Soft, comfortable polymer dry electrodes for high quality ECG and EEG recording

Conventional gel electrodes are widely used for biopotential measurements, despite important drawbacks such as skin irritation, long set-up time and uncomfortable removal. Recently introduced dry electrodes with rigid metal pins overcome most of these problems; however, their rigidity causes discomfort and pain. This paper presents dry electrodes offering high user comfort, since they are fabricated from EPDM rubber containing various additives for optimum conductivity, flexibility and ease of fabrication. The electrode impedance is measured on phantoms and human skin. After optimization of the polymer composition, the skin-electrode impedance is only similar to 10 times larger than that of gel electrodes. Therefore, these electrodes are directly capable of recording strong biopotential signals such as ECG while for low-amplitude signals such as EEG, the electrodes need to be coupled with an active circuit. EEG recordings using active polymer electrodes connected to a clinical EEG system show very promising results: alpha waves can be clearly observed when subjects close their eyes, and correlation and coherence analyses reveal high similarity between dry and gel electrode signals. Moreover, all subjects reported that our polymer electrodes did not cause discomfort. Hence, the polymer-based dry electrodes are promising alternatives to either rigid dry electrodes or conventional gel electrodes

Pulse Arrival Time Segmentation Into Cardiac and Vascular Intervals - Implications for Pulse Wave Velocity and Blood Pressure Estimation

Objective: This study demonstrates a novel method for pulse arrival time (PAT) segmentation into cardiac isovolumic contraction (IVC) and vascular pulse transit time to approximate central pulse wave velocity (PWV). Methods: 10 subjects (38 +/- 10 years, 121 +/- 12 mmHg SBP) ranging from normotension to hypertension were repeatedly measured at rest and with induced changes in blood pressure (BP), and thus PWV. ECG was recorded simultaneously with ultrasound-based carotid distension waveforms, a photoplethysmography-based peripheral waveform, noninvasive continuous and intermittent cuff BP. Central PAT was segmented into cardiac and vascular time intervals using a fiducial point in the carotid distension waveform that reflects the IVC onset. Central and peripheral PWVs were computed from (segmented) intervals and estimated arterial path lengths. Correlations with Bramwell-Hill PWV, systolic and diastolic BP (SBP/DBP) were analyzed by linear regression. Results: Central PWV explained more than twice the variability (R-2) in Bramwell-Hill PWV compared to peripheral PWV (0.56 vs. 0.27). SBP estimated from central PWV undercuts the IEEE mean absolute deviation threshold of 5 mmHg, significantly lower than peripheral PWV or PAT (4.2 vs. 7.1 vs. 10.1 mmHg). Conclusion: Cardiac IVC onset signaled in carotid distension waveforms enables PAT segmentation to obtain unbiased vascular pulse transit time. Corresponding PWV estimates provide the basis for single-site assessment of central arterial stiffness, confirmed by significant correlations with Bramwell-Hill PWV and SBP. Significance: In a small-scale cohort, we present proof-of-concept for a novel method to estimate central PWV and BP, bearing potential to improve the practicality of cardiovascular risk assessment in clinical routines

Pulse Arrival Time Segmentation Into Cardiac and Vascular Intervals - Implications for Pulse Wave Velocity and Blood Pressure Estimation

Objective: This study demonstrates a novel method for pulse arrival time (PAT) segmentation into cardiac isovolumic contraction (IVC) and vascular pulse transit time to approximate central pulse wave velocity (PWV). Methods: 10 subjects (38 +/- 10 years, 121 +/- 12 mmHg SBP) ranging from normotension to hypertension were repeatedly measured at rest and with induced changes in blood pressure (BP), and thus PWV. ECG was recorded simultaneously with ultrasound-based carotid distension waveforms, a photoplethysmography-based peripheral waveform, noninvasive continuous and intermittent cuff BP. Central PAT was segmented into cardiac and vascular time intervals using a fiducial point in the carotid distension waveform that reflects the IVC onset. Central and peripheral PWVs were computed from (segmented) intervals and estimated arterial path lengths. Correlations with Bramwell-Hill PWV, systolic and diastolic BP (SBP/DBP) were analyzed by linear regression. Results: Central PWV explained more than twice the variability (R-2) in Bramwell-Hill PWV compared to peripheral PWV (0.56 vs. 0.27). SBP estimated from central PWV undercuts the IEEE mean absolute deviation threshold of 5 mmHg, significantly lower than peripheral PWV or PAT (4.2 vs. 7.1 vs. 10.1 mmHg). Conclusion: Cardiac IVC onset signaled in carotid distension waveforms enables PAT segmentation to obtain unbiased vascular pulse transit time. Corresponding PWV estimates provide the basis for single-site assessment of central arterial stiffness, confirmed by significant correlations with Bramwell-Hill PWV and SBP. Significance: In a small-scale cohort, we present proof-of-concept for a novel method to estimate central PWV and BP, bearing potential to improve the practicality of cardiovascular risk assessment in clinical routines

BCAP31-related syndrome: The first de novo report

Pathogenic variants in the BCAP31 gene have recently been associated with a severe congenital neurological phenotype, named DDCH after its key features: deafness, dystonia and central hypomyelination. BCAP31 is located at the Xq28 chromosomal region and only male individuals are currently known to be affected, the pathogenic variant being usually transmitted by healthy mothers. Here, we describe a three-year-old male child referred for severe developmental delay, failure to thrive, hearing loss and dyskinetic movements. After a conventional diagnostic workflow, including a normal array-CGH, a tentative diagnosis of dyskinetic cerebral palsy was retained. Clinical exome sequencing in the trio identified a small intragenic deletion in exon 8 of BCAP31, c.709_721del (p.Val237Trpfs*69), originated de novo and not previously reported. Based on the ACMG variant classification, this variant is predicted to be 'likely pathogenic'. Given the consistent phenotypical overlap with the subjects already ascertained with DDCH, we considered this variant to be clinically relevant for this child and causative of his condition.status: publishe

Unravelling the impact of COVID-19 on mental health : a scoping review on traumatogenic events using the phases of response to disaster model

Background: Disease outbreaks such as the COVID-19 pandemic give rise to high levels of psychological distress in people worldwide. Since this is the first pandemic of its kind, the best available evidence is needed on what psychological needs could be expected during and after the pandemic. Objectives: In this scoping review existing research on traumatogenic events is examined in order to identify the potential impact on mental health of the COVID pandemic. The research findings are organized using the the phases of disaster response model. Results: A total of 34 longitudinal studies, 2 studies with multiple waves of data collection and 92 cross-sectional studies met the inclusion criteria. The studies included in this scoping review could be classified as: 87 studies on COVID-19, 2 on SARS, 19 on wars, 19 on terrorist attacks and 1 on a nuclear accident. Results indicate that stress, anxiety, depressive symptoms, insomnia, denial, anger, grief and fear can be anticipated as common reactions. The longer a pandemic continues, the higher the psychological strain is expected to be. Conclusions: The phases of response to disaster model offers a valid frame to unravel the impact of the pandemic on mental health over time. Specific attention must be given to vulnerable groups, whereby specific risk factors include age, gender, pre-existing mental health problems, healthcare profession, migration background, isolation and low socio economic status. However, these may change over time, and a delayed manifestation of psychosocial problems needs to be considered too. Mental health governance is, therefore, warranted throughout and even up to 6 months after the pandemic

Artefact Detection in Impedance Pneumography Signals: A Machine Learning Approach

Impedance pneumography has been suggested as an ambulatory technique for the monitoring of respiratory diseases. However, its ambulatory nature makes the recordings more prone to noise sources. It is important that such noisy segments are identified and removed, since they could have a huge impact on the performance of data-driven decision support tools. In this study, we investigated the added value of machine learning algorithms to separate clean from noisy bio-impedance signals. We compared three approaches: a heuristic algorithm, a feature-based classification model (SVM) and a convolutional neural network (CNN). The dataset consists of 47 chronic obstructive pulmonary disease patients who performed an inspiratory threshold loading protocol. During this protocol, their respiration was recorded with a bio-impedance device and a spirometer, which served as a gold standard. Four annotators scored the signals for the presence of artefacts, based on the reference signal. We have shown that the accuracy of both machine learning approaches (SVM: 87.77 ± 2.64% and CNN: 87.20 ± 2.78%) is significantly higher, compared to the heuristic approach (84.69 ± 2.32%). Moreover, no significant differences could be observed between the two machine learning approaches. The feature-based and neural network model obtained a respective AUC of 92.77±2.95% and 92.51±1.74%. These findings show that a data-driven approach could be beneficial for the task of artefact detection in respiratory thoracic bio-impedance signals

Polymer-based dry electrodes for high user comfort ECG/EEG measurements

Conventional ECG and EEG gel electrodes are widely used in health care applications. These electrodes deliver high-quality signals due to their low impedance, but they have important drawbacks, such as time-consuming electrode set-up for EEG followed by a painful removal, skin irritation by the gel, signal degradation due to drying of the gel, etc. To solve this, various types of dry electrodes attract attention last years. Hard metal dry electrodes show low impedance, but most are not comfortable for the patient. Flexible polymer-based electrodes are presented in this work to avoid the disadvantages of gel electrodes while significantly improving user comfort. Different additives are mixed in these polymers and optimized to improve various relevant properties. An important electrode property is low impedance, which directly affects signal quality and influences the sensitivity to motion artifacts. The polymer composition influences also the mechanical properties, as well as the material flow during molding and hence the electrode fabrication yield. Moreover, various electrode shapes are tested to achieve appropriate mechanical properties and increase user comfort. For ECG & EEG applications, the best performing dry electrodes are selected and results are compared with wet electrode signals .status: publishe