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Item type:Publication, Access status: with files , Gender and age-related decline in lower limb standing muscle strength: benchmarking for rehabilitation assessment(Multidisciplinary Digital Publishing Institute (MDPI), 2025-12-22); ; This study aimed to demonstrate a novel sensor-based measuring stand for objective assessment of multi-directional lower limb muscle strength and to establish essential, age- and gender-stratified normative benchmarks. This cross-sectional study measured relative leg strength (N/kg) across six standing movements in 99 healthy, non-professional athletes (males and females aged 20–30, 40–50, and 60–70 years). Results confirmed that men exhibited significantly greater strength than women across all six directions (17% to 35% difference). Furthermore, a marked age-related decline was consistently observed in both sexes, with the largest and most clinically relevant differences (often exceeding 30%) concentrated in the transition to the 60–70-year range. Methodologically, these findings are limited to demonstrating age-related differences rather than longitudinal decline and are specific to an active, healthy cohort. This study demonstrates the sensor-based stand as an efficient, objective tool for comprehensive strength assessment, but its clinical utility is prospective and requires further validation against diverse and pathological patient populations.Publicationtype: Journal Article10 7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , CATO: Wake-Up reCeiver-bAsed communicaTiOn for Batteryless Devices(Multidisciplinary Digital Publishing Institute (MDPI), 2025-11-07); ; ; ; Batteryless devices offer an unparalleled opportunity for long-term, low-maintenance, and sustainable operation. These opportunities are especially attractive in the context of the Internet of Things (IoT). Such devices, however, rely on a stringent energy budget for their operation. As a result, batteryless devices often operate intermittently. Therefore, energy-intensive functionalities such as wireless communication, though valuable in practical applications, are still a significant challenge to realize on such devices. This work proposes wake-up receiver-based solutions for facilitating energy-efficient communication among batteryless, energy-harvesting devices. As a foundation for realizing wireless communication, we introduce BEWARE-MAC, a MAC protocol that exploits the capabilities of the underlying WuR to enable efficient message exchanges among batteryless devices. To demonstrate the broadcast capabilities of BEWARE-MAC, we propose WEND, a WuR-based neighbor discovery protocol that can operate on intermittently powered, batteryless devices. Finally, we present an evaluation of the proposed protocols using both experimental and simulation-based results. Our results suggest that BEWARE-MAC can improve the goodput of energy-constrained devices by up to 61.1%.Publicationtype: Journal Article70 28 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Exploitation of modal superposition toward forced vibration localization in a coupled symmetric oscillator array(Multidisciplinary Digital Publishing Institute (MDPI), 2025-05-14); ; ; In transducer arrays, symmetric grouping of identical elements is often employed to achieve uniform array performance. Such arrays can possess high coupling, preventing localized operation of individual transducers. This paper provides insight into how forced vibration localizes in a symmetric system of coupled oscillators. We use a simple lumped-parameter model of highly coupled oscillators derived from ultrasound transducer arrays. Forced vibration localization can be shown to be inversely related to the coupling strength between the oscillators. The results demonstrate how forced vibration in a coupled symmetric system may localize through modal superposition and how it may be tuned via the spacing of natural frequencies. Breaking the system’s symmetry leads to normal mode localization, which can be shown to affect the forced vibration response. The results reveal a variation in the system’s resonance frequency, attributed to curve veering effects.Publicationtype: Journal Article25 17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , The effect of annotation quality on wear semantic segmentation by CNN(Multidisciplinary Digital Publishing Institute (MDPI), 2024-07-23); ; ; Grossmann, DanielIn this work, we investigate the impact of annotation quality and domain expertise on the performance of Convolutional Neural Networks (CNNs) for semantic segmentation of wear on titanium nitride (TiN) and titanium carbonitride (TiCN) coated end mills. Using an innovative measurement system and customized CNN architecture, we found that domain expertise significantly affects model performance. Annotator 1 achieved maximum mIoU scores of 0.8153 for abnormal wear and 0.7120 for normal wear on TiN datasets, whereas Annotator 3 with the lowest expertise achieved significantly lower scores. Sensitivity to annotation inconsistencies and model hyperparameters were examined, revealing that models for TiCN datasets showed a higher coefficient of variation (CV) of 16.32% compared to 8.6% for TiN due to the subtle wear characteristics, highlighting the need for optimized annotation policies and high-quality images to improve wear segmentation.Publicationtype: Journal Article23 76 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Non-invasive determination of the mass flow rate for particulate solids using microwaves(Multidisciplinary Digital Publishing Institute (MDPI), 2023-12-14); ; This paper presents a novel technique for the mass flow rate determination of particulate solids called the “Sliding Mass Technique”. The mass flow rate is a measure of the mass of a substance that passes through a given cross-sectional area per unit time. Its calculation requires simultaneous detection of the concentration and velocity of the Material Under Test. A novel measurement technique is designed for determining the concentration of the mass flow without the necessity for density evaluation. The mass flow rate is determined by fusing the established concentration results with velocity results obtained from “Microwave Spatial Filtering Velocimetry”. A new metamaterial-based mass flow sensor for particulate solids was designed, realized and measured in an industrial environment. A Software-Defined Radio (Ettus Research<sup>™</sup>’s USRP B210) was utilized as a sensor electronic system for DAQ purposes. A MATLAB app was developed to operate the SDR. Measurements were carried out on-site using a state-of-the-art wood pellet heating system with wood pellets with different moisture contents. The measurement results were found to be in very good agreement with the expected results, which strengthens the feasibility of this newly proposed measurement technique.Publicationtype: Journal Article63 30 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , A comparative study of visual identification methods for highly similar engine tubes in aircraft maintenance, repair and overhaul(Multidisciplinary Digital Publishing Institute (MDPI), 2023-07-28); ; Unique identification of machine parts is critical to production and maintenance, repair and overhaul (MRO) processes in the aerospace industry. Despite recent advances in automating these identification processes, many are still performed manually. This is time-consuming, labour-intensive and prone to error, particularly when dealing with visually similar objects that lack distinctive features or markings or when dealing with parts that lack readable identifiers due to factors such as dirt, wear and discolouration. Automation of these processes has the potential to alleviate these problems. However, due to the high visual similarity of components in the aerospace industry, commonly used object identifiers are not directly transferable to this domain. This work focuses on the challenging component spectrum engine tubes and aims to understand which identification method using only object-inherent properties can be applied to such problems. Therefore, this work investigates and proposes a comprehensive set of methods using 2D image or 3D point cloud data, incorporating digital image processing and deep learning approaches. Each of these methods is implemented to address the identification problem. A comprehensive benchmark problem is presented, consisting of a set of visually similar demonstrator tubes, which lack distinctive visual features or markers and pose a challenge to the different methods. We evaluate the performance of each algorithm to determine its potential applicability to the target domain and problem statement. Our results indicate a clear superiority of 3D approaches over 2D image analysis approaches, with PointNet and point cloud alignment achieving the best results in the benchmark.Publicationtype: Journal Article63 76 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Towards recognition of human actions in collaborative tasks with robots : extending action recognition with tool recognition methods(Molecular Diversity Preservation International, 2023-06-19); ; ; ; This paper presents a novel method for online tool recognition in manual assembly processes. The goal was to develop and implement a method that can be integrated with existing Human Action Recognition (HAR) methods in collaborative tasks. We examined the state-of-the-art for progress detection in manual assembly via HAR-based methods, as well as visual tool-recognition approaches. A novel online tool-recognition pipeline for handheld tools is introduced, utilizing a two-stage approach. First, a Region Of Interest (ROI) was extracted by determining the wrist position using skeletal data. Afterward, this ROI was cropped, and the tool located within this ROI was classified. This pipeline enabled several algorithms for object recognition and demonstrated the generalizability of our approach. An extensive training dataset for tool-recognition purposes is presented, which was evaluated with two image-classification approaches. An offline pipeline evaluation was performed with twelve tool classes. Additionally, various online tests were conducted covering different aspects of this vision application, such as two assembly scenarios, unknown instances of known classes, as well as challenging backgrounds. The introduced pipeline was competitive with other approaches regarding prediction accuracy, robustness, diversity, extendability/flexibility, and online capability.Publicationtype: Journal ArticleScopus© Citations 4 54 99 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Mobile-BAT - A novel ultra-low power wildlife tracking system(Multidisciplinary Digital Publishing Institute (MDPI), 2023-05-31); ; ; ; We introduce a novel ultra-low power system for tracking animal movements over long periods with an unprecedented high-temporal-resolution. The localization principle is based on the detection of cellular base stations using a miniaturized software-defined radio, weighing 2.0 g, including the battery, and having a size equivalent to two stacked 1-euro cent coins. Therefore, the system is small and lightweight enough to be deployed on small, wide-ranging, or migrating animals, such as European bats, for movement analysis with an unprecedented spatiotemporal resolution. The position estimation relies on a post-processing probabilistic RF pattern-matching method based on the acquired base stations and power levels. In several field tests, the system has been successfully verified, and a run-time of close to one year has been demonstrated.Publicationtype: Journal Article56 59 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Sensor fusion for the robust detection of facial regions of neonates using neural networks(Multidisciplinary Digital Publishing Institute (MDPI), 2023-05-19); ; ; ; The monitoring of vital signs and increasing patient comfort are cornerstones of modern neonatal intensive care. Commonly used monitoring methods are based on skin contact which can cause irritations and discomfort in preterm neonates. Therefore, non-contact approaches are the subject of current research aiming to resolve this dichotomy. Robust neonatal face detection is essential for the reliable detection of heart rate, respiratory rate and body temperature. While solutions for adult face detection are established, the unique neonatal proportions require a tailored approach. Additionally, sufficient open-source data of neonates on the NICU is lacking. We set out to train neural networks with the thermal-RGB-fusion data of neonates. We propose a novel indirect fusion approach including the sensor fusion of a thermal and RGB camera based on a 3D time-of-flight (ToF) camera. Unlike other approaches, this method is tailored for close distances encountered in neonatal incubators. Two neural networks were used with the fusion data and compared to RGB and thermal networks. For the class “head” we reached average precision values of 0.9958 (RetinaNet) and 0.9455 (YOLOv3) for the fusion data. Compared with the literature, similar precision was achieved, but we are the first to train a neural network with fusion data of neonates. The advantage of this approach is in calculating the detection area directly from the fusion image for the RGB and thermal modality. This increases data efficiency by 66%. Our results will facilitate the future development of non-contact monitoring to further improve the standard of care for preterm neonates.Publicationtype: Journal Article71 76 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Acoustic backscatter communication and power transfer for batteryless wireless sensors(Multidisciplinary Digital Publishing Institute (MDPI), 2023-03-30); Sensors for industrial and structural health monitoring are often in shielded and hard-to-reach places. Acoustic wireless power transfer (WPT) and piezoelectric backscatter enable batteryless sensors in such scenarios. Although the low efficiency of WPT demands power-conserving sensor nodes, backscatter communication, which consumes near-zero power, has not yet been combined with WPT. This study reviews the available approaches to acoustic WPT and active and passive acoustic through-metal communication. We design a batteryless and backscattering tag prototype from commercially available components. Analysis of the prototypes reveals that low-power hardware poses additional challenges for communication, i.e., unstable and inaccurate oscillators. Therefore, we implement a software-defined receiver using digital phase-locked loops (DPLLs) to mitigate the effects of oscillator instability. We show that DPLLs enable reliable backscatter communication with inaccurate clocks using simulation and real-world measurements. Our prototype achieves communication at 2 kBs⁻¹ over a distance of 3 m. Furthermore, during transmission, the prototype consumes less than 300 μW power. At the same time, over 4 mW of power is received through wireless transmission over a distance of 3 m with an efficiency of 2.8%.Publicationtype: Journal ArticleScopus© Citations 2 95 165