Bayesian inference. Delta [HbO2] was measured by 24-channel near-infrared spectroscopy (NIRS) and arterial BP signals were obtained by simultaneous resting-state measurements in patients with stroke, that is, 9 with left hemiparesis (L-H group), 8 with right hemiparesis (R-H group), and 17 age-matched healthy individuals as control (healthy group). The coupling functions from MAP to delta [HbO2] oscillators were identified and analyzed in four frequency intervals (I, 0.6-2 Hz; II, 0.145-0.6 Hz; III, 0.052-0.145 Hz; and IV, 0.021-0.052 Hz). In L-H group, the CS from MAP to delta [HbO2] in interval III in channel 8 was significantly higher than that in healthy group (p = 0.003). Compared with the healthy controls, the coupling in MAP→delta [HbO2] showed higher amplitude in interval I and IV in patients with stroke. The increased CS and coupling amplitude may be an evidence of impairment in CA, thereby confirming the presence of impaired CA in patients with stroke. In interval III, the CS in L-H group from MAP to delta [HbO2] in channel 16 (p = 0.001) was significantly lower than that in healthy controls, which might indicate the compensatory mechanism in CA of the unaffected side in patients with stroke. No significant difference in region-wise CS between affected and unaffected sides was observed in stroke groups, indicating an evidence of globally impaired CA. These findings provide a method for the assessment of CA and will contribute to the development of therapeutic interventions in stroke patients.

Frequency-specific Effective Connectivity in Subjects with Cerebral Infarction as Revealed by NIRS Method.

A connectivity-based approach can highlight the network reorganization in the chronic phases after stroke and contributes to the development of therapeutic interventions. Using dynamic Bayesian inference, this study aimed to assess the effective connectivity (EC) in various frequency bands through the near-infrared spectroscopy (NIRS) method in subjects with cerebral infarction (CI). A phase-coupling model was established based on phase information extracted using the wavelet transform of NIRS signals. Coupling strength and the main coupling direction were estimated using dynamic Bayesian inference. Wilcoxon test and chi-square test were used to determine the significant difference in EC between two groups. Results showed that the coupling strength of the EC in the CI group significantly decreased relative to that in the healthy group. The decrease was most significant in the frequency intervals IV (0.021 Hz-0.052 Hz; p = 0.0006) and VI (0.005 Hz-0.095 Hz; p = 0.0028). The main coupling direction changed from the right prefrontal cortex to the right motor cortex and left motor cortex in the frequency intervals IV (p1 = 0.041, p2 = 0.047) and II (p1 = 0.0017, p2 = 0.0036), respectively. The EC decreased or was even lost significantly in the EC map of the CI group. Experimental results indicated that information propagation was blocked in the CI group than in the healthy group and resulted in the decreased coupling strength and connectivity loss. The main coupling direction of the motor section changed from driving into being driven because of the degradation of limb movement function.

Functional connectivity analysis using fNIRS in healthy subjects during prolonged simulated driving.

Noninvasive and accurate assessment of driving fatigue in relation to brain activity during long-term driving can contribute to traffic safety and accident prevention. This study evaluated functional connectivity (FC) in relevant brain regions. Synergistic mechanisms in different brain regions were detected by a novel simulator, which combined semi-immersive virtual reality technology and functional near-infrared spectroscopy. Each subject was instructed to complete driving tasks coupled with a mental calculation task. Wavelet coherence (WCO) and wavelet phase coherence (WPCO) were calculated and assessed in frequency intervals (I) 0.6-2 and (II) 0.145-0.6Hz as global connectivity measures; (III) 0.052-0.145, (IV) 0.021-0.052, (V) 0.0095-0.021 and (VI) 0.005-0.0095Hz as FC. WCO and WPCO revealed the strength and synchronization of cerebral connectivity, respectively. Significantly low WCO levels were found in intervals I and III in prefrontal cortex (PFC) and IV in motor cortex (MC) at the end of the driving task. Furthermore, significantly low WPCO were found in intervals I, and III in PFC and interval IV in MC. Experimental findings suggested that progressive mental fatigue adversely influences the cognitive function in the PFC and the cooperative mechanism between the PFC and MC.

Vigilance Task-Related Change in Brain Functional Connectivity as Revealed by Wavelet Phase Coherence Analysis of Near-Infrared Spectroscopy Signals.

This study aims to assess the vigilance task-related change in connectivity in healthy adults using wavelet phase coherence (WPCO) analysis of near-infrared spectroscopy signals (NIRS). NIRS is a non-invasive neuroimaging technique for assessing brain activity. Continuous recordings of the NIRS signals were obtained from the prefrontal cortex (PFC) and sensorimotor cortical areas of 20 young healthy adults (24.9 ± 3.3 years) during a 10-min resting state and a 20-min vigilance task state. The vigilance task was used to simulate driving mental load by judging three random numbers (i.e., whether odd numbers). The task was divided into two sessions: the first 10 min (Task t1) and the second 10 min (Task t2). The WPCO of six channel pairs were calculated in five frequency intervals: 0.6-2 Hz (I), 0.145-0.6 Hz (II), 0.052-0.145 Hz (III), 0.021-0.052 Hz (IV), and 0.0095-0.021 Hz (V). The significant WPCO formed global connectivity (GC) maps in intervals I and II and functional connectivity (FC) maps in intervals III to V. Results show that the GC levels in interval I and FC levels in interval III were significantly lower in the Task t2 than in the resting state (p < 0.05), particularly between the left PFC and bilateral sensorimotor regions. Also, the reaction time (RT) shows an increase in Task t2 compared with that in Task t1. However, no significant difference in WPCO was found between Task t1 and resting state. The results showed that the change in FC at the range of 0.6-2 Hz was not attributed to the vigilance task per se, but the interaction effect of vigilance task and time factors. The findings suggest that the decreased attention level might be partly attributed to the reduced GC levels between the left prefrontal region and sensorimotor area. The present results provide a new insight into the vigilance task-related brain activity.