FB Technik
Filtern
Dokumenttyp
Volltext vorhanden
- ja (14)
Gehört zur Bibliographie
- nein (14) (entfernen)
Schlagworte
- Elektrode (2)
- Flüssigkristalline Polymere (2)
- Parkinson-Krankheit (2)
- Rauigkeit (2)
- electrode model (2)
- surface roughness (2)
- Algorithmus (1)
- Astrozyt (1)
- BEV (1)
- Bewegung (1)
- Bewegungsstörung (1)
- Biaxial fiber orientation (1)
- Datenausgabe (1)
- Datensatz (1)
- Depression (1)
- Dielectric analysis (1)
- Dielektrizitätszahl (1)
- Eckenverrundung (1)
- Elektrischer Leiter (1)
- Elektrisches Kabel (1)
- Elektroantrieb (1)
- Elektrokortikogramm (1)
- Elektromobilität (1)
- Elektrophysiologie (1)
- Epoxide (1)
- Essenzieller Tremor (1)
- Evolventenverzahnung (1)
- Faserorientierung (1)
- Flachs (1)
- Flax/epoxy composites (1)
- Ganganalyse (1)
- Gehen (1)
- Geometrie (1)
- Halbleiterlaser (1)
- Helix (1)
- Hirnstimulation (1)
- Hochfrequenz (1)
- Hochverzahnung (1)
- Koaxialkabel (1)
- Konfokale Mikroskopie (1)
- Kopfkürzung (1)
- Kupfer (1)
- Laser (1)
- Laser-Rastermikroskopie (1)
- Latenzzeit <Informatik> (1)
- Magnetische Stimulation (1)
- Maschinelles Lernen (1)
- Maschinelles Sehen (1)
- Messung (1)
- Microstructure flax/epoxy (1)
- Modul (1)
- Monte Carlo simulation (1)
- Monte-Carlo-Simulation (1)
- Mustererkennung (1)
- Nervenkrankheit (1)
- Neuronales Netz (1)
- OLED (1)
- OLED latency (1)
- Organischer Stoff (1)
- Pedografie (1)
- Permutation (1)
- Profilverschiebung (1)
- Psychometrie (1)
- Punktetransfer (1)
- RF attenuation (1)
- Reaktionszeit (1)
- Relative permittivity (1)
- Schrägverzahnung (1)
- Sensor (1)
- Spektroskopie (1)
- Stereokamera (1)
- Stirnrad (1)
- Terahertzbereich (1)
- Tesselation (1)
- Tesselierung (1)
- Transkranielle magnetische Stimulation (1)
- Trochoide (1)
- Unidirectional fiber orientation (1)
- Verbundwerkstoff (1)
- Verdrillung <Elektrotechnik> (1)
- Verschleißprüfung (1)
- Wälzfräsen (1)
- Zahnkopfspiel (1)
- Zahnrad (1)
- Zahnradherstellung (1)
- Zentralnervensystem (1)
- anomalies in permutations (1)
- astrocytes (1)
- charge storage capacity (CSCc) (1)
- coaxial (1)
- cognitive performance assessment (1)
- computer vision (1)
- confocal microscopy (1)
- control systems (1)
- copper conductors (1)
- cortical electrical stimulation (1)
- cortical stimulation (1)
- deep brain stimulation (1)
- distributed-feedback (1)
- electrical drive (1)
- electrocorticogram (1)
- electrode impedance (1)
- electromobility (1)
- electroplating (1)
- foot pressure sensors (1)
- human gait (1)
- in vivo two-photon laser-scanning microscopy (1)
- including semiconductors (1)
- k-Means-Algorithmus (1)
- laser materials processing (1)
- lasers (1)
- liquid crystal polymer electrodes (1)
- material extrusion (1)
- movement disorders (1)
- neuron-glia interaction (1)
- organic materials (1)
- output impedance (1)
- platinum (1)
- pose estimation (1)
- pulsed current (1)
- reaction time measurement (1)
- recurrent neural networks (1)
- risk of falls (1)
- semiconductor lasers (1)
- sensitivity analysis (1)
- spectral estimation (1)
- spectroscopy (1)
- stereoscopic cameras (1)
- stimulator characterization (1)
- stimulator model (1)
- stl (1)
- terahertz (1)
- transmission phase (1)
- tremor (1)
- twisted-pair (1)
- ultrafast processes in condensed matter (1)
- ultrasound (1)
- visible lasers (1)
- volume holographic gratings (1)
- wear-level monitoring (1)
- wearable motion sensors (1)
Institut
- FB Technik (14) (entfernen)
Deep brain stimulation (DBS) is an established therapy for movement disorders such as in Parkinson's disease (PD) and essential tremor (ET). Adjusting the stimulation parameters, however, is a labour-intensive process and often requires several patient visits. Physicians prefer objective tools to improve (or maintain) the performance in DBS. Wearable motion sensors (WMS) are able to detect some manifestations of pathological signs, such as tremor in PD. However, the interpretation of sensor data is often highly technical and methods to visualise tremor data of patients undergoing DBS in a clinical setting are lacking. This work aims to visualise the dynamics of tremor responses to DBS parameter changes with WMS while patients performing clinical hand movements. To this end, we attended DBS programming sessions of two patients with the aim to visualise certain aspects of the clinical examination. PD tremor and ET were effectively quantified by acceleration amplitude and frequency. Tremor dynamics were analysed and visualised based on setpoints, movement transitions and stability aspects. These methods have not yet been employed and examples demonstrate how tremor dynamics can be visualised with simple analysis techniques. We therefore provide a base for future research work on visualisation tools in order to assist clinicians who frequently encounter patients for DBS therapy. This could lead to benefits in terms of enhanced evaluation of treatment efficacy in the future.
Abstract: This paper is about detecting the difference between fully-random and semi-random shuffleing data sets, with the use of unsupervised learning algorithms. Because of the limits of the k-means algorithm alone, a recurrent autoencoder is used for feature extraction to improve the results of k-means. In the next step the autoencoder alone is used for clustering.
Introduction: In the last years, machine learning has been used more and more in different areas and it is also appropriate for for pattern recognition in data. Random data is characterized through the missing of defined patterns. Permutations without repetitions have the highest amount of entropy for a sequence of its length, which is similar to random data according to Andrei Kolmogorov, who states that random data have the highest amount of information and can’t be compressed. Therefore, this paper analyses the difference between random permutations and good shuffled permutations, which have some remaining patterns left. This is done via a recurrent autoencoder.
Decoding the cellular network interaction of neurons and glial cells are important in the development of new therapies for diseases of the central nervous system (CNS). Electrophysiological in vivo studies in mice will help to understand the highly complex network. In this paper, the optimization of epidural liquid crystal polymer (LCP) electrodes for different platinum electroplating parameters are presented and compared. Constant current and pulsed current electroplating varied in strength and duration was used to decrease the electrode impedance and to increase the charge storage capacity (CSCc). In best cases, both methods generated similar results with an impedance reduction of about 99%. However, electroplating with pulsed currents was less parameter-dependent than the electroplating with constant current. The use of ultrasound was essential to generate platinum coatings without plating defects. Electrode model parameters extracted from the electrode impedance reflected the increase in surface porosity due to the electroplating processes.
Gait analysis is a systematic study of human movement. Combining wearable foot pressure sensors and machine learning (ML) solutions for a high-fidelity body pose tracking from RGB video frames could reveal more insights into gait abnormalities. However, accurate detection of heel strike (HS) and toe-off (TO) events is crucial to compute interpretable gait parameters. In this work, we present an experimental platform to study the timing of gait events using a new wearable foot pressure sensor (ActiSense System, IEE S.A., Luxembourg), and Google’s open-source ML solution MediaPipe Pose. For this purpose, two StereoPi systems were built to capture stereoscopic videos and images in real time. MediaPipe Pose was applied to the synchronized StereoPi cameras, and two algorithms (ALs) were developed to detect HS and TO events for gait and analysis. Preliminary results from a healthy subject walking on a treadmill show a mean relative deviation across all time spans of less than 4% for the ActiSense device and less than 16% for AL2 (33% for AL1) employing MediaPipe Pose on StereoPi videos. Finally, this work offers a platform for the development of sensor- and video-based ALs to automatically identify the timing of gait events in healthy individuals and those with gait disorders.
Dielectric properties of unidirectional and biaxial flax/epoxy composites at frequencies up to 1 GHz
(2023)
The relative permittivity of flax/epoxy composites in unidirectional and biaxial orientations was mapped in the frequency range of 1 kHz to 200 kHz, and for the first time in the range of 1 MHz to 1 GHz. In addition, permittivity was investigated for the first time in the temperature range between − 20 °C and 50 °C. These composites, produced using the vacuum infusion process, are increasingly used for sustainable and lightweight structural components in the automotive industry. The relative permittivity was determined using a self-developed plate capacitor with an LCR bridge and an impedance analyzer. An examination of the microstructure of the flax/epoxy composites shows that the fibers are disordered in the composite, resulting in local variations in fiber volume fraction. Furthermore, it was shown that the matrix also infiltrates into the fiber itself, resulting in an increase of the matrix fraction. It was found that unidirectional fabrics had a higher relative permittivity than biaxial fabrics, due to a higher fiber volume fraction and lower proportion of epoxy. The results suggest that it is the fiber volume fraction, rather than the manufacturing process and fiber orientation, that primarily determines the relative permittivity. It was also found that the permittivity continues to decrease below room temperature and thus behaves in a manner typical of the material in this temperature range as well.
Geometrieerzeugung von Evolventenzahntrieben: Profilverschobene schrägverzahnte Stirnzahnräder
(2022)
In dieser Arbeit wird die Zahnradgeometrie von Stirnrädern berechnet und formatiert, um sie in ein CAD-Programm zu übertragen. Dabei werden die Konturen der Evolvente und der Trochoide nach den gleichen Regel wie bei der Herstellung durch Wälzfräsen erzeugt. Der Anwender hat die Möglichkeit die Haupteigenschaften wie Modul, Zahnkopfspiel und Eckenverrundung einzugeben. Zusätzlich können auch schrägverzahnte, profilverschobene Stirnräder mit Hochverzahnung und Kopfkürzung erzeugt werden.
Per Datenausgabe werden die Koordinaten gespeichert und durch ein Makro in das CAD-Programm übertragen. Aus den beiden Konturzügen wird der 3D-Körper durch Austragen entlang der Helix erzeugt.
Zur Weiterverarbeitung wird die Zahnradgeometrie nach manueller Tesselierung in ein universales Dateiformat exportiert.
Electric drive systems are increasingly used in automobiles. However, the combination of comfort, dynamics and safety requirements places high demands on the torque accuracy. The complex interplay of battery, inverter and electrical machine causes a lot of system uncertainties based on parameter fluctuations and measurement errors that influence the system performance. In this paper these influences on the closed loop torque control are analyzed and quantified using a variance based sensitivity analysis. The method enables to connect the variance of the torque accuracy with the parameter uncertainties causing this variance. Moreover, it quantifies the influences of the parameters independent of the complexity of the analyzed system. In addition, two methods to ensure convergence of the estimated variance based sensitivity measures are proposed. The results of the analysis are presented for 19 static working points of an battery electric drive system.
Electrical stimulation is used for example to treat neuronal disorders and depression with deep brain stimulation or transcranial electrical stimulation. Depending on the application, different electrodes are used and thus different electrical characteristics exist, which have to be handled by the stimulator. Without a measuring device the user would have to rely on the stimulator being able to deliver the needed stimulation signal. Therefore, the objective of this paper is to present a method to increase the level of confidence with characterization and modelling of the electrical behavior by using the example of one channel of our stimulation device for experimental use. In several simulation studies with an electrode model with values in a typical range for cortical applications the influence of the load onto the stimulator and the possibility to pre-estimate measuring signals in complex networks are shown.
Organic semiconductor distributed feedback laser fabricated by direct laser interference ablation
(2007)
We use a pulsed, frequency tripled picosecond Nd:YAG laser for holographic ablation to pattern a surface relief grating into an organic semiconductor guest-host system. The resulting second order distributed feedback lasers exhibit laser action with laser thresholds being comparable to those obtained with resonators structured by standard lithographic techniques. The details of the interference ablation of tris-(8-hydroxyquinoline) aluminum (Alq(3)) doped with the laser dye 4- dicyanomethylene-2-methyl-6-(p-dimethylaminostyryl)-4H-pyran (DCM) are presented and discussed. Lasing action is demonstrated at a wavelength of 646.6 nm, exploiting second order Bragg reflection in a relief grating with a period of 399 nm.
For the assessment of human reaction time, a test environment was developed. This system consists of an embedded device with organic light-emitting diode (OLED) displays with push buttons for the combined presentation of visual stimulation and registration of the haptic human reaction. The test leader can define the test sequence with the aid of a graphical user interface (GUI) on a personal computer (PC). The validation of the system was proved by measuring the latency times of the whole system, which are conditioned by the specific hard- and software constellation. Through the investigation of the display’s light radiation by a photodiode and the recorded current consumption, latency times and their variance were specified. In the fastest mode the system can reach an error limit of 60 μs.