Gnostic functions constitute an important component of higher cortical processing, integrating visual, auditory, and tactile modalities to support bodily perception and spatial awareness. One of the established tools for evaluating these functions is the Petrie Test, a method that has remained largely unchanged since its introduction. Although clinically valuable, the traditional test depends on subjective manual readings, which reduce repeatability, extend evaluation time, and preclude automated data handling. This limitation underscores the need for a modernized approach that preserves the original methodology while enabling objective, digitized output. This paper presents Haptic Embed, an embedded, wireless, and fully automated redesign of the diagnostic prism used in the Petrie Test. The system incorporates a membrane potentiometer for linear position sensing, an ESP32-based control unit, onboard signal processing, and Bluetooth transmission to a desktop application. The proposed system was further evaluated through a clinical study, the objective of which was to assess gnostic functions using the modernized Petrie Test device, with a secondary aim of comparing athletes and non-athletes. Fifty participants were tested (athletes: n=30; non-athletes: n=20). Two assessments were conducted to evaluate somatognosis: the Petrie Test, which utilized a sensor-equipped prism, and a manual Pelvic Size Test. The testing methodology remained identical to the original; only the classic prism was replaced with the modernized version, preserving all dimensions and proportions. Results showed that average deviations of perceived width remained within the normal clinical range (±6 mm), with no statistically significant differences between athletes and non-athletes. These findings indicate that established assessment methods can be effectively enhanced with embedded technologies without altering their diagnostic principles. By reducing investigator dependency and streamlining clinical workflow, the proposed solution provides a reliable foundation for future neurodiagnostic and physiotherapeutic applications.

This research addresses the long-term measurement of environmental data in geographically remote areas and an energy-optimized method of storing data on a storage medium. For this purpose, we have developed our measurement module Advanced Data Logger (ADL). In terms of connectivity, the module operates in three modes: 1) offline-when measured data is primarily stored on the storage medium; 2) Internet of Things (IoT) ready-measured data is stored on the storage medium and sent to the remote server in defined batches; and 3) online mode-when measured data is preferably sent to the remote server immediately after measurement. The design aims to minimize the module's power consumption so that the autonomous operating time is close to one year. As part of the design, the Simple File System (simpleFS) software module is designed for the role of a simple file system (FS) optimized to minimize I/O operations. Its other feature in data storage is the automatic normalization of the data transmitted from the attached sensors. The last part of the design is the AdlReader software solution, used to configure the hardware (HW) module and to retrieve the measured data files. We verified the correct operation of the ADL module along with nine sensors built in a vertical soil temperature profile probe in experimental installation and operation for two months. According to the requirements for our solution, the expected operation time of the ADL module is 9-12 months.

A sufficient oxygen supply of the fetus is necessary for a proper development of the organs. Transabdominal fetal pulse oximetry is a method that allows to measure the oxygenation of the fetal blood non-invasively by placing the light sources and photodetectors on the belly of the pregnant woman. The shape of the measured fetal pulse wave is needed to extract parameters for the estimation of the oxygen saturation. This work presents an extension of our previously presented signal processing strategy that allows to extract an average shape of the fetal pulse wave from noisy mixed photoplethysmograms (PPG) with dominating maternal and very weak fetal signal components. An adaptive noise canceller and a comb filter are used to suppress the maternal component. The quality of the resulting fetal signal is sufficient to identify single pulse waves in time domain. Further processing demonstrates the extraction of the mean shape of a single fetal pulse wave by synchronous averaging of several detected pulses. The method is evaluated with different datasets of several simulated and synthetic signals measured with a tissue mimicking phantom. The feasibility of the approach is demonstrated by preparing the mixed PPGs to perform fetal pulse oximetry in future studies. However, clinical measurements are needed to finally evaluate the proposed system beyond synthetic datasets.

The fetal pulse curve can be captured by placing light sources and detectors on the belly of a pregnant woman. Following the principle of reflection pulse oximetry, the light emitted into the abdomen is modulated by pulsing maternal and fetal arteries. The acquired signal is a mixture of a weak fetal and a dominating maternal photoplethysmogram (PPG). A first step towards estimation of the fetal oxygen level is the reconstruction of the purely fetal signal in time domain. As already shown in a former work, comb filters are well suited for the task, in case the fetal heart rate is known. In this work we extend the method by utilizing an adaptive noise canceller (ANC) to estimate the fetal pulse rate for comb filter design. Synthetic test signals with constant and time variable pulse rates are generated in order to achieve reproducible conditions. The ANC is fed by the mixed PPG and the maternal reference signal to reduce the dominant maternal components. The fetal pulse rate is computed by evaluating peaks in the resulting signal in time and frequency domain. The findings are used for comb filter design. It is shown that the extraction of the fetal pulse curve from the synthetic mixed PPGs by using the proposed strategy is promising. Clinical test measurements are the next step for evaluation.

Non-invasive fetal pulse oximetry is the application of reflection pulse oximetry to the abdomen of a pregnant woman. Light sources and detectors areplaced on the belly. Emitted photons travel through maternal and fetal tissue and back to the detectors. The captured photoplethysmogram (PPG) is a complex mixture of the maternal and fetal pulse curve. A purely fetal PPG in time domain is needed to estimate the oxygen level of the unborn child. In this work we describe the application of comb filters to separate the fetalfrom the maternal signal. Finite element simulations and phantom measurements are utilized to generate and measure synthetic signals at different heart rates and noise levels. Comb filters with peak frequencies matched to the fetal heart rate are applied to the mixed PPGs. The filtered signals prove that the extraction of the fetal signal is sufficient even at a distance between the maternal and the fetal signal magnitudes of around 80 dB. The resulting signal quality is sufficient for beat to beat analysis and feature extraction in the time domain. We conclude that comb filtering is a suitable signal separation method for non-invasive fetal pulse oximetry.

Searching for medical equipment in hospitals produces high costs. However, it is necessary to check each medical device periodically. Wireless systems in a medical environment must comply with the legal limits for electromagnetic interference (EMI). This work presents a tagging system for real time localization of tagged equipment respecting that some medical devices are very sensitive for EMI. Therefor, every room is equipped with a base station and a star-shaped 2.4 GHz wireless network topology, which conforms with the latest legislative requirements for the EC and US market. Considering that, the device tags consist of a compact IEEE 802.15.4 ZigBit transceiver module with an adapted and extended stack. Furthermore, the device tags are equipped with sensors for detecting manipulation and motion. The base stations are connected to the server via wired TCP/IP network with Power over Ethernet (PoE), which reduces the radio traffic and considerably simplifies communication. Virtual floor plans in the dashboard software visualize the actual positions of the medical devices. The user is able to locate either a single device by its name or a list of all devices in a ward. Using two AAA batteries the device tags have an operation time of 24 months, wherein they can be in motion for 7.75 percent. The web-based dashboard software gants the medical staff an easy access via computer or mobile device. In addition, the dashboard is able to access the SAP database of the hospital for detailed information about the medical device.

Transabdominal fetal pulse oximetry is an approach to measure oxygen saturation of the unborn child non-invasively. The principle of pulse oximetry is applied to the abdomen of a pregnant woman, such that the measured signal includes both, the maternal and the fetal pulse curve. One of the major challenges is to extract the shape of the fetal pulse curve from the mixed signal for computation of the oxygen saturation. In this paper we analyze the principle kind of connection of the fetal and maternal pulse curves in the measured signal. A time varying finite element model is used to rebuild the basic measurement environment, including a bulk tissue and two independently pulsing arteries to model the fetal and maternal blood circuit. The distribution of the light fluence rate in the model is computed by applying diffusion equation. From the detectors we extracted the time dependent fluence rate and analyzed the signal regarding its components. The frequency spectra of the signals show peaks at the fetal and maternal basic frequencies. Additional signal components are visible in the spectra, indicating multiplicative coupling of the fetal and maternal pulse curves. We conclude that the underlying signal model of algorithms for robust extraction of the shape of the fetal pulse curve, have to consider additive and multiplicative signal coupling.

Transabdominal fetal pulse oximetry is a method to estimate the state of oxygenation of a fetus in-utero, utilizing the principle of reflection pulse oximetry. The extraction of fetal related information from a mixed fetal-maternal signal is elementary. Minimizing the ratio of purely maternal components of the signal at the detector side obviously facilitates signal separation. In this paper we analyze the influence of tissue geometries to the fluence composition at the surface of the abdomen. Monte-Carlo method is used to compute photon propagation in spherical layered tissue models. Spatial fluence distributions at the surface of the models are visualized and discussed. Our results show the characteristic effects of the distance between the fetus and the surface and the radius of the abdomen to the fluence composition at the detector. Further, the simulations indicate suitable source-detector configurations considering various anatomical conditions. We conclude that an adoption of the source-detector configuration to the individual tissue geometry at hand is necessary to achieve a proper signal composition and quality. Utilizing simulations for sensor design enhances the understanding of photon distributions in complex tissue geometries and supports a successful implementation of transabdominal fetal pulse oximetry.