Pre-eclampsia is one of the most common causes of maternal and perinatal death worldwide. It is a hypertensive pregnancy disease with reduced perfusion of numerous organs. The main symptoms of the disease include elevated blood pressure, proteinuria and the associated subcutaneous fluid retention in the fingers, hands and face of the pregnant woman. In this paper a concept of a portable prototype for early-detection of pre-eclampsia is presented. The assembled sensor systems enable portable monitoring of the main symptoms to detect changes at an early stage. The sensor system for determining blood pressure is based on photoplethysmography. The sensor system for detecting subcutaneous fluid retention uses the absorption bands of the fluid when illuminated with near-infrared light. For the validation experiments, finger models made of silicone with different fluid retention levels were produced. The results show a correlation between the measured transmitted light intensity and the fluid retention. The results represent a possibility for the portable measurement of important vital parameters in connection with pre-eclampsia.

Psychological trials, such as behavioural avoidance tests (BAT), are a fundamental part of the phobia therapeutic process.

These usually result in collecting new data about the patient, for instance, observations about the particular behaviour.

In order to link physiological reactions with specific points in time during psychological trials, it is necessary to integrate observation data with data collected automatically by sensors, such as wearable devices.

To this end, this paper introduces FRAME -- a framework for combining real-world events occurring during psychological trials with physiological data collected by wearables.

FRAME consists of three parts, an Observation App, a data integration module and a Virtual Reality (VR) App.

The Observation App captures events and their exact time of occurrence.

The integration module links the observations with the respective physiological data, to allow a much more in-depth analysis of physiological reactions.

The VR App provides a virtual scenario based on the BAT in vivo, thus enabling a BAT in virtuo.

The practical applicability of FRAME is employed and tested within a study comparing behavioural avoidance tests in vivo and in virtuo, assessing patients with arachnophobia.

Introduction

While various models and studies have investigated the simulation and theoretical description of human gait, previous research has not considered irregular situations such as slipping and tripping. However, understanding these situations could be crucial and provide insight into assessing dynamic balance, a factor that is closely linked to the risk of falling. The first step is to investigate the system under normal walking using a participant group that includes people who are

particularly susceptible to an increased risk of falling, such as older adults or people with certain health conditions that have so far been neglected in the literature.

Methods

In this study a control engineering approach was used to estimate the parameters of the human gait system. A total of 32 subjects aged 18 to 79 years, with different body masses and walking speeds, were analyzed. Measurements were conducted on a treadmill with integrated force plates, while participants wore inertial measurement units (IMUs) at lumbar level and were filmed with cameras.

Results

The calculated spring-mass-damping model parameters, including stiffness (𝑘) and damping (𝑐), varied widely among participants, with stiffness ranging from 3.89 to 61.78 kN/m and damping from 0.19 to 2.68 kNs/m. Contrary to previous findings, no linear relationships were observed between

stiffness or damping and velocity, age, or mass. Outliers were identified and related in a plausible way to visual inspection.

Conclusion

In conclusion, our study successfully characterized human walking during periodic excitation for a diverse participant group using a simple control engineering approach, yielding comparable results to previous studies. Our results pave the way for future investigations to analyze the response of an individual participant to irregular gait perturbations.

The unified Parkinson’s disease rating scale, used to monitor the disease progression, is based on visual assessments of motor symptoms. Vocal manifestations of Parkinson’s disease differ from the motor ones, specifically in their rate of change with disease severity. As such, a different scale is needed to provide the voice measures of the disease severity. This study employed a dataset of voice-quality features from repeated recordings of Parkinson’s disease patients. The changes of all voice features across the categories were evaluated using one-way analysis-of-variance and support vector regression. Significant changes and marked non-linearly increasing or decreasing trends were shown for all features, for the three-categories scale. Significant changes and trends were obtained in the 12-categories scale, but only for the mild category and the severe category range of scores. The findings imply a potential for voice-based monitoring for the early and late severity stages of Parkinson’s disease that could be continuously used by patients and provide timely warnings of deterioration.

This paper shows the possibility of using Ultra-wideband (UWB) DW3000 transceivers for noninvasive vital sign monitoring via a transversal propagation method. The transceivers can provide a cheaper, more flexible, and easier-to-apply measurement of vital signs than traditional electrocardiogram (ECG) devices. This will not substitute the common medical use but instead can make vital sign monitoring more accessible in other scenarios. Potential applications beyond clinical settings, like measuring the vital signs of a car driver, can be achieved. The primary focus of this study is the possibility of utilizing inexpensive UWB transceivers for ballistocardiography (BCG) measurements. The vital signs are measured on a small focus group to verify the results on a larger spectrum. A photoplethysmogram (PPG) device is used for reference measurement. The results show a great accuracy of 3 breaths per minute for respiration rate measurement. The heartbeat measurement shows an error mostly within 3 bpm due to the resolution of the proposed setup. Methods for further verification of the results, together with increasing the accuracy and resolution of the setup are proposed.

Hyper-viscoelastic models have been used to characterize large strains coupled with viscosity. In this study, we aimed to model the urethral in-vivo biomechanics through a hyper-viscoelastic implementation. First, we used isotropic 2-parameter Demiray model for identification of urethral tube inflation after refining the values of quasistatic states. Attempting the approach by Holzapfel et. al., the average ratio of the elastic and dynamic modulus was computed to determine the stress contribution of the viscoelastic branches. The values of the parameters were determined after constraining a constant Energy dissipation (generalized maxwell) over range 1s to 100s. For the hyper-viscoelastic comparison implementation, it was observed that the goodness of fit criteria performs good for half of the samples (Adjusted R2>0.95). In some samples, the model is limited to fit ‘S’ shape curves but still performed well. The above identification technique and the hyper-viscoelastic in-silico approaches show that our approach fares optimally for the creep response characterization of the urethra.