Bioimpedance plethysmography with capacitive electrodes and sole force sensors: comparative trial

Foot impedance plethysmography was implemented using two types of electrodes (dry and capacitive) and sole force sensors. The latter are commonly used for assessing diabetic foot ulcers (DFU). For impedance plethysmography, a tetrapolar configuration has been used with three different plantar setups: four skin contact electrodes, four capacitive contact electrodes and two Force Sensing Resistors (FSRs). In this work, FSRs have been considered as possible capacitive electrodes because the top substrate contains interdigitating conductive electrodes and a semiconductive polymer. All the measurements have been performed using a 1 mA/10 kHz excitation current and have been tried under the feet of a standing person to detect impedance plethysmography signals. Contact electrodes allow a good cardiac pulse signal while capacitive contact through the socks features mains interferences. Force sensing resistors with their force-dependent resistance in parallel to the capacitive coupling, were not able to detect cardiac pulse. But promising results can be anticipated from these findings provided higher frequencies are used and larger sensor areas to help detect altered skin states in diabetic foot.

Pre-stimulus fluctuations in heart-synchronised neural activity predict subsequent self-association with affective stimuli

We frequently associate ourselves with certain affective attributes (e.g., I am joyful, I am lazy, etc.) and not others. However, little is understood about how such self-associations come about. Interoceptive predictive theories propose that a sense of self, especially in an affective context, results from the brain making inferences about internal bodily states. A key prediction of these theories is that for an affective attribute to be self-associated, it would depend not only on the stimulus, but also non-stimulus-specific fluctuations in one’s bodily state; a hypothesis not yet tested. We measured EEG response synchronised to the cardiac cycle – a common way to measure interoceptive neural processing – prior to the presentation of pleasant and unpleasant adjectives to participants. Participants responded if the adjectives were self-descriptive or not. We found that cardiac-pulse-synchronised neural activity prior to the presentation of unpleasant adjectives predicted whether participants subsequently associated that adjective to themselves. This effect was observed over midfrontal scalp locations, commonly observed in interoceptive neural processing. No such effect was observed for pleasant adjectives, or by randomly shuffling the cardiac peak times to account for non-interoceptive neural differences. Our results confirm a key prediction of interoceptive predictive coding theories – that bodily signals are not just modulated in response to self-related and affective arousal, but that a subjective sense of affective self arises due to neural processing of bodily signals. Our results have important implications for many neuropsychiatric disorders that involve altered self-referential processing of unpleasant stimuli.

Motion artifacts reduction in cardiac pulse signal acquired from video imaging

This study examines the possibility of remotely measuring the cardiac pulse activity of a patient, which could be an alternative technique to the classical method. This type of measurement is non-invasive. However, several limitations may deteriorate the accuracy of the results, including changes in ambient illumination, motion artifacts (MA) and other interferences that may occur through video recording. The paper in hand presents a new approach as a remedy for the aforementioned problem in cardiac pulse signals extracted from facial video recordings. Partitioning provides the basis for the presented MA reduction method; the acquired signals are partitioned into two sets for each second and every partition is shifted to the mean level and then all the partitions are recombined again into one signal, which is followed by low-pass filtering for enhancement. The proposed compared with ordinary pulse oximetry Photoplethysmographic (PPG) method. The resulted correlation coefficient was found (0.957) when calculated between the results of the proposed method and the ordinary one. Experiments were implemented using a common camera by creating a dataset from 11 subjects. The ease of implementation of this method with a simple that can be used to monitor the cardiac pulse rates in both home and the clinical environments.

Data-driven beamforming techniques to attenuate ballistocardiogram (BCG) artefacts in EEG-fMRI without detecting cardiac pulses in electrocardiography (ECG) recordings

Simultaneous recording of EEG and fMRI is a very promising non-invasive neuroimaging technique, providing a wide range of complementary information to characterize underlying mechanisms associated with brain functions. However, EEG data obtained from the simultaneous EEG-fMRI recordings are strongly influenced by MRI related artefacts, namely gradient artefacts (GA) and ballistocardiogram (BCG) artefacts. The GA is induced by temporally varying magnetic field gradients used for MR imaging, whereas the BCG artefacts are produced by cardiac pulse driven head motion in the strong magnetic field of the MRI scanner, so that this BCG artefact will be present when the subject is lying in the scanner, even when no fMRI data are acquired. When compared to corrections of the GA, the BCG artefact corrections are more challenging to remove due to its inherent variabilities and dynamic changes over time. Typically, the BCG artefacts obscure the EEG signals below 20Hz, and this remains problematic especially when the frequency of interest of EEG signals is below 20Hz, such as Alpha (8-13Hz) and Beta (13-30Hz) band EEG activity, or sleep spindle (11-16Hz) and slow-wave oscillations (<1 Hz) during sleep. The standard BCG artefact corrections, as for instance Average Artefact Subtraction method (AAS), require detecting cardiac pulse (R-peak) events from simultaneous electrocardiography (ECG) recordings. However, ECG signals in the MRI scanner are sometimes distorted and will become problematic for detecting reliable R-peaks. In this study, we focused on a beamforming technique, which is a spatial filtering technique to reject sources of signal variance that do not appear dipolar in the source space. This technique attenuates all unwanted source activities outside of a presumed region of interest without having to specify the location or the configuration of these underlying source signals. Specifically, in this study, we revisited the advantages of the beamforming technique to attenuate the BCG artefact in EEG-fMRI, and also to recover meaningful task-based induced neural signals during an attentional network task (ANT) which required participants to identify visual cues and respond as accurately and quickly as possible. We analysed EEG-fMRI data in 20 healthy participants when they were performing the ANT, and compared four different BCG correction approaches (non-BCG corrected, AAS BCG corrected, beamforming+AAS BCG corrected, beamforming BCG corrected). We demonstrated that beamforming BCG corrected data did not only significantly reduce the BCG artefacts, but also significantly recovered the expected task-based induced brain activity when compared to the standard AAS BCG corrections. Without detecting R-peak events from the ECG, this data-driven beamforming technique appears promising especially for longer data acquisition of sleep and resting EEG-fMRI. Our findings extend previous work regarding the recovery of meaningful EEG signals by an optimized suppression of MRI related artefacts.HighlightsBeamforming spatial filtering technique attenuates ballistocardiogram (BCG) artefacts in EEG-fMRI without detecting cardiac pulses in electrocardiography (ECG) recordings.Beamforming BCG denoising technique recovers expected task-based induced visual alpha and motor beta event-related desynchronization (ERD).Beamforming technique improves signal-noise ratios (SNR) of neural activities as compared to sensor level signals.Data-driven beamforming technique appears promising for longer data acquisition of sleep and resting EEG-fMRI without relying on ECG signals.

Association of remote imaging photoplethysmography and cutaneous perfusion in volunteers

Remote imaging photoplethysmography (iPPG) senses the cardiac pulse in outer skin layers and is responsive to mean arterial pressure and pulse pressure in critically ill patients. Whether iPPG is sufficiently sensitive to monitor cutaneous perfusion is not known. This study aimed at determining the response of iPPG to changes in cutaneous perfusion measured by Laser speckle imaging (LSI). Thirty-seven volunteers were engaged in a cognitive test known to evoke autonomic nervous activity and a Heat test. Simultaneous measurements of iPPG and LSI were taken at baseline and during cutaneous perfusion challenges. A perfusion index (PI) was calculated to assess iPPG signal strength. The response of iPPG to the challenges and its relation to LSI were determined. PI of iPPG significantly increased in response to autonomic nervous stimuli and to the Heat test by 5.8% (p = 0.005) and 11.1% (p < 0.001), respectively. PI was associated with LSI measures of cutaneous perfusion throughout experiments (p < 0.001). iPPG responses to study task correlated with those of LSI (r = 0.62, p < 0.001) and were comparable among subjects. iPPG is sensitive to autonomic nervous activity in volunteers and is closely associated with cutaneous perfusion.

Vascular origins of low-frequency oscillations in the cerebrospinal fluid signal in resting-state fMRI: Interpretation using photoplethysmography

Slow and rhythmic spontaneous oscillations of cerebral blood flow are well known to have diagnostic utility, notably frequencies of 0.008-0.03 Hz (B-waves) and 0.05-0.15Hz (Mayer waves or M waves). However, intracranial measurements of these oscillations have been difficult. Oscillations in the cerebrospinal fluid (CSF), which are influenced by the cardiac pulse wave, represent a possible avenue for non-invasively tracking these oscillations using resting-state functional MRI (rs-fMRI), and have been used to correct for vascular oscillations in rs-fMRI functional connectivity calculations. However, the relationship between low-frequency CSF and vascular oscillations is unclear. In this study, we investigate this relationship using fast simultaneous multi-slice rs-fMRI coupled with fingertip photoplethysmography (PPG). We not only extract B-wave and M-wave range spectral power from the PPG signal, but also derive the pulse-intensity ratio (PIR, a surrogate of slow blood-pressure oscillations), the second-derivative of the PPG (SDPPG, a surrogate of arterial stiffness) and heart-rate variability (HRV). The main findings of this study are: (1) signals in different CSF regions (ROIs) are not equivalent in their vascular contributions or in their associations with vascular and tissue rs-fMRI signals; (2) the PPG signal contains the highest signal contribution from the M-wave range, while PIR contains the highest signal contribution from the B-wave range; (3) in the low-frequency range, PIR is more strongly associated with rs-fMRI signal in the CSF than PPG itself, and than HRV and SDPPG; (4) PPG-related vascular oscillations only contribute to < 20% of the CSF signal in rs-fMRI, insufficient support for the assumption that low-frequency CSF signal fluctuations directly reflect vascular oscillations. These findings caution the use of CSF as a monolithic region for extracting physiological nuisance regressors in rs-fMRI applications. They also pave the way for using rs-fMRI in the CSF as a potential tool for tracking cerebrovascular health through, for instance the strong relationship between PIR and the CSF signal.

Design, Implementation, and Validation of a Pulsatile Heart Phantom Pump

The developments in Computed Tomography (CT) and Magnetic Resonance allow visualization of blood flow in vivo using these techniques. However, validation tests are needed to determine a gold standard. For the validation tests, controllable systems that can generate pulsatile flow are needed. In this study, we aimed to develop an affordable pulsatile pump and an artificial circulatory system to simulate the blood flow for validation purposes. Initially, the prerequisites for the phantom were pulsating flow output equal to that of the human cardiac pulse pattern; the flow pattern of the mimicked cardiac output should be equal to that of a human, a variable stroke volume (40–120 ml/beat), and a variable heart rate (60–170 bpm). The developed phantom setup was tested with CT scanner. A washout profile was created based on the image intensity of the selected slice. The test was successful for a heart rate of 70 bpm and a stroke volume of 68 ml, but the system failed to work at various heartbeats and stroke volumes. This was due to the problems with software of the microcontroller. As conclusion in this study, we present a proof of concept for a pulsatile heart phantom pump that can be used in validation tests.