Complex gastroschisis requires timely intervention to protect the fetal intestine from inflammation and strangulation and avoid viscero-abdominal disproportion (VAD). Earlier results in ovine models for the fetoscopic management of gastroschisis highlight the benefits of minimally invasive coverage; yet specialized instruments appear to be needed for better procedural execution. The aim of this study was to create and validate a first prototype instrument for the prenatal covering of the protruded intestines in gastroschisis. A 7-mm diameter fetoscopic instrument was designed to hold and deploy a protective bag over the gastroschisis defect after suture fixation to the fetus. An inanimate model was used to evaluate the instrument’s usability and effectiveness: Eleven participants performed bag placement and suturing both with and without the prototype, enabling a comparative assessment of procedural performance. Statistical analysis was conducted to evaluate the duration of the procedure, while product deficiencies were qualitatively assessed using a Likert-scale questionnaire. The overall usability of the prototype was further evaluated using the system usability scale (SUS). The prototype consistently enhanced bag handling and positioning. Median procedural time slightly increased from 118.5 to 120.5 s with the prototype (p = 0.98), without affecting the overall procedural efficiency. Usability assessments using the SUS (median score: 67.95) and the Likert scale indicated a generally favorable response. Importantly, usability ratings were consistent regardless of participants’ prior experience in minimally invasive surgery (p = 0.43), underscoring the intuitive design and ease of adoption of the prototype. Despite a minor increase in procedural time, the prototype enabled secure bag placement and demonstrated moderate usability across all participants. This is particularly relevant for fetal procedures requiring amnioinfusion, as opposed to partial amniotic carbon dioxide insufflation (PACI) used in the inanimate model. However, further mechanical refinement is warranted to enhance performance and address usability concerns.

Step width is an important clinical motor marker for gait stability assessment. While laboratory-based systems can measure it with high accuracy, wearable solutions based on inertial measurement units do not directly provide spatial information such as distances. Therefore, we propose a magnetic estimation approach based on a pair of shank-worn magnetoelectric (ME) sensors. In this pilot study, we estimated the step width of eight healthy participants during treadmill walking and compared it to an optical motion capture (OMC) reference. In a direct comparison with OMC markers attached to the magnetic system, we achieved a high estimation accuracy in terms of the mean absolute error (MAE) for step width (≤1 cm) and step width variability (<0.1 cm). In a more general comparison with heel-mounted markers during the swing phase, the standard deviation of the error (<0.5 cm, measure for precision), the step width variability estimation MAE (<0.2 cm) and the Spearman correlation (>0.88) of individual feet were still encouraging, but the accuracy was negatively affected by a constant proxy bias (3.7 and 4.6 cm) due to the different anatomical reference points used in each method. The high accuracy of the system in the first case and the high precision in the second case underline the potential of magnetic motion tracking for gait stability assessment in wearable movement analysis.

Existing approaches to non-invasive electroanatomical mapping face a fundamental challenge: accurately representing the continuous propagation velocities crucial for cardiac arrhythmia localization. Current methods either sacrifice precision by using discrete delays or require computationally intensive biophysical models that limit clinical applicability. We investigated interconnected all-pass filter networks as a novel middle ground that enables continuous, differentiable representation of cardiac propagation velocities while maintaining computational tractability. Through systematic analysis of these networks' fundamental properties and scaling behavior, we demonstrate successful gradient-based optimization of propagation velocities in networks of up to 50 filters and 2D arrangements of 5 x 5 voxels using magnetocardiographic measurements, while identifying critical scaling challenges in more complex geometries. Our experiments establish that reliable convergence requires at least 32-48 magnetic sensors operating below a noise threshold root of approximately 7pT/root Hz. . Runtime analysis shows linear computational scaling with system size, with GPU implementations achieving up to 50 x acceleration over CPU versions, processing a realistic cardiac model with about 30 000 voxels in under 5 s per epoch. These findings establish the theoretical feasibility of all-pass filter networks for cardiac propagation velocity modeling while identifying practical implementation requirements for clinical applications. This approach could reduce patient risks by eliminating invasive catheterization procedures and enable longitudinal studies and research applications not feasible with current invasive methods.

Motion analysis is of great interest to a variety of applications, such as virtual and augmented reality and medical diagnostics. Hand movement tracking systems, in particular, are used as a human–machine interface. In most cases, these systems are based on optical or acceleration/angular speed sensors. These technologies are already well researched and used in commercial systems. In special applications, it can be advantageous to use magnetic sensors to supplement an existing system or even replace the existing sensors. The core of a motion tracking system is a localization unit. The relatively complex localization algorithms present a problem in magnetic systems, leading to a relatively large computational complexity. In this paper, a new approach for pose estimation of a kinematic chain is presented. The new algorithm is based on spatially rotating magnetic dipole sources. A spatial feature is extracted from the sensor signal, the dipole direction in which the maximum magnitude value is detected at the sensor. This is introduced as the “maximum vector”. A relationship between this feature, the location vector (pointing from the magnetic source to the sensor position) and the sensor orientation is derived and subsequently exploited. By modelling the hand as a kinematic chain, the posture of the chain can be described in two ways: the knowledge about the magnetic correlations and the structure of the kinematic chain. Both are bundled in an iterative algorithm with very low complexity. The algorithm was implemented in a real-time framework and evaluated in a simulation and first laboratory tests. In tests without movement, it could be shown that there was no significant deviation between the simulated and estimated poses. In tests with periodic movements, an error in the range of 1° was found. Of particular interest here is the required computing power. This was evaluated in terms of the required computing operations and the required computing time. Initial analyses have shown that a computing time of 3 μs per joint is required on a personal computer. Lastly, the first laboratory tests basically prove the functionality of the proposed methodology.

Thin-film magnetoelectric (ME) sensors offer a promising potential to measure biomagnetic signals in the near future. Unfortunately, this sensor type shows usually a large cross-sensitivity to all kinds of mechanic distortion due to the resonant structure. In order to overcome this problem several sensor designs have been proposed. Beside these approaches adaptive noise cancellation techniques can be used to reduce the noise coupling while keeping the sensor setup simple. In this contribution reference sensors, realized as piezoelectric cantilevers, are presented and compared to microphones by means of their feasibility to improve the signal-to-noise ratio (SNR) using adaptive cancellation approaches. If a loudspeaker is used as noise source, no crucial differences are measured. But if a vibrator is used as noise source to generate structure-borne noise, the piezoelectric (PE) cantilevers are superior. As the difference of the resonance frequencies between ME and PE sensor is decreased the SNR improvement increases at low excitation levels. In total an SNR improvement over 30 dB can be achieved.