Search

Background: Heart rate (HR) is a critical biomarker that provides insights into overall health, stress levels, and the autonomic nervous system. Pulse wave signals contain valuable information about the cardiovascular system and heart status. However, signal acquisition in wearables poses challenges, particularly when using electrical sensors, due to factors like the distance from the heart, body movement, and suboptimal electrode placement. Methods: Electrical bioimpedance (EBI) measurements using bipolar and tetrapolar electrode systems were employed for pulse wave signal acquisition from the wrist in both perpendicular and distal configurations. Signal preprocessing techniques, including baseline removal via Hankel matrix methods, normalization, cross-correlation, and peak detection, were applied to improve signal quality. This study describes the combination of sensor-level signal acquisition and processing for accurate wearable HR estimation. Results: The bipolar system was shown to produce larger ΔZ(t), while the tetrapolar system demonstrated higher sensitivity. Distal placement of the electrodes yielded greater ΔZ(t) (up to 0.231 Ω) when targeting both wrist arteries. Bandpass filtering resulted in a better signal-to-noise ratio (SNR), achieving 3.6 dB for the best bipolar setup and 4.8 dB for the tetrapolar setup, compared to 2.6 and 3.3 dB SNR, respectively, with the Savitzky–Golay filter. The custom HR estimation algorithm presented in this paper demonstrated improved accuracy over a reference method, achieving an average error of 1.8 beats per minute for the best bipolar setup, with a mean absolute percentage error (MAPE) of 8%. Conclusions: The analysis supports the feasibility of using bipolar electrode setups on the wrist and highlights the importance of electrode positioning relative to the arteries. The proposed signal processing method, featuring a preprocessing pipeline and HR estimation algorithm, provides a proof-of-concept demonstration for HR estimation from EBI signals acquired at the wrist.

The monitoring of hemodynamic parameters, such as heart rate and blood pressure, provides valuable indications of overall cardiovascular health. It is preferable that such monitoring is non-invasive and in real time via an affordable, compact and small-scale device for maximum convenience. Numerous literature sources have exploited derivations of these parameters from photoplethysmogram (PPG) and electrical bioimpedance (EBI) signal measurements through the use of calculation algorithms of varying complexity. Compared to electrocardiogram (ECG), these measurement techniques have a merit of well-established practices of designing a wearable device that could conveniently be put on a wrist. The current paper provides a comprehensive review on the use of PPG and EBI measurement techniques in the context of hemodynamic parameter monitoring using a wearable device. A special emphasis is placed on the most basic hemodynamic parameter—heart rate—describing different algorithms of heart rate detection and monitoring. The last section provides an overview of commercially available and in-home wearable device technologies based on PPG and EBI measurements, their design challenges, and future prospects.

Bioimpedance monitoring is an increasingly important non-invasive technique for assessing physiological parameters such as body composition, hydration levels, heart rate, and breathing. However, sensor signals obtained from real-world experimental conditions invariably contain noise, which can significantly degrade the reliability of the derived quantities. Therefore, it is crucial to evaluate the quality of measured signals to ensure accurate physiological parameter values. In this study, we present a novel wrist-worn wearable device for bioimpedance monitoring, and propose a method for estimating signal quality for sensor signals obtained on the device. The method is based on the continuous wavelet transform of the measured signal, identification of wavelet ridges, and assessment of their energy weighted by the ridge duration. We validate the algorithm using a small-scale experimental study with the wearable device, and explore the effects of variables such as window size and different skin/electrode coupling agents on signal quality and repeatability. In comparison with traditional wavelet-based signal denoising, the proposed method is more adaptive and achieves a comparable signal-to-noise ratio.

Health monitoring of structures operating in ambient environments is performed through operational modal analysis, where the identified modal parameters, such as resonant frequencies, damping ratios and operation deflection shapes, characterize the state of structural integrity. The current study shows that, first, time-frequency methods, such as continuous wavelet transform, can be used to identify these parameters and may even provide a large amount of such data, increasing the reliability of structural health monitoring systems. Second, the identified resonant frequencies and damping ratios are used as features in a damage-detection scheme, utilizing the kernel density estimate (KDE) of an underlying probability distribution of features. The Euclidean distance between the centroids of the KDEs, at reference and in various other cases of structural integrity, is used as an indicator of deviation from reference. Validation of the algorithm was carried out in a vast experimental campaign on glass fibre-reinforced polymer samples with a cylindrical shell structure subjected to varying degrees of damage. The proposed damage indicator, when compared with the well-known Mahalanobis distance metric, yielded comparable damage detection accuracy, while at the same time being not only simpler to calculate but also able to capture the severity of damage.

This study determines the effectiveness and suitability of acoustic emission in order to monitor the structural health condition of railway pre-stressed concrete sleepers since the acoustic emission sensing provides effective means for detecting cracking events and quantifying the crack density. The aim of this study is two-fold. First, we establish a novel acoustic emission source separation that offers the possibility for analyzing the content of each source separately. This study is thus the first to demonstrate that these sources can be separated from each other by employing a classification algorithm based on decision trees. Hence, a technically sound decision can be made regarding the severity of the damage and appropriate measures can be taken. Second, the paper presents a new method for compressing the essential acoustic emission information of the loaded structure for further post-processing. Data compression of 70 % with respect to the full set of features is achieved through the elimination of those acoustic emission signatures that yield the largest mutual correlation with other signatures. The reduced set of acoustic emission signatures (only two uncorrelated features) still possesses the essential information of structural health of the structure of interest at a cost of a relatively small drop in classification accuracy from around 96% to 84%. The proposed method is validated experimentally on full-scale pre-stressed concrete sleepers under positive and negative bending moment configurations under static three-point bending tests, which correspond to anticipated failure modes at rail seats by industry.

Fiber Bragg grating (FBG) optical sensors are state-of-the-art technology that can be integrated into the road structure, providing real-time traffic-induced strain readings and ensuring the monitoring of the road’s structural health. By implementing specific FBG sensors, it is possible to detect each vehicle’s axle count and the induced strain changes in the road structure. In this study, FBG sensors are embedded at the top of the 240-mm-thick cement-treated reclaimed asphalt pavement mixture layer of the road (specifically, 25 mm deep within the road). Optical sensors’ signal interrogation units are used to measure the strain and temperature and collect data of the road’s passing vehicles, starting from passenger cars that have two axles and up to heavy trucks that have six axles. Passenger cars with 2 axles generate a typical (90% events) strain of 0.8–4.1 μm/m, the 2-axle minibus 5.5–8.5 μm/m, 2–3-axle trucks 11–26 μm/m, but 4–6-axle trucks 14–36 μm/m per each axle. A large number of influencing parameters determine the pavement design leading to the great uncertainty in the prediction of the strain at the boundary between the asphalt surface and cement-treated base layers. Real-time strain and temperature measurements help to understand the actual behavior of the pavement structure under an applied load, thus assisting in validating the proposed pavement design.

Sexual dysfunction in multiple sclerosis (MS) is a significant, but often underestimated and overlooked suffering. Interventions to treat sexual dysfunction in MS are rare. The relation between sexual dysfunction in MS and psychological as well as neuropsychological aspects is evident. However, this field of research remains markedly underdeveloped in this severe chronic illness. The aim of this scoping review is to describe the relevant knowledge in this area and to identify psychological interventions to treat sexual dysfunctions in MS.A scoping review was conducted to answer the following questions: (1) Which psychological and neuropsychological factors impact on sexual dysfunction in MS and vice versa? (2) What kind of psychological interventions aiming to improve sexual dysfunctions in MS are available? A comprehensive search and review of MEDLINE, PsycINFO, and CINAHL was completed by using a recent methodological framework for scoping reviews.23 publications covering a total of 13,259 people with MS and 532 healthy controls were identified. Sexual dysfunction was found to be very common in MS and there is an obvious relation to psychological disorders as e.g. depression and anxiety and also to psychological aspects as partner relationship and quality of life. The relation between sexual dysfunction in MS and neuropsychological impairment has only rarely been studied and no clear results were found. Only two studies were identified, assessing the effectiveness of psychological intervention studies on sexual dysfunction in people with MS, and a third study presenting a secondary analysis of a study targeting depression. All three studies reported significant improvements in sexual dysfunction as well as partly in psychological variables.There is a pressing need for the development and adequate evaluation of psychological interventions for sexual dysfunctions in MS. In addition, sexual dysfunction and its impact on psychological wellbeing should be more focussed in clinical care.This review is registered with PROSPERO; Registration number: CRD42016033066.

Railway prestressed concrete sleepers are a structural and safety-critical component in railway tracks. [...]