From wires to waves, a novel sensor system for in vivo pressure monitoring.

Pressure monitoring in various organs of the body is essential for appropriate diagnostic and therapeutic purposes. In almost all situations, monitoring is performed in a hospital setting. Technological advances not only promise to improve clinical pressure monitoring systems, but also engage toward the development of fully implantable systems in ambulatory patients. Such systems would not only provide longitudinal time monitoring to healthcare personnel, but also to the patient who could adjust their way-of-life in response to the measurements. In the past years, we have developed a new type of piezoresistive pressure sensor system. Different bench tests have demonstrated that it delivers precise and reliable pressure measurements in real-time. The potential of this system was confirmed by a continuous recording in a patient that lasted for almost a day. In the present study, we further characterized the functionality of this sensor system by conducting in vivo implantation experiments in nine female farm pigs. To get a step closer to a fully implantable system, we also adapted two different wireless communication solutions to the sensor system. The communication protocols are based on MICS (Medical Implant Communication System) and BLE (Bluetooth Low Energy) communication. As a proof-of-concept, implantation experiments in nine female pigs demonstrated the functionality of both systems, with a notable technical superiority of the BLE.

Integrated software for multi-dimensional analysis of motion using tracking, electrophysiology, and sensor signals.

Tracking followed by analysis of specific point-of-interest from conventional or high-speed video recordings have been widely used for decades in various scientific disciplines such as sport, physiotherapy, and behavioral science. Another method used to characterize movement in 3D involves the use of motion capture systems, which produce files containing a collection of 3D-coordinates and corresponding timestamps. When studying animal or human movement, combining motion tracking with other recording methods-like monitoring muscle activity or sensor signals-can yield valuable insights. However, manual analysis of data from these diverse sources can be time-consuming and prone to errors. To address this issue, this article introduces a new, free, and open-source software developed in MATLAB. This software can be used as-is, or developed further to meet specific requirements. Once the coordinates are imported, multiple tools can be used for data preprocessing, such as to correct mistakes that may have occurred during tracking because of software errors or suboptimal video quality. In addition, the software can import coordinates from multiple cameras and combine them into a unified data series. With these inputs, the software can automatically calculate kinematic parameters and descriptive statistics, generate 2D and 3D animations, and analyze gait cycles, enabling swift and accurate analysis of multidimensional motion data. Moreover, the software can import electrophysiology traces and sensor signals, which can be filtered, rectified, smoothed, and correlated with the kinematic data in various ways. Thanks to its user-friendly graphical user interface, the software is easy to navigate and can be used to analyze complex movements without any need for coding skills. This versatile tool is well-suited for a wide range of experimental contexts, making it a valuable resource for researchers across diverse scientific disciplines.