Central and cerebrovascular effects of leg crossing in humans with sympathetic failure

A B S T R A C T Leg crossing increases arterial pressure and combats symptomatic orthostatic hypotension in patients with sympathetic failure. This study compared the central and cerebrovascular effects of leg crossing in patients with sympathetic failure and healthy controls. We addressed the relationship between MCA V mean (middle cerebral artery blood velocity; using transcranial Doppler ultrasound), frontal lobe oxygenation [O 2 Hb (oxyhaemoglobin)] and MAP (mean arterial pressure), CO (cardiac output) and TPR (total peripheral resistance) in six patients (aged 37-67 years; three women) and age-and gender-matched controls during leg crossing. In the patients, leg crossing increased MAP from 58 (42-79) to 72 (52-89) compared with 84 (70-95) to 90 (74-94) mmHg in the controls. MCA V mean increased from 55 (38-77) to 63 (45-80) and from 56 (46-77) to 64 (46-80) cm/s respectively (P < 0.05), with a larger rise in O 2 Hb [1.12 (0.52-3.27)] in the patients compared with the controls [0.83 (− 0.11 to 2.04) μmol/l]. In the control subjects, CO increased 11 % (P < 0.05) with no change in TPR. By contrast, in the patients, CO increased 9 % (P < 0.05), but also TPR increased by 13 % (P < 0.05). In conclusion, leg crossing improves cerebral perfusion and oxygenation both in patients with sympathetic failure and in healthy subjects. However, in healthy subjects, cerebral perfusion and oxygenation were improved by a rise in CO without significant changes in TPR or MAP, whereas in patients with sympathetic failure, cerebral perfusion and oxygenation were improved through a rise in MAP due to increments in both CO and TPR

Estimation of Respiratory Rate during Biking with a Single Sensor Functional Near-Infrared Spectroscopy (fNIRS) System

Objective: The employment of wearable systems for continuous monitoring of vital signs is increasing. However, due to substantial susceptibility of conventional bio-signals recorded by wearable systems to motion artifacts, estimation of the respiratory rate (RR) during physical activities is a challenging task. Alternatively, functional Near-Infrared Spectroscopy (fNIRS) can be used, which has been proven less vulnerable to the subject’s movements. This paper proposes a fusion-based method for estimating RR during bicycling from fNIRS signals recorded by a wearable system. Methods: Firstly, five respiratory modulations are extracted, based on amplitude, frequency, and intensity of the oxygenated hemoglobin concentration (O2Hb) signal. Secondly, the dominant frequency of each modulation is computed using the fast Fourier transform. Finally, dominant frequencies of all modulations are fused, based on averaging, to estimate RR. The performance of the proposed method was validated on 22 young healthy subjects, whose respiratory and fNIRS signals were simultaneously recorded during a bicycling task, and compared against a zero delay Fourier domain band-pass filter. Results: The comparison between results obtained by the proposed method and band-pass filtering indicated the superiority of the former, with a lower mean absolute error (3.66 vs. 11.06 breaths per minute, p0.05). The proposed fusion strategy also outperformed RR estimations based on the analysis of individual modulation. Significance: This study orients towards the practical limitations of traditional bio-signals for RR estimation during physical activities

Performance of near-infrared spectroscopy in measuring local O2 consumption and blood flow in skeletal muscle

Mesure de la consommation d'oxygène locale et de la circulation sanguine par spectroscopie infrarouge chez 26 sujets effectuant un exercice de préhension isométrique. Comparaison avec la méthode de Fick et la pléthysmographi

Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals

Background: Near-infrared spectroscopy (NIRS) relative concentration signals contain ‘noise’ from physiological processes such as respiration and heart rate. Simultaneous assessment of NIRS and respiratory rate (RR) using a single sensor would facilitate a perfectly time-synced assessment of (cerebral) physiology. Our aim was to extract respiratory rate from cerebral NIRS intensity signals in neonates admitted to a neonatal intensive care unit (NICU). Methods: A novel algorithm, NRR (NIRS RR), is developed for extracting RR from NIRS signals recorded from critically ill neonates. In total, 19 measurements were recorded from ten neonates admitted to the NICU with a gestational age and birth weight of 38 ± 5 weeks and 3092 ± 990 g, respectively. We synchronously recorded NIRS and reference RR signals sampled at 100 Hz and 0.5 Hz, respectively. The performance of the NRR algorithm is assessed in terms of the agreement and linear correlation between the reference and extracted RRs, and it is compared statistically with that of two existing methods. Results: The NRR algorithm showed a mean error of 1.1 breaths per minute (BPM), a root mean square error of 3.8 BPM, and Bland–Altman limits of agreement of 6.7 BPM averaged over all measurements. In addition, a linear correlation of 84.5% (p p Conclusions: We showed the possibility of extracting RR from neonatal NIRS in an intensive care environment, which showed high correspondence with the reference RR recorded. Adding the NRR algorithm to a NIRS system provides the opportunity to record synchronously different physiological sources of information about cerebral perfusion and respiration by a single monitoring system. This allows for a concurrent integrated analysis of the impact of breathing (including apnea) on cerebral hemodynamics

Effects of aging on the cerebrovascular orthostatic response

When healthy subjects stand up, it is associated with a reduction in cerebral blood velocity and oxygenation although cerebral autoregulation would be considered to prevent a decrease in cerebral perfusion. Aging is associated with a higher incidence of falls, and in the elderly falls may occur particularly during the adaptation to postural change. This study evaluated the cerebrovascular adaptation to postural change in 15 healthy younger (YNG) vs. 15 older (OLD) subjects by recordings of the near-infrared spectroscopy-determined cerebral oxygenation (cO(2)Hb) and the transcranial Doppler-determined mean middle cerebral artery blood velocity (MCA V-mean). In OLD (59 (52-65) years) vs. can, YNG (29 (27-33) years), the initial postural decline in mean arterial pressure (-52+/-3% vs. -67+/-3%), cO(2)Hb (-3.4+/-2.5 mu mol l(-1) vs. -5.3+/-1.7 mu mol l(-1)) and MCA V-mean (-16+/-4% vs. -29+/-3%) was smaller. The decline in MCA V-mean was related to the reduction in MAP. During prolonged orthostatic stress, the decline in MCA V-mean,and cO(2)Hb in OLD remained smaller. We conclude that with healthy aging the postural reduction in cerebral perfusion becomes less prominent. (C) 2009 Elsevier Inc. All rights reserved

Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference

Objective: Respiration is recognized as a systematic physiological interference in functional near-infrared spectroscopy (fNIRS). However, it remains unanswered as to whether it is possible to estimate the respiratory rate (RR) from such interference. Undoubtedly, RR estimation from fNIRS can provide complementary information that can be used alongside the cerebral activity analysis, e.g., sport studies. Thus, the objective of this paper is to propose a method for RR estimation from fNIRS. Our primary presumption is that changes in the baseline wander of oxygenated hemoglobin concentration (O2Hb) signal are related to RR. Methods: fNIRS and respiratory signals were concurrently collected from subjects during controlled breathing tasks at a constant rate from 0.1 Hz to 0.4 Hz. Firstly, the signal quality index algorithm is employed to select the best O2Hb signal, and then a band-pass filter with cut-off frequencies from 0.05 to 2 Hz is used to remove very low- and high-frequency artifacts. Secondly, troughs of the filtered O2Hb signal are localized for synthesizing the baseline wander (S1) using cubic spline interpolation. Finally, the fast Fourier transform of the S1 signal is computed, and its dominant frequency is considered as RR. In this paper, two different datasets were employed, where the first one was used for the parameter adjustment of the proposed method, and the second one was solely used for testing. Results: The low mean absolute error between the reference and estimated RRs for the first and second datasets (2.6 and 1.3 breaths per minute, respectively) indicates the feasibility of the proposed method for RR estimation from fNIRS. Significance: This paper provides a novel view on the respiration interference as a source of complementary information in fNIRS