Volume 61, Issue 6 - Highlight issue: Biosignal Analysis

Visually evoked potentials (VEPs) are signals evoked by a visual stimulus. They consist of brief discrete deflections embedded in background electroencephalographic (EEG) activity, which often has larger amplitude. Background EEG cancelation is a major part of VEPs analysis algorithms often realized by coherent averaging or other methods requiring large minimal amount of registered sweeps. In some cases, especially for pediatric patients, or in poor patient compliance cases, long procedure duration and fatigue might cause impaired attention and non-steady target fixation, affecting the quality of recorded VEPs. The possibility to reconstruct VEPs in every single sweep from limited size ensembles opens new diagnostic possibilities and shortens the registration procedure improving its quality. A proposed method is based on truncated expansion (Karhunen-Loève transform) of VEP signals applying generalized universal basis functions (eigenvectors of covariation matrix) calculated from learning set of sweeps, i.e. an ensemble of collected typical recordings. It realizes the possibility to reconstruct a signal from every single sweep even in limited size ensembles of registered sweeps. Application of adaptively time-shifted basis functions enables optimal reconstruction of the signal with latency shift or jitter.

The aim was to assess accuracy of tidal volumes (TV) calculated by impedance pneumography (IP), reproducibility of calibration coefficients (CC) between IP and pneumotachometry (PNT), and their relationship with body posture, breathing rate and depth. Fourteen students performed three sessions of 18 series: normal and deep breathing at 6, 10, 15 breaths/min rates, while supine, sitting and standing; 18 CC were calculated for every session. Session 2 was performed 2 months after session 1, session 3 1–3 days after session 2. TV were calculated using full or limited set of CC from current session, in case of sessions 2 and 3 also using CC from session 1 and 2, respectively. When using full set of CC from current session, IP underestimated TV by -3.2%. Using CC from session 2 for session 3 measurements caused decrease of relative difference: -3.9%, from session 1 for session 2: -5.3%; for limited set of CC: -5.0%. The body posture had significant effect on CC. The highest accuracy was obtained when all factors influencing CC were considered. The application of CC related only to body posture may result in shortening of calibration and moderate accuracy loss. Using CC from previous session compromises accuracy moderately.

Analysis of electromyography (EMG) data has been shown to be valuable in biomedical and clinical research. However, most analysis tools do not consider the non-linearity of EMG data or the synergistic effects of multiple neuromuscular activities. The SYNERGOS algorithm was developed to assess a single index based on non-linear analysis of multiple neuromuscular activation (MNA) of different muscles. This index has shown promising results in Parkinsonian gait, but it was yet to be explored whether the SYNERGOS index is generalizable. In this study, we evaluated generalizability of the SYNERGOS index over the course of several trials and over separate days with different walking speeds. Ten healthy adults aged from 18 to 40 years walked on a treadmill on two different days, while EMG data was collected from the upper and lower right leg. SYNERGOS indices were obtained and a generalizability analysis was conducted. The algorithm detected changes in MNA in response to altering gait speed and depicted a high generalizability coefficient (ρ^2${\hat \rho ^2}$) of 0.823 with a standard error of 5.117 with nominal inter-trial or inter-day effects. We concluded SYNERGOS may be a valuable tool in EMG analysis due to its generalizability and its sensitivity to task modifications and associated neuromotor changes.

The protocol for estimating force of contraction by triceps surae (TS) muscles requires the immobilization of the ankle during dorsiflexion and plantar flexion. However, large variability in the results has been observed. To identify the cause of this variability, experiments were conducted where ankle dorsiflexion force and electromyogram (EMG) of the TS were recorded under two conditions: (i) toes were strapped and (ii) toes were unstrapped, with all other conditions such as immobilization of the ankle remaining unchanged. The root mean square (RMS) of the EMG and the force were analyzed and one-tail Student’s t-test was performed for significance between the two conditions. The RMS of the EMG from TS muscles was found to be significantly higher (~55%) during dorsiflexion with toes unstrapped compared with when the toes were strapped. The torque corresponding to dorsiflexion was also higher with toes unstrapped. Our study has shown that it is important to strap the toes when measuring the torque at the ankle and EMG of the TS muscles.

Systemic arterial blood pressure (BP) is one of the most important parameters of the cardiovascular system. An oscillometric NIBP monitor was specifically designed to measure oscillometric pulsations and mean arterial pressure (MAP) during inflation and deflation of the cuff. Nineteen healthy young (age 23.1±1.7 years; mean±SD) and 35 elderly (83.9±7.9 years; mean±SD) subjects were studied. Differential analysis of MAP during inflation and deflation show mean |ΔMAP|=2.9±2.6 mm Hg in the young group (mean±SD) and |ΔMAP|=6.3±5.2 mm Hg for seniors (mean±SD). There was a significant difference (p<0.05) in means of |ΔMAP| measured during cuff inflation and cuff deflation between both groups. In about 50% of elderly subjects |ΔMAP| was higher than 5 mm Hg. Potential clinical relevance of the method needs to be further evaluated.

The study of heart autonomic control (HAC) in patients with chronic kidney disease (CKD) undergoing dialysis treatment has been carried out, however, there are no studies reporting the reliability of measurements of HAC parameters involving the mentioned samples and conditions. The reliability of many HAC parameters was evaluated from patients with CKD during two sessions of hemodialysis. The successive R-R intervals were recorded during two sessions of hemodialysis from 14 CKD patients that were undergoing dialysis for at least 6 months and with no history of recurrent hypotensive events. HAC parameters were obtained with time and frequency domain analysis, as well as with nonlinear methods. The reliability was measured with the intraclass correlation coefficient (ICC). The results showed excellent reliability (ICC=0.90–0.98) for most heart rate variability (HRV) parameters, especially the parameters obtained in the time domain [square root of the mean squared differences between successive R-R intervals (RMSSD), percentage of adjacent R-R intervals that differ by more than 50 ms (pNN50), mean of the 5-min standard deviations of R-R intervals (SDNNi), and triangular index] and with non-linear methods [standard deviation of the instantaneous variability beat-to-beat (SD1), standard deviation in long-term continuous R-R intervals (SD2), detrended fluctuation analysis (DFA) α1 and α2, approximate and sample entropies, and correlation dimension (D2): ICC=0.86–0.96]. Among the parameters obtained in the frequency domain (normalized magnitude from the spectrum of low-frequency components (LFnu), normalized magnitude from the spectrum of high-frequency components (HFnu), and LF/HF ratio), the LF/HF ratio showed better reliability (ICC=0.96 vs. ICC=0.70). Measurements of HAC parameters have excellent test-retest reliability for the studied samples and conditions.

Vital parameter monitoring of term and preterm infants during incubator care with self-adhesive electrodes or sensors directly positioned on the skin [e.g. photoplethysmography (PPG) for oxygen saturation or electrocardiography (ECG)] is an essential part of daily routine care in neonatal intensive care units. For various reasons, this kind of monitoring contains a lot of stress for the infants. Therefore, there is a need to measure vital parameters (for instance respiration, temperature, pulse, oxygen saturation) without mechanical or conductive contact. As a non-contact method of monitoring, we present an adapted version of camera-based photoplethysmography imaging (PPGI) according to neonatal requirements. Similar to classic PPG, the PPGI camera detects small temporal changes in the term and preterm infant’s skin brightness due to the cardiovascular rhythm of dermal blood perfusion. We involved 10 preterm infants in a feasibility study [five males and five females; mean gestational age: 26 weeks (24–28 weeks); mean biological age: 35 days (8–41 days); mean weight at the time of investigation: 960 g (670–1290 g)]. The PPGI camera was placed directly above the incubators with the infant inside illuminated by an infrared light emitting diode (LED) array (850 nm). From each preterm infant, 5-min video sequences were recorded and analyzed post hoc. As the measurement scenario was kept as realistic as possible, the infants were not constrained in their movements in front of the camera. Movement intensities were assigned into five classes (1: no visible motion to 5: heavy struggling). PPGI was found to be significantly sensitive to movement artifacts. However, for movement classes 1–4, changes in blood perfusion according to the heart rate (HR) were recovered successfully (Pearson correlation: r=0.9759; r=0.765 if class 5 is included). The study was approved by the Ethics Committee of the Universal Hospital of the RWTH Aachen University, Aachen, Germany (EK 254/13).

Photoplethysmography (PPG) waveforms are rich in cardiovascular information, and hence, their analysis is significant in the diagnosis and prevention of cardiovascular diseases (CVDs). The second derivative of photoplethysmography (SDPPG) analysis for the accurate detection of significant points in characterising the PPG waveform is challenging. In this paper, a SDPPG analysis algorithm is proposed based on a resampling technique which normalises the signal and ensures the presence of all significant points of interest in all its recurrences. The proposed delineator detects a , b and e waves in SDPPG, which are based on the combined analysis of PPG waveforms and their second derivatives, characterising them beat-by-beat by electrocardiogram (ECG) signals. Experiments have been conducted on 46 PPG signal records, each of 10-s duration with low and varying amplitudes, and regular and irregular heart rhythms for healthy adults, as well as unhealthy and aged patients obtained from the large-scale openly available database PhysioNet. Based on the experiments conducted, it is found that the proposed algorithm performs better than existing methods in terms of sensitivity and positive predictivity with a highest sensitivity of 99.84% with respect to a (onset) and b waves, 99.67% for e waves (dicrotic notch), and 100% of positive predictivity for a and b waves and 99.82% in case of e waves.

Rearranged origin of heart rhythm in patients with atrial fibrillation (AF) influences the regulation of the heart and consequently the respiratory rhythm, and the bidirectional interaction of these rhythms not documented. Hence, we examined coupling of the RR interval and the respiration (Resp) signal by coherence, Granger causality and the cross-sample entropy method of time series analysis in patients with AF and a healthy control group. In healthy subjects, the influence of respiration on cardiac rhythm was found as increased coherence at the breathing frequency (BF) range, significantly stronger interaction and synchrony from Resp to RR than from RR to Resp. On the contrary, in patients with AF, coherence at BF diminished, there were no causal interactions between signals in both directions, which resulted in equally great asynchrony between them. In AF, the absence of full functionality of the sinoatrial node, as an integrator of neural cardiac control, resulted in diminished vagal modulation of heart periods and consequently impaired bidirectional cardio-respiratory interaction.