Refine
Year of publication
Document Type
- Conference Proceeding (50)
- Master's Thesis (34)
- Report (17)
- Article (9)
- Bachelor Thesis (3)
- Doctoral Thesis (3)
- Other Publications (3)
- Working Paper (2)
Language
- English (63)
- German (56)
- Multiple languages (2)
Keywords
- .NET Remoting (1)
- 2 D environment Laser data (1)
- AAL (2)
- ADO.NET (1)
- ASP.NET (1)
- Accelerometers (1)
- Active Server Pages (1)
- ActiveX Data Objects (ADO) (1)
- Activity monitoring (1)
- Agenten-Plattform (1)
- Akquisition <Vertrieb> (1)
- Ambient assisted living (1)
- Analog-Digital-Umsetzer (1)
- Analog-to-digital-Converter ; Spice Simulation ; Analog integrated circuit design ; (1)
- Annotation (1)
- Anwendung (1)
- Apnoe (1)
- Arbeitsablauf (1)
- Arbeitsplatzcomputer (1)
- Archivierung (1)
- Artefaktkorrektur (1)
- Assisted living (1)
- Atmung (2)
- Atmungssignal (1)
- Audi (1)
- Auftragsabwicklung (1)
- Automatisches Eintakten (1)
- Automotive (1)
- Autonomous Mobile Indoor Robot (1)
- BCG (2)
- BW (1)
- Balanced Scorecard (1)
- Ballistocardiography (1)
- Ballistokardiographie (1)
- Benutzerinteraktion (1)
- Benutzeroberfläche (1)
- Betriebssystem (1)
- Bewegung (1)
- Bewegungssignal (1)
- Bio-vital data (1)
- Biomedical Signal Capturing (1)
- Biomedical signals (1)
- Biosignal analysis (1)
- Biosignal processing (1)
- Biovital signal (2)
- Blockchain (1)
- Bootloader (1)
- Breathing (1)
- Breathing rate (1)
- C sharp (1)
- C++ (1)
- CL <C++> (1)
- CRM (1)
- CSTA (1)
- Canny Edge Detector (1)
- Canny-Kantendetektor (1)
- Checkstyle (1)
- Client Management System ; Haaland Internet Productions ; Client Relationship Management ; workflow (1)
- Codierung (1)
- Common Criteria (1)
- Computer Telephony Integration (1)
- Computersimulation (1)
- Controlling (1)
- Convolution (1)
- Convolutional neural network (1)
- Correlation (1)
- Cross Site Scripting (1)
- DTD (1)
- Data fusion (1)
- Datenbankmodellierung (1)
- Datenstruktur (1)
- Datentypeditor (1)
- Deep Convolutional Neural Network (1)
- Deep learning (2)
- Detektiv Langohr (1)
- Dijkstra Algorithm (1)
- Dijkstra Algorithmus (1)
- Distributed ledger (1)
- Dokumentenerstellung (1)
- Dokumententyp (1)
- Dokumentvorlage (1)
- Driving (1)
- Driving safety (1)
- Driving stress (1)
- Drowsiness (1)
- E-Health (1)
- ECG (5)
- EEG (1)
- EJB (1)
- EKG (1)
- ELF (1)
- EMG (1)
- Echtzeitsystem (1)
- Eindringerkennung (1)
- Einkommensteuer (1)
- Electrocardiography (2)
- Electromyography (1)
- Entwurfsmuster (1)
- Erkennung (1)
- FACS (1)
- FSR sensor (1)
- Facial Action Coding System (1)
- Facility-Management (1)
- Fehlersuche (1)
- Feldbus (1)
- Filter (1)
- Force resistor sensor (1)
- Formel (1)
- Framework (1)
- Framework <Informatik> (2)
- Freistellungssemesterbericht (17)
- GDPR (1)
- GUI (1)
- Geschäftsprozessmodellierung (1)
- Gesetz <Physik> (1)
- Graphische Benutzeroberfläche (1)
- Grundschule (1)
- HTML (1)
- Handy (1)
- Harris Corner Detector (1)
- Harris-Eckendetektor (1)
- Health information exchange (1)
- Heart rate (5)
- Heart rate variability (1)
- Helpdesk-System (1)
- Herzfrequenz (2)
- I3M (1)
- Illuminance (1)
- Impedance measurement (1)
- Implementierung (1)
- Information Security Management (1)
- Installation (1)
- Interfaceeditor (1)
- Internet of Things (1)
- Interpretability (1)
- Intranet (1)
- IoT (1)
- J2EE (1)
- JDBC (1)
- JTAPI (1)
- Java (2)
- Java 2 Enterprise Edition (2)
- Java <Programmiersprache> (2)
- Java Beans (1)
- Java Naming and Directory Interface (1)
- Java Server Pages (1)
- Joi (1)
- Karosseriebau (1)
- Khepera (1)
- Komponente (1)
- Konfigurationsmanagement (1)
- Konfigurationsverwaltung (1)
- Kontaktloses Hardware-System (1)
- Kraftfahrzeugbau (1)
- Kundenmanagement (1)
- Künstliche Intelligenz (1)
- LDAP (1)
- LVP (1)
- Laser-Sensor (1)
- Laserimpuls (1)
- Lasermesstechnik (1)
- Layout (1)
- Lehrveranstaltungsplan (1)
- Lernprogramm (1)
- Link Handler (1)
- Logimatik TM/3 (1)
- Logopädie (1)
- Lohn (1)
- Lohnsteuer (1)
- Lohnsteuerabzug (1)
- Low-pass filters (1)
- Lösung (1)
- MIDP (1)
- Machine learning (2)
- Marktanalyse (1)
- Maschinelles Lernen (1)
- Medical systems (1)
- Mess- und Steuerungssystem ; DDNA (1)
- Mimik (1)
- Mobile-Agenten (1)
- Mobilfunk (1)
- Mobilfunkprotokoll (1)
- Model View Controller (1)
- Monitoring (1)
- Monitoring <Informatik> (1)
- Movement detection (3)
- Multinomial logistic regression (2)
- Mund-Kiefer-Gesichtsbereich (1)
- MySQL 4.0 (1)
- Müdigkeitserkennung (1)
- Namenskonvention (1)
- Navigation (1)
- Navigieren (1)
- Nebenstellenanlage (1)
- Neuronal Netze (1)
- Neuronales Netz (1)
- Nokia (1)
- Non-invasive (1)
- Non-invasive sleep study (2)
- Nortel Meridian (1)
- OLAP (1)
- OSE (1)
- Oberflächeninspektion von Pressteilen (1)
- Oberflächenprüfung (1)
- Objektorientierung (1)
- OnTechnology ; CCM ; OnCommand ; Deployment Werkzeuge ; unattended Setup (1)
- Organisationsform (1)
- Outlook (1)
- PHP (1)
- PPG (1)
- PSG (1)
- PSQI (1)
- Pattern recognition (1)
- Pflichtenheft (1)
- Photoplethysmography (1)
- Physical activity (1)
- Physiognomik (1)
- Point Operations (1)
- Portal (1)
- Portal-Komponenenten (1)
- Posture tracking (1)
- PowerPC (1)
- Pressure sensor (1)
- Pressure sensors (2)
- Privacy by Design (1)
- Probabilistic modeling (1)
- Probability of Exploitation (1)
- Produktion (1)
- Produkttest (1)
- Programmierstil (1)
- Programmierumgebung (1)
- Prozesskette (1)
- Prozessleitsystem (1)
- Prozessmanagement (1)
- Prozessmodell (1)
- Punktoperationen (1)
- Qt (1)
- Qualitätsmanagement (1)
- Qualitätssicherung (1)
- Qualitätssicherung im Automobilbau (1)
- Quellenabzug (1)
- Quellenprinzip (1)
- RMI (1)
- Releasemanagement (1)
- Remediation Strategies (1)
- Remote Access (1)
- Requirements Engineering (1)
- Residual Neural Network (1)
- Respiration Rate (1)
- Respiration rate (1)
- Respiratory sounds (1)
- Roboter (2)
- SAP AG (1)
- SAP Enterprise Portal (1)
- SAP LE-TRA (1)
- SAP R/3 (1)
- SAP Vertriebs-Manager-Portal (1)
- SAX <Programmierumgebung> (1)
- SOAP <Protokoll> (1)
- SPICE <Programm> (1)
- SQL (1)
- SQL Injection (1)
- SVG (1)
- Sales Performance Analyse (1)
- Schlaf (1)
- Schlafanalyse (4)
- Schlafphasen (1)
- Schlafphasenerkennung (1)
- Schlafstadien (1)
- Schlafstudie (1)
- Schriftzeichenerkennung (1)
- Schweizerische Versicherungs-Gesellschaft (1)
- Scoring Systems (1)
- SeMoA (1)
- Security by Design (1)
- Seitenformatierung (1)
- Seitenlayout (1)
- Selbstorganisierende Karte (1)
- Sensor Bed (1)
- Sensor grid (1)
- Sensors (1)
- Sicherheit (1)
- Signal acquisition (1)
- Signal processing (3)
- Skin (1)
- Sleep (2)
- Sleep Stages (1)
- Sleep apnea (1)
- Sleep apnoea (1)
- Sleep efficiency (1)
- Sleep latency (1)
- Sleep medicine (3)
- Sleep phase (1)
- Sleep positions (2)
- Sleep quality (3)
- Sleep stage classification (1)
- Sleep stages (2)
- Sleep study (11)
- Sleep tracking (1)
- Sleep/Wake states (1)
- Smart Home (1)
- Smart bed (1)
- Smart cushion (1)
- Smart home (1)
- Smart-care (1)
- Softwareentwicklung (2)
- Softwareentwicklung / Projekt (1)
- Softwarekomponenten (1)
- Softwareproduktionsumgebung (1)
- Sprachstörung (1)
- Static Code Analysis (1)
- Statistics (1)
- Stethoscope (1)
- Steuerung (1)
- Stress (3)
- Stress detection (2)
- Stress measurement (1)
- Struts (1)
- Swing (1)
- System design (1)
- TSAPI (1)
- TSN (1)
- Tauchen (1)
- Tauchphysik (1)
- Telemedicine (2)
- Test (1)
- Test Suite (1)
- Transistortechnologie (1)
- Transportproblem (1)
- Transportsteuerung (1)
- Treiber <Programm> (1)
- Un-certainty (1)
- Unterstützungssystem <Informatik> (1)
- Update (1)
- Verbindungsoptimierung (1)
- Vergleich (1)
- Versionsverwaltung (1)
- Verteiltes System (1)
- Visual C++ (1)
- VisualBASIC für Applikationen (1)
- Vulnerability Prioritization (1)
- WML (1)
- WSDL (1)
- Wearable (1)
- Web Services (3)
- WebObjects 5 (1)
- Webanwendung (1)
- Winterthur (1)
- Wissensmanagement (1)
- World wide web (1)
- XML (6)
- XML-Anwendungsdeskriptor (1)
- XPath (1)
- XSL (1)
- XSL-FO (2)
- XSLT (2)
- Zeichenerkennung (1)
- Zeitreihenklassifikation (1)
- Zürcher Kantonalbank (1)
- chat system (1)
- distance measurement (1)
- dual-ported RAM (1)
- facial expression recognition ; action unit recognition (1)
- integrierte Java Laufzeitumgebung (1)
- istant messaging system (1)
- low-level feature extraction (1)
- mySAP Enterprise Portal (1)
- pFlow (1)
- support vector machines (1)
Institute
- Fakultät Informatik (121) (remove)
Background:
One of the most promising health care development areas is introducing telemedicine services and creating solutions based on blockchain technology. The study of systems combining both these domains indicates the ongoing expansion of digital technologies in this market segment.
Objective:
This paper aims to review the feasibility of blockchain technology for telemedicine.
Methods:
The authors identified relevant studies via systematic searches of databases including PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar. The suitability of each for inclusion in this review was assessed independently. Owing to the lack of publications, available blockchain-based tokens were discovered via conventional web search engines (Google, Yahoo, and Yandex).
Results:
Of the 40 discovered projects, only 18 met the selection criteria. The 5 most prevalent features of the available solutions (N=18) were medical data access (14/18, 78%), medical service processing (14/18, 78%), diagnostic support (10/18, 56%), payment transactions (10/18, 56%), and fundraising for telemedical instrument development (5/18, 28%).
Conclusions:
These different features (eg, medical data access, medical service processing, epidemiology reporting, diagnostic support, and treatment support) allow us to discuss the possibilities for integration of blockchain technology into telemedicine and health care on different levels. In this area, a wide range of tasks can be identified that could be accomplished based on digital technologies using blockchains.
Preliminary results of homomorphic deconvolution application to surface EMG signals during walking
(2021)
Homomorphic deconvolution is applied to sEMG signals recorded during walking. Gastrocnemius lateralis and tibialis anterior signals were acquired according to SENIAM recommendation. MUAP parameters like amplitude and scale were estimated, whilst the MUAP shape parameter was fixed. This features a useful time-frequency representation of sEMG signal. Estimation of scale MUAP parameter was verified extracting the mean frequency of filtered EMG signal, extracted from the scale parameter estimated with two different MUAP shape values.
Normal breathing during sleep is essential for people’s health and well-being. Therefore, it is crucial to diagnose apnoea events at an early stage and apply appropriate therapy. Detection of sleep apnoea is a central goal of the system design described in this article. To develop a correctly functioning system, it is first necessary to define the requirements outlined in this manuscript clearly. Furthermore, the selection of appropriate technology for the measurement of respiration is of great importance. Therefore, after performing initial literature research, we have analysed in detail three different methods and made a selection of a proper one according to determined requirements. After considering all the advantages and disadvantages of the three approaches, we decided to use the impedance measurement-based one. As a next step, an initial conceptual design of the algorithm for detecting apnoea events was created. As a result, we developed an activity diagram on which the main system components and data flows are visually represented.
Respiratory diseases are leading causes of death and disability in the world. The recent COVID-19 pandemic is also affecting the respiratory system. Detecting and diagnosing respiratory diseases requires both medical professionals and the clinical environment. Most of the techniques used up to date were also invasive or expensive.
Some research groups are developing hardware devices and techniques to make possible a non-invasive or even remote respiratory sound acquisition. These sounds are then processed and analysed for clinical, scientific, or educational purposes.
We present the literature review of non-invasive sound acquisition devices and techniques.
The results are about a huge number of digital tools, like microphones, wearables, or Internet of Thing devices, that can be used in this scope.
Some interesting applications have been found. Some devices make easier the sound acquisition in a clinic environment, but others make possible daily monitoring outside that ambient. We aim to use some of these devices and include the non-invasive recorded respiratory sounds in a Digital Twin system for personalized health.
A residual neural network was adapted and applied to the Physionet/Computing data in Cardiology Challenge 2020 to detect 24 different classes of cardiac abnormalities from 12-lead. Additive Gaussian noise, signal shifting, and the classification of signal sections of different lengths were applied to prevent the network from overfitting and facilitating generalization. Due to the use of a global pooling layer after the feature extractor, the network is independent of the signal’s length. On the hidden test set of the challenge, the model achieved a validation score of 0.656 and a full test score of 0.27, placing us 15th out of 41 officially ranked teams (Team name: UC_Lab_Kn). These results show the potential of deep neural networks for ap- plication to raw data and a complex multi-class multi-label classification problem, even if the training data is from di- verse datasets and of differing lengths.
Ballistocardiography (BCG) can be used to monitor heart rate activity. Besides, the accelerometer should have high sensitivity and minimal internal noise; a low-cost approach was taken into consideration. Several measurements have been executed to determine the optimal positioning of a sensor under the mattress to obtain a signal strong enough for further analysis. A prototype for an unobtrusive accelerometer-based measurement system has been developed and tested in a conventional bed without any specific extras. The influence of the human sleep position for the output accelerometer data was tested. The obtained results indicate the potential to capture BCG signals using accelerometers. The measurement system can detect heart rate in an unobtrusive form in the home environment.
The main aim of presented in this manuscript research is to compare the results of objective and subjective measurement of sleep quality for older adults (65+) in the home environment. A total amount of 73 nights was evaluated in this study. Placing under the mattress device was used to obtain objective measurement data, and a common question on perceived sleep quality was asked to collect the subjective sleep quality level. The achieved results confirm the correlation between objective and subjective measurement of sleep quality with the average standard deviation equal to 2 of 10 possible quality points.
We compared vulnerable and fixed versions of the source code of 50 different PHP open source projects based on CVE reports for SQL injection vulnerabilities. We scanned the source code with commercial and open source tools for static code analysis. Our results show that five current state-of-the-art tools have issues correctly marking vulnerable and safe code. We identify 25 code patterns that are not detected as a vulnerability by at least one of the tools and 6 code patterns that are mistakenly reported as a vulnerability that cannot be confirmed by manual code inspection. Knowledge of the patterns could help vendors of static code analysis tools, and software developers could be instructed to avoid patterns that confuse automated tools.
We propose and apply a requirements engineering approach that focuses on security and privacy properties and takes into account various stakeholder interests. The proposed methodology facilitates the integration of security and privacy by design into the requirements engineering process. Thus, specific, detailed security and privacy requirements can be implemented from the very beginning of a software project. The method is applied to an exemplary application scenario in the logistics industry. The approach includes the application of threat and risk rating methodologies, a technique to derive technical requirements from legal texts, as well as a matching process to avoid duplication and accumulate all essential requirements.
We present source code patterns that are difficult for modern static code analysis tools. Our study comprises 50 different open source projects in both a vulnerable and a fixed version for XSS vulnerabilities reported with CVE IDs over a period of seven years. We used three commercial and two open source static code analysis tools. Based on the reported vulnerabilities we discovered code patterns that appear to be difficult to classify by static analysis. The results show that code analysis tools are helpful, but still have problems with specific source code patterns. These patterns should be a focus in training for developers.
The evaluation of the effectiveness of different machine learning algorithms on a publicly available database of signals derived from wearable devices is presented with the goal of optimizing human activity recognition and classification. Among the wide number of body signals we choose a couple of signals, namely photoplethysmographic (optically detected subcutaneous blood volume) and tri-axis acceleration signals that are easy to be simultaneously acquired using commercial widespread devices (e.g. smartwatches) as well as custom wearable wireless devices designed for sport, healthcare, or clinical purposes. To this end, two widely used algorithms (decision tree and k-nearest neighbor) were tested, and their performance were compared to two new recent algorithms (particle Bernstein and a Monte Carlo-based regression) both in terms of accuracy and processing time. A data preprocessing phase was also considered to improve the performance of the machine learning procedures, in order to reduce the problem size and a detailed analysis of the compression strategy and results is also presented.
Good sleep is crucial for a healthy life of every person. Unfortunately, its quality often decreases with aging. A common approach to measuring the sleep characteristics is based on interviews with the subjects or letting them fill in a daily questionnaire and afterward evaluating the obtained data. However, this method has time and personal costs for the interviewer and evaluator of responses. Therefore, it would be important to execute the collection and evaluation of sleep characteristics automatically. To do that, it is necessary to investigate the level of agreement between measurements performed in a traditional way using questionnaires and measurements obtained using electronic monitoring devices. The study presented in this manuscript performs this investigation, comparing such sleep characteristics as "time going to bed", "total time in bed", "total sleep time" and "sleep efficiency". A total number of 106 night records of elderly persons (aged 65+) were analyzed. The results achieved so far reveal the fact that the degree of agreement between the two measurement methods varies substantially for different characteristics, from 31 minutes of mean difference for "time going to bed" to 77 minutes for "total sleep time". For this reason, a direct exchange of objective and subjective measuring methods is currently not possible.
Polysomnography is a gold standard for a sleep study, and it provides very accurate results, but its cost (both personnel and material) are quite high. Therefore, the development of a low-cost system for overnight breathing and heartbeat monitoring, which provides more comfort while recording the data, is a well-motivated challenge. The system proposed in this manuscript is based on the usage of resistive pressure sensors installed under the mattress. These sensors can measure slight pressure changes provoked during breathing and heartbeat. The captured signal requires advanced processing, like applying filters and amplifiers before the analog signal is ready for the next step. Then, the output signal is digitalized and further processed by an algorithm that performs a custom filtering before it can recognize breathing and heart rate in real-time. The result can be directly visualized. Furthermore, a CSV file is created containing the raw data, timestamps, and unique IDs to facilitate further processing. The achieved results are promising, and the average deviation from a reference device is about 4bpm.
Cardiovascular diseases are directly or indirectly responsible for up to 38.5% of all deaths in Germany and thus represent the most frequent cause of death. At present, heart diseases are mainly discovered by chance during routine visits to the doctor or when acute symptoms occur. However, there is no practical method to proactively detect diseases or abnormalities of the heart in the daily environment and to take preventive measures for the person concerned. Long-term ECG devices, as currently used by physicians, are simply too expensive, impractical, and not widely available for everyday use. This work aims to develop an ECG device suitable for everyday use that can be worn directly on the body. For this purpose, an already existing hardware platform will be analyzed, and the corresponding potential for improvement will be identified. A precise picture of the existing data quality is obtained by metrological examination, and corresponding requirements are defined. Based on these identified optimization potentials, a new ECG device is developed. The revised ECG device is characterized by a high integration density and combines all components directly on one board except the battery and the ECG electrodes. The compact design allows the device to be attached directly to the chest. An integrated microcontroller allows digital signal processing without the need for an additional computer. Central features of the evaluation are a peak detection for detecting R-peaks and a calculation of the current heart rate based on the RR interval. To ensure the validity of the detected R-peaks, a model of the anatomical conditions is used. Thus, unrealistic RR-intervals can be excluded. The wireless interface allows continuous transmission of the calculated heart rate. Following the development of hardware and software, the results are verified, and appropriate conclusions about the data quality are drawn. As a result, a very compact and wearable ECG device with different wireless technologies, data storage, and evaluation of RR intervals was developed. Some tests yelled runtimes up to 24 hours with wireless Lan activated and streaming.
In previous studies, we used a method for detecting stress that was based exclusively on heart rate and ECG for differentiation between such situations as mental stress, physical activity, relaxation, and rest. As a response of the heart to these situations, we observed different behavior in the Root Mean Square of the Successive differences heartbeats (RMSSD). This study aims to analyze Virtual Reality via a virtual reality headset as an effective stressor for future works. The value of the Root Mean Square of the Successive Differences is an important marker for the parasympathetic effector on the heart and can provide information about stress. For these measurements, the RR interval was collected using a breast belt. In these studies, we can observe the Root Mean Square of the successive differences heartbeats. Additional sensors for the analysis were not used. We conducted experiments with ten subjects that had to drive a simulator for 25 minutes using monitors and 25 minutes using virtual reality headset. Before starting and after finishing each simulation, the subjects had to complete a survey in which they had to describe their mental state. The experiment results show that driving using virtual reality headset has some influence on the heart rate and RMSSD, but it does not significantly increase the stress of driving.
This work is a study about a comparison of survey tools and it should help developers in selecting a suited tool for application in an AAL environment. The first step was to identify the basic required functionality of the survey tools used for AAL technologies and to compare these tools by their functionality and assignments. The comparative study was derived from the data obtained, previous literature studies and further technical data. A list of requirements was stated and ordered in terms of relevance to the target application domain. With the help of an integrated assessment method, the calculation of a generalized estimate value was performed and the result is explained. Finally, the planned application of this tool in a running project is explained.
This paper presents the implementation of deep learning methods for sleep stage detection by using three signals that can be measured in a non-invasive way: heartbeat signal, respiratory signal, and movement signal. Since signals are measurements taken during the time, the problem is seen as time-series data classification. Deep learning methods are chosen to solve the problem are convolutional neural network and long-short term memory network. Input data is structured as a time-series sequence of mentioned signals that represent 30 seconds epoch, which is a standard interval for sleep analysis. The records used belong to the overall 23 subjects, which are divided into two subsets. Records from 18 subjects were used for training the data and from 5 subjects for testing the data. For detecting four sleep stages: REM (Rapid Eye Movement), Wake, Light sleep (Stage 1 and Stage 2), and Deep sleep (Stage 3 and Stage 4), the accuracy of the model is 55%, and F1 score is 44%. For five stages: REM, Stage 1, Stage 2, Deep sleep (Stage 3 and 4), and Wake, the model gives an accuracy of 40% and F1 score of 37%.