610 Medizin, Gesundheit
Refine
Document Type
- Journal article (82)
- Conference proceeding (81)
- Book chapter (8)
- Doctoral Thesis (2)
- Book (1)
- Patent / Standard / Guidelines (1)
- Report (1)
Is part of the Bibliography
- yes (176)
Institute
- Informatik (113)
- Life Sciences (47)
- Technik (8)
- ESB Business School (7)
Publisher
- Springer (39)
- Hochschule Reutlingen (17)
- Università Politecnica delle Marche (9)
- Elsevier (8)
- Deutsche Gesellschaft für Computer- und Roboterassistierte Chirurgie e.V. (7)
- MDPI (7)
- IEEE (6)
- IOP (6)
- SPIE (5)
- De Gruyter (4)
Background/Aim: The aim of this study was the conception, production, material analysis and cytocompatibility analysis of a new collagen foam for medical applications. Materials and Methods: After the innovative production of various collagen sponges from bovine sources, the foams were analyzed ex vivo in terms of their structure (including pore size) and in vitro in terms of cytocompatibility according to EN ISO 10993-5/-12. In vitro, the collagen foams were compared with the established soft and hard tissue materials cerabone and Jason membrane (both botiss biomaterials GmbH, Zossen, Germany). Results: Collagen foams with different compositions were successfully produced from bovine sources. Ex vivo, the foams showed a stable and long-lasting primary structure quality with a bubble area of 1,000 to 2,000 μm2. In vitro, all foams showed sufficient cytocompatibility. Conclusion: Collagen sponges represent a promising material for hard and soft tissue regeneration. Future studies could focus on integrating and investigating different additives in the foams.
Die Bereitstellung klinischer Informationen im Operationssaal ist ein wichtiger Aspekt zur Unterstützung des chirurgischen Teams. Die roboter-assistierte Ösophagusresektion ist ein besonders komplexer Eingriff, der Potenzial zur workflowbasierten Unterstützung bietet. Wir präsentieren erste Ergebnisse der Entwicklung eines Checklisten-Tools mit der zugrundeliegenden Modellierung des chirurgischen Workflows und Informationsbedarf der Chirurgen. Das Checklisten-Tool zeigt hierfür die durchzuführenden Schritte chronologisch an und stellt zusätzliche Informationen kontextadaptiert bereit. Eine automatische Dokumentation von Start- und Endzeiten einzelner OP-Phasen und Schritte soll zukünftige Prozessanalysen der Operation ermöglichen.
This paper presents a generic method to enhance performance and incorporate temporal information for cardiorespiratory-based sleep stage classification with a limited feature set and limited data. The classification algorithm relies on random forests and a feature set extracted from long-time home monitoring for sleep analysis. Employing temporal feature stacking, the system could be significantly improved in terms of Cohen’s κ and accuracy. The detection performance could be improved for three classes of sleep stages (Wake, REM, Non-REM sleep), four classes (Wake, Non-REM-Light sleep, Non-REM Deep sleep, REM sleep), and five classes (Wake, N1, N2, N3/4, REM sleep) from a κ of 0.44 to 0.58, 0.33 to 0.51, and 0.28 to 0.44 respectively by stacking features before and after the epoch to be classified. Further analysis was done for the optimal length and combination method for this stacking approach. Overall, three methods and a variable duration between 30 s and 30 min have been analyzed. Overnight recordings of 36 healthy subjects from the Interdisciplinary Center for Sleep Medicine at Charité-Universitätsmedizin Berlin and Leave-One-Out-Cross-Validation on a patient-level have been used to validate the method.
Programmable nano-bio interfaces driven by tuneable vertically configured nanostructures have recently emerged as a powerful tool for cellular manipulations and interrogations. Such interfaces have strong potential for ground-breaking advances, particularly in cellular nanobiotechnology and mechanobiology. However, the opaque nature of many nanostructured surfaces makes non-destructive, live-cell characterization of cellular behavior on vertically aligned nanostructures challenging to observe. Here, a new nanofabrication route is proposed that enables harvesting of vertically aligned silicon (Si) nanowires and their subsequent transfer onto an optically transparent substrate, with high efficiency and without artefacts. We demonstrate the potential of this route for efficient live-cell phase contrast imaging and subsequent characterization of cells growing on vertically aligned Si nanowires. This approach provides the first opportunity to understand dynamic cellular responses to a cell-nanowire interface, and thus has the potential to inform the design of future nanoscale cellular manipulation technologies.
Die digitale Transformation und gesellschaftliche Entwicklungen verändern die Arbeitswelt nicht erst seit der Corona-Pandemie. Kommunikation, Kreativität und agile Vorgehensweisen in der Arbeitsorganisation rücken in den Vordergrund und werden gerade in Krisenzeiten zu wichtigen Stärken von Unternehmen. Der Grad der Selbstorganisation von Teams steigt und erfordert mehr individuelle Selbstorganisation der Beschäftigten. Dies birgt neben vielen Chancen auch Gesundheitsrisiken.
Der Report beleuchtet die agile Organisation und weitere moderne Organisationsmodelle wie die Soziokratie, die Holokratie und die evolutionäre Organisation unter dem Gesundheitsaspekt. All diese Organisationsmodelle sind gekennzeichnet durch die Abflachung von Hierarchien, eine stärkere Sinnorientierung, mehr Flexibilität sowie die Integration von Leistungspotentialen der Beschäftigten. Die Gemeinsamkeiten, aber auch Unterschiede und Konfliktpotenziale werden ausführlich erklärt.
Mit diesem Hintergrundwissen können Beratende Gesundheitsthemen besser in Phasen gesundheitlicher Belastungen einbringen und richtig adressieren. Der iga.Report 44 gibt einen Überblick zum noch jungen Stand der Forschung und liefert zahlreiche Ansatzpunkte für die Präventionsarbeit und die Betriebliche Gesundheitsförderung in einer neuen Arbeitswelt.
Die Corona-Pandemie hat zu einer Einschränkung des Alltags der medizinischen Versorgung geführt. Das zeigt sich u.a. in zum Teil erheblichen Zugangsbeschränkungen zu Krankenhäusern und Praxen mit stark reduzierter Einbestellung von Patienten, der Einhaltung von gesteigerten Hygienemaßnahmen mit entsprechend längeren Wartezeiten, dem Zugangsverbot für Begleitpersonen und nicht zuletzt der Angst vieler Patienten vor einer Ansteckung bei einem Aufenthalt in medizinischen Bereichen. Folge dessen war und ist, dass ein deutlich wahrnehmbarer Rückgang der Patientenzahlen in den Krankenhausambulanzen und Praxen zu verzeichnen war. Davon war die Augenheilkunde als Fachdisziplin mit einem hohen Anteil an ambulanten und geplanten, chirurgischen Eingriffen in besonderem Maße betroffen.
Health monitoring in a home environment can have broader use since it may provide continuous control of health parameters with relatively minor intrusiveness into regular life. This work aims to verify if it is possible to replace the typical in some sleep medicine areas subjective questioning by an objective measurement using electronic devices. For this purpose, a study was conducted with ten subjects, in which objective and subjective measurement of relevant sleep parameters took place. The results of both measurement methods were evaluated and analyzed. The results showed that while for some measures, such as Total Time in Bed, there is a high agreement between objective and subjective measurements, for others, such as sleep quality, there are significant differences. For this reason, currently, a combination of both measurement methods may be beneficial and provide the most detailed results, while a partial replacement can already reduce the number of questions at the subjective measurement by measurement through electronic devices.
Purpose
Injury or inflammation of the middle ear often results in the persistent tympanic membrane (TM) perforations, leading to conductive hearing loss (HL). However, in some cases the magnitude of HL exceeds that attributable by the TM perforation alone. The aim of the study is to better understand the effects of location and size of TM perforations on the sound transmission properties of the middle ear.
Methods
The middle ear transfer functions (METF) of six human temporal bones (TB) were compared before and after perforating the TM at different locations (anterior or posterior lower quadrant) and to different degrees (1 mm, ¼ of the TM, ½ of the TM, and full ablation). The sound-induced velocity of the stapes footplate was measured using single-point laser-Doppler-vibrometry (LDV). The METF were correlated with a Finite Element (FE) model of the middle ear, in which similar alterations were simulated.
Results
The measured and calculated METF showed frequency and perforation size dependent losses at all perforation locations. Starting at low frequencies, the loss expanded to higher frequencies with increased perforation size. In direct comparison, posterior TM perforations affected the transmission properties to a larger degree than anterior perforations. The asymmetry of the TM causes the malleus-incus complex to rotate and results in larger deflections in the posterior TM quadrants than in the anterior TM quadrants. Simulations in the FE model with a sealed cavity show that small perforations lead to a decrease in TM rigidity and thus to an increase in oscillation amplitude of the TM mainly above 1 kHz.
Conclusion
Size and location of TM perforations have a characteristic influence on the METF. The correlation of the experimental LDV measurements with an FE model contributes to a better understanding of the pathologic mechanisms of middle-ear diseases. If small perforations with significant HL are observed in daily clinical practice, additional middle ear pathologies should be considered. Further investigations on the loss of TM pretension due to perforations may be informative.
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.
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.
The present work proposes the use of modern ICT technologies such as smartphones, NFCs, internet, and web technologies, to help patients in carrying out their therapies. The implemented system provides a calendar with a reminder of the assumptions, ensures the drug identification through NFC, allows remote assistance from healthcare staff and family members to check and manage the therapy in real-time. The system also provides centralized information on the patient's therapeutic situation, helpful in choosing new compatible therapies.
We investigated the state of artificial intelligence (AI) in pharmaceutical research and development (R&D) and outline here a risk and reward perspective regarding digital R&D. Given the novelty of the research area, a combined qualitative and quantitative research method was chosen, including the analysis of annual company reports, investor relations information, patent applications, and scientific publications of 21 pharmaceutical companies for the years 2014 to 2019. As a result, we can confirm that the industry is in an ‘early mature’ phase of using AI in R&D. Furthermore, we can demonstrate that, despite the efforts that need to be managed, recent developments in the industry indicate that it is worthwhile to invest to become a ‘digital pharma player’.
It has been widely shown that biomaterial surface topography can modulate host immune response, but a fundamental understanding of how different topographies contribute to pro-inflammatory or anti-inflammatory responses is still lacking. To investigate the impact of surface topography on immune response, we undertook a systematic approach by analyzing immune response to eight grades of medical grade polyurethane of increasing surface roughness in three in vitro models of the human immune system. Polyurethane specimens were produced with defined roughness values by injection molding according to the VDI 3400 industrial standard. Specimens ranged from 0.1 μm to 18 μm in average roughness (Ra), which was confirmed by confocal scanning microscopy. Immunological responses were assessed with THP-1-derived macrophages, human peripheral blood mononuclear cells (PBMCs), and whole blood following culture on polyurethane specimens. As shown by the release of pro-inflammatory and anti-inflammatory cytokines in all three models, a mild immune response to polyurethane was observed, however, this was not associated with the degree of surface roughness. Likewise, the cell morphology (cell spreading, circularity, and elongation) in THP-1-derived macrophages and the expression of CD molecules in the PBMC model on T cells (HLA-DR and CD16), NK cells (HLA-DR), and monocytes (HLA-DR, CD16, CD86, and CD163) showed no influence of surface roughness. In summary, this study shows that modifying surface roughness in the micrometer range on polyurethane has no impact on the pro-inflammatory immune response. Therefore, we propose that such modifications do not affect the immunocompatibility of polyurethane, thereby supporting the notion of polyurethane as a biocompatible material.
The recovery of our body and brain from fatigue directly depends on the quality of sleep, which can be determined from the results of a sleep study. The classification of sleep stages is the first step of this study and includes the measurement of vital data and their further processing. The non-invasive sleep analysis system is based on a hardware sensor network of 24 pressure sensors providing sleep phase detection. The pressure sensors are connected to an energy-efficient microcontroller via a system-wide bus. A significant difference between this system and other approaches is the innovative way in which the sensors are placed under the mattress. This feature facilitates the continuous use of the system without any noticeable influence on the sleeping person. The system was tested by conducting experiments that recorded the sleep of various healthy young people. Results indicate the potential to capture respiratory rate and body movement.
Methods based exclusively on heart rate hardly allow to differentiate between physical activity, stress, relaxation, and rest, that is why an additional sensor like activity/movement sensor added for detection and classification. The response of the heart to physical activity, stress, relaxation, and no activity can be very similar. In this study, we can observe the influence of induced stress and analyze which metrics could be considered for its detection. The changes in the Root Mean Square of the Successive Differences provide us with information about physiological changes. A set of measurements collecting the RR intervals was taken. The intervals are used as a parameter to distinguish four different stages. Parameters like skin conductivity or skin temperature were not used because the main aim is to maintain a minimum number of sensors and devices and thereby to increase the wearability in the future.
The ballistocardiography is a technique that measures the heart rate from the mechanical vibrations of the body due to the heart movement. In this work a novel noninvasive device placed under the mattress of a bed estimates the heart rate using the ballistocardiography. Different algorithms for heart rate estimation have been developed.
Artificial intelligence (AI) technologies, such as machine learning or deep learning, have been predicted to highly impact future organizations and radically change the way how projects are managed. The Project Management Institute (PMI), the network of around 1.1 million certified project managers, ranked AI as one of the top three disruptors of their profession. In an own study on the effect of AI, 37% of the project management processes can be executed by machine learning and other AI technologies. In addition, Gartner recently postulated that 80% of the work of today's project managers may be eliminated by AI in 2030.
This editorial aims to outline today's project and portfolio management in context of pharmaceutical research and development (R&D), followed by an AI-vision and a more tangible mission, and illustrate what the consequences of an AI-enabled project and portfolio management could be for pharmaceutical R&D.
Die rasante Entwicklung der Sensortechnik im Endverbraucherbereich lässt einen klinischen Nutzen der verfügbaren dezentral erhobenen Daten aus dem Patientenalltag zur Überwachung des individuellen Gesundheitszustands vermuten. Zur Überprüfung dieser Vermutung ist die Bereitstellung einer entsprechenden Plattform in den klinischen Alltag erforderlich. Hierzu wird die bwHealthApp entwickelt, mit der sowohl die aktuelle Bandbreite als auch die Evolution der Sensortechnik auf die klinische Anwendung abbildbar ist. Mit dem flexiblen Entwurf lässt sich der klinische Nutzen für die personalisierte Medizin evaluieren. Außerdem bietet die bwHealthApp einen an Machbarkeit orientierten Diskussionsbeitrag zu offenen rechtlichen, regulatorischen und ethischen Fragestellungen der Digitalisierung in der Medizin in Deutschland.
The aim of this work was to investigate the mean fill weight control of a continuous capsule-filling process, whether it is possible to derive controller settings from an appendant process model. To that end, a system composed out of fully automated capsule filler and an online gravimetric scale was used to control the filled weight. This setup allows to examine challenges associated with continuous manufacturing processes, such as variations in the amount of active pharmaceutical ingredient (API) in the mixture due to fluctuations of the feeders or due to altered excipient batch qualities. Two types of controllers were investigated: a feedback control and a combination of feedback and feedforward control. Although both of those are common in the industry, determining the optimal parameter settings remains an issue. In this study, we developed a method to derive the control parameters based on process models in order to obtain optimal control for each filled product. Determined via rapid automated process development (RAPD), this method is an effective and fast way of determining control parameters. The method allowed us to optimize the weight control for three pharmaceutical excipients. By conducting experiments, we verified the feasibility of the proposed method and studied the dynamics of the controlled system. Our work provides important basic data on how capsule filler can be implemented into continuous manufacturing systems.
In networked operating room environments, there is an emerging trend towards standardized non-proprietary communication protocols which allow to build new integration solutions and flexible human-machine interaction concepts. The most prominent endeavor is the IEEE 11073 SDC protocol. For some uses cases, it would be helpful if not just medical devices could be controlled based on SDC, but also building automation systems like light, shutters, air condition, etc. For those systems, the KNX protocol is widely used. We build an SDC-to-KNX gateway which allows to use the SDC protocol for sending commands to connected KNX devices. The first prototype system was successfully implemented at the demonstration operating room at Reutlingen University. This is a first step toward the integration of a broader variety of KNX devices.
Documentation of clinical processes, especially in the perioperative are, is a base requirement for quality of service. Nonetheless, the documentation is a burden for the medical staff since it distracts from the clinical core process. An intuitive and user-friendly documentation system could increase documentation quality and reduce documentation workload. The optimal system solution would know what happened and the person documenting the step would need a single “confirm” button. In many cases, such a linear flow of activities is given as long as only one profession (e.g. anaestesiology, scrub nurse) is considered, but even in such cases, there might be derivations from the linear process flow and further interaction is required.
Intraoperative brain deformation, so called brain shift, affects the applicability of preoperative magnetic resonance imaging (MRI) data to assist the procedures of intraoperative ultrasound (iUS) guidance during neurosurgery. This paper proposes a deep learning-based approach for fast and accurate deformable registration of preoperative MRI to iUS images to correct brain shift. Based on the architecture of 3D convolutional neural networks, the proposed deep MRI-iUS registration method has been successfully tested and evaluated on the retrospective evaluation of cerebral tumors (RESECT) dataset. This study showed that our proposed method outperforms other registration methods in previous studies with an average mean squared error (MSE) of 85. Moreover, this method can register three 3D MRI-US pair in less than a second, improving the expected outcomes of brain surgery.
Checklists are a valuable tool to ensure process quality and quality of care. To ensure proper integration in clinical processes, it would be desirable to generate checklists directly from formal process descriptions. Those checklists could also be used for user interaction in context-aware surgical assist systems. We built a tool to automatically convert Business Process Model and Notation (BPMN) process models to checklists displayed as HTML websites. Gateways representing decisions are mapped to checklist items that trigger dynamic content loading based on the placed checkmark. The usability of the resulting system was positively evaluated regarding comprehensibility and end-user friendliness.
Pharmaceutical companies are among the top investors into research and development (R&D) globally, as product innovation is still the main growth driver for the industry and because the related complexities necessitate enormous R&D investments. The market demand for new medicines to be more efficacious or to provide better safety than existing drugs and the regulatory need to prove superiority in clinical trials are reasons why drug R&D is increasingly expensive and pharmaceutical companies need to manage extraordinarily high costs per approved new compound.
Purpose: Gliomas are the most common and aggressive type of brain tumors due to their infiltrative nature and rapid progression. The process of distinguishing tumor boundaries from healthy cells is still a challenging task in the clinical routine. Fluid attenuated inversion recovery (FLAIR) MRI modality can provide the physician with information about tumor infiltration. Therefore, this paper proposes a new generic deep learning architecture, namely DeepSeg, for fully automated detection and segmentation of the brain lesion using FLAIR MRI data.
Methods: The developed DeepSeg is a modular decoupling framework. It consists of two connected core parts based on an encoding and decoding relationship. The encoder part is a convolutional neural network (CNN) responsible for spatial information extraction. The resulting semantic map is inserted into the decoder part to get the full-resolution probability map. Based on modified U-Net architecture, different CNN models such as residual neural network (ResNet), dense convolutional network (DenseNet), and NASNet have been utilized in this study.
Results: The proposed deep learning architectures have been successfully tested and evaluated on-line based on MRI datasets of brain tumor segmentation (BraTS 2019) challenge, including s336 cases as training data and 125 cases for validation data. The dice and Hausdorff distance scores of obtained segmentation results are about 0.81 to 0.84 and 9.8 to 19.7 correspondingly.
Conclusion: This study showed successful feasibility and comparative performance of applying different deep learning models in a new DeepSeg framework for automated brain tumor segmentation in FLAIR MR images. The proposed DeepSeg is open source and freely available at https://github.com/razeineldin/DeepSeg/.
In Zusammenarbeit mit dem Medizinproduktehersteller ulrich medical wird eine User Experience und Usability Studie an der Software der im Moment eingesetzten Kontrastmittelinjektoren durchgeführt. Das Unternehmen möchte eine neue Variante eines Kontrastmittelinjektors entwickeln, der als Basis eine verbesserte Version dieser Softwares enthält. Benutzerstudien können mit den unterschiedlichsten Methoden durchgeführt werden. Das geeignete Vorgehen muss definiert und die Testpersonen in Bezug zur eingesetzten Methode ermittelt werden. Bei Medizinprodukten muss zusätzlich auf strikte Auflagen in Normen und Gesetzen geachtet werden. Die Grundlage zur Methodenauswahl bildet eine Recherche zu Usability und User Experience Vorgaben für Medizinprodukte. Die Studie wird anhand quantitativer Daten eines Usability Tests im Labor, Fragebögen zur User Experience und qualitativen Post Test- Interviews evaluiert. In erster Linie dient diese Studie der Ermittlung von möglichen Verbesserungen, welche in der darauf folgenden Masterthesis vertieft und umgesetzt werden.
The field of breath analysis has developed to be of growing interest in medical diagnosis and patient monitoring. The main advantages are that it’s noninvasive, painless and repeatable in flexible cycles. Even though breath analysis is being researched for a couple of decades there are still many unanswered questions. Human breath contains volatile organic compounds which are emitted from inside the body. Some of these compounds can be assigned to specific sources, such as inflammation or cancer, but also to non health related origins. This paper gives an overview of breath analysis for the purpose of disease diagnosis and health monitoring. Therefore, literature regarding breath analysis in the medical field has been analyzed, from its early stages to the present. As a result, this paper gives an outline of the topic of breath analysis.
Haptisches Feedback ist nach zahlreichen Studien ein wichtiger Bestandteil in der medizinischen Robotik. Die meisten Systeme befinden sich jedoch noch im Forschungsstatus und verfolgen unterschiedliche Ansätze. In der Teleoperation wird mit sensorlosen und Sensor-Systemen geforscht. Sensoren bieten, im Gegensatz zu den Encodern in sensorlosen Systemen, genaue Messungen, sind allerdings teuer in der Anschaffung, schwer zu desinfizieren und müssen in OP-Besteck integriert werden. In Hands-On Systemen fühlt der Operateur im Gegensatz zu Teleoperationssystemen direkt die auftretenden Kräfte bei der Benutzung. Der Roboter bietet in diesen Systemen nur die benötigte Stabilität und Genauigkeit, gesteuert werden sie direkt durch den Menschen. Dagegen werden in Teleoperationssystemen gezielte Controller eingesetzt. Hier hat sich der für den OP entwickelte sigma.7 durchgesetzt. Gegenüber der für die Allgemeinheit entwickelten Konkurrenz bietet er haptisches Feedback in allen nötigen Freiheitsgraden und eine entsprechende Kraftrückkoppelung.
In der Kryochirurgie wird Kälte verwendet, um tumoröses Gewebe abzutöten. Dazu werden Kryosonden in den Tumor gestochen und stark abgekühlt. Hierbei gibt es verschiedene Herausforderungen, welchen computergestützt begegnet werden kann. Diese Arbeit gibt die Ergebnisse einer Literaturrecherche zu den Herausforderungen wieder. Die vorgestellten Arbeiten beschäftigten sich mit der Simulation des im Tumor entstehenden Eisballs, dem korrekten Positionieren der Kryosonden im Tumor, dem Überwachen des Eingriffs sowie dem Entwickeln von Simulationen für Trainingszwecke. Dabei zeigt sich, dass der Einsatz von computergestützten Lösungen die Kryochirurgie für Operateur und Patient verbessern kann.
This book contains the proceedings of the KES International conferences on Innovation in Medicine and Healthcare (KES-InMed-19) and Intelligent Interactive Multimedia Systems and Services (KES-IIMSS-19), held on 17–19 June 2019 and co-located in St. Julians, on the island of Malta, as part of the KES Smart Digital Futures 2019 multi theme conference.
The major areas covered by KES-InMed-19 include: Digital IT Architecture in Healthcare; Advanced ICT for Medical and Healthcare; Biomedical Engineering, Trends, Research and Technologies and Healthcare Support System. The major areas covered by KES-IIMSS-19 were: Interactive Technologies; Artificial Intelligence and Data Analytics; Intelligent Services and Architectures and Applications.
This book is of use to researchers in these vibrant areas, managers, industrialists and anyone wishing to gain an overview of the latest research in these fields.
Size and function of bioartificial tissue models are still limited due to the lack of blood vessels and dynamic perfusion for nutrient supply. In this study, we evaluated the use of cytocompatible methacryl-modified gelatin for the fabrication of a hydrogel-based tube by dip-coating and subsequent photo-initiated cross-linking. The wall thickness of the tubes and the diameter were tuned by the degree of gelatin methacryl-modification and the number of dipping cycles. The dipping temperature of the gelatin solution was adjusted to achieve low viscous fluids of approximately 0.1 Pa s and was different for gelatin derivatives with different modification degrees. A versatile perfusion bioreactor for the supply of surrounding tissue models was developed, which can be adaped to several geometries and sizes of blood-vessel mimicking tubes. The manufactured bendable gelatin tubes were permeable for water and dissolved substances, like Nile Blue and serum albumin. As a proof of concept, human fibroblasts in a three-dimensional collagen tissue model were sucessfully supplied with nutrients via the central gelatin tube under dynamic conditions for 2 days. Moreover, the tubes could be used as scaffolds to build-up a functional and viable endothelial layer. Hence, the presented tools can contribute to solving current challenges in tissue engineering.
In 2017, Philips' goal was to use innovation to improve the lives of three billion people a year by 2025. To achieve that, the company was shifting from selling medical products in a transactional manner to providing integrated healthcare solutions based on digital health technology. Based on our interviews with 23 executives at Philips, the case examines the two directions of the transformation required by this shift: externally, Philips worked on transforming how healthcare was conducted. Healthcare professionals would have to change the way they worked and reimbursement schemes needed to change to incentivize payers, providers, and patients in vastly different ways. Internally, Philips needed to redesign how its employees worked. The company componentized its business, introduced digital platforms, and co-created integrated solutions with the various stakeholders of the healthcare industry. In other words: Philips was transforming itself in order the reinvent healthcare in the digital age.
Autism spectrum disorders (ASD) affect a large number of children both in the Russian Federation and in Germany. Early diagnosis is key for these children, because the sooner parents notice such disorders in a child and the rehabilitation and treatment program starts, the higher the likelihood of his social adaptation. The difficulties in raising such a child lie in the complexity of his learning outside of children's groups and the complexity of his medical care. In this regard, the development of digital applications that facilitate medical care and education of such children at home is important and relevant. The purpose of the project is to improve the availability and quality of healthcare and social adaptation at home of children with ASD through the use of digital technologies.
Multi-dimensional patient data, such as time varying volume data, data of different imaging modalities, surface segmentations etc. are of growing importance in the clinical routine. For many use cases, it is of major importance to replicate a certain visualization of a data set created on one machine on a different computer using different software tools. Up until now, there exists no standardized methodology for this consistent presentation. We propose an extension of the Digital Imaging und Communications in Medicine (DICOM) called “Multi dimensional Presentation State” and outline scope and first results of the standardization process.
Workflow driven support systems in the peri-operative area have the potential to optimize clinical processes and to allow new situation-adaptive support systems. We started to develop a workflow management system supporting all involved actors in the operating theatre with the goal to synchronize the tasks of the different stakeholders by giving relevant information to the right team members. Using the OMG standards BPMN, CMMN and DMN gives us the opportunity to bring established methods from other industries into the medical field. The system shows each addressed actor their information in the right place at the right time to make sure every member can execute their task in time to ensure a smooth workflow. The system has the overall view of all tasks. Accordingly, a workflow management system including the Camunda BPM workflow engine to run the models, and a middleware to connect different systems to the workflow engine and some graphical user interfaces to show necessary information or to interact with the system are used. The complete pipeline is implemented with a RESTful web service. The system is designed to include different systems like hospital information system (HIS) via the RESTful web service very easily and without loss of data. The first prototype is implemented and will be expanded.
The goal of the presented project is to develop the concept of home e-health centers for barrier-free and cross-border telemedicine. AAL technologies are already present on the market but there is still a gap to close until they can be used for ordinary patient needs. The general idea needs to be accompanied by new services, which should be brought together in order to provide a full coverage of service for the users. Sleep and stress were chosen as predominant influence in the population. The executed scientific study of available home devices analyzing sleep has provided the necessary to select appropriate devices. The first choice for the project implementation is the device EMFIT QS+. This equipment provides a part of a complete system that a home telemedical hospital can provide at a level of precision and communication with internal and/or external health services.
The metric and qualitative analysis of models of the upper and lower dental arches is an important aspect of orthodontic treatment planning. Currently available eLearning systems for dental education only allow access to digital learning materials, and do not interactively support the learning progress. Moreover, to date no study compared the efficiency of learning methods based on physical or digital study models. For this pilot study, 18 dental students were separated into two groups to investigate whether the learning success in study model analysis with an interactive elearning system is higher based on digital models or on conventional plaster models. The results show that with the digital method less time is needed per model analysis. Moreover, the digital approach leads to higher total scores than that based on plaster models. We conclude that interactive eLearning using digital dental arch models is a promising tool for dental education.
OR-Pad - Entwicklung eines Prototyps zur sterilen Informationsanzeige am OP-Situs : meeting abstract
(2019)
Hintergrund: Oftmals werden Informationen aus der Krankenakte oder von Bildgebungsverfahren nur auf recht weit vom Operationsgebiet entfernten Monitoren, außerhalb der ergonomischen Sichtachse des Operateurs, dargestellt. Dies führt dazu, dass relevante Informationen übersehen werden oder ihr Informationspotenzial nicht ausgeschöpft werden kann. In Papierform mitgenommene Notizen befinden sich während der OP außerhalb des sterilen Bereichs und sind dadurch für den Operateur nicht ohne Weiteres zugänglich. Auch bei intraoperativen Einträgen für die OP Dokumentation ist der Operateur auf die Mithilfe der Assistenz angewiesen. Durch die zusätzlichen Kommunikationswege entstehen dabei ein personeller und zeitlicher Mehraufwand und das Fehlerpotenzial nimmt zu. Das anwendungsorientierte Forschungsprojekt OR-Pad - Nutzung von portablen Informationsanzeigen im Operationssaal - soll dem Operateur zu einem verbesserten Informationsfluss verhelfen. Die Idee entstand aus der klinischen Routine der Anatomie und Urologie des Universitätsklinikums Tübingen und wird nun durch Fördermittel vom Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg sowie vom Europäischen Fonds für regionale Entwicklung an der Hochschule Reutlingen zu einem High Fidelity-Prototypen weiterentwickelt.
Ziel: Ziel des OR-Pad Projekts ist es, während einer OP zum aktuellen Zeitpunkt klinisch relevante Informationen in unmittelbarer Nähe zum Operateur darzustellen. Mithilfe des Systems soll der Informationsfluss zwischen dem Eingriff sowie dessen Vor- und Nachbereitung optimiert werden. Der Operateur soll vorab relevante Informationen, wie aktuelle Röntgenbilder oder persönliche Notizen, zur intraoperativen Anzeige auswählen können, die dann am OP-Situs auf einer sterilen Informationsanzeige dargestellt werden. Durch die Positionierung soll eine ergonomische Sichtachse sowie die direkte Interaktion mit dem System ermöglicht werden. Kontextrelevante Informationen sollen basierend auf dem aktuellen OP-Verlauf durch die Entwicklung einer Situationserkennung automatisch bereitgestellt werden. Zur Optimierung des Informationsflusses gehört ebenfalls die Unterstützung der OP-Dokumentation. Für diese sollen während des Eingriffs manuell vom Operateur sowie automatisch vom System Einträge, wie Zeitpunkte oder intraoperative Aufnahmen, erstellt werden. Aus diesen soll nach dem Eingriff die OP-Dokumentation generiert und damit der Prozess qualitativer und zeiteffizienter gestaltet werden.
Methodik: Zur Erreichung des Ziels werden zunächst die klinischen Anforderungen spezifiziert und in ein Lastenheft überführt. Hierfür werden Interviews und Beobachtungen bei mehreren Interventionen durchgeführt. Nach dem User-Centered-Designprozess werden Personas und Nutzungsszenarien entworfen und mit klinischen Projektpartnern in mehreren Iterationen evaluiert. Es gilt eine Informationsarchitektur aufzubauen, die eine Einbettung klinischer Informationssysteme sowie Bild- und Gerätedaten aus dem OP-Netzwerk erlaubt. Eine Situationserkennung, basierend auf Prozessmodellen, soll zur Abschätzung des Operationsfortschritts entwickelt werden. Zur Befestigung der Informationsanzeige sollen geeignete Haltemechanismen eingesetzt werden. Das OR-Pad System soll laufend im Lehr- und Forschungs-OP der Hochschule Reutlingen getestet und im Sinne agiler Produktentwicklung mit den klinischen Projektpartnern abgestimmt werden. Der finale Funktionsprototyp soll abschließend in den Versuchs-OPs der Anatomie Tübingen getestet und evaluiert werden.
Ergebnisse: Über eine erste Datenerhebung mittels Contextual Inquiry konnten erste Anforderungen an das OR-Pad System erfasst werden, woraus ein Low-Fidelity-Prototyp resultierte. Die Evaluation über Experteninterviews führte in die zweite Iteration, in der das Konzept entsprechend der Ergebnisse angepasst wurde. Über Hospitationen am Uniklinikum Tübingen fand eine weitere Datenerhebung zur Erstellung von Szenarien für die intraoperativen Anwendungsfälle statt. Anhand der Anforderungen wurde ein Konzept für die Benutzerschnittstelle entworfen, die im weiteren Verlauf mit den klinischen Projektpartnern evaluiert wird.
Background/Aim: The aim of this study was the development of a new osteoconductivity index to determine the bone healing capacities of bone substitute materials (BSM) on the basis of 3D microcomputed tomographic (μ-CT) data. Materials and Methods: Sinus biopsies were used for the comparative analysis of the integration behavior of two xenogeneic BSM (cerabone® and Bio Oss®). 3D μ-CT and data sets from histomorphometrical measurements based on 2D histological slices were used to measure the bone-material-contact and the tissue distribution within the biopsies. The tissue reactions to both BSM were microscopically analyzed. Results: The 3D and 2D results of the osteoconductivity measurements showed comparable material-bone contacts for both BSM, but the 2D data were significantly lower. The same results were found when tissue distribution was measured in both groups. The histopathological analysis showed comparative tissue reactions in both BSM. Conclusion: Osteoconductivity index is a reliable measurement parameter for determining the healing capacities of BSM. The observed differences between both measurement methods could be assigned to the resolution capacity of μ-CT data that did not allow for a precise interface distinction between both BSM and bone tissue. Histomorphometrical data based on histological slides still allow for a more exact evaluation.
Artefaktkorrektur und verfeinerte Metriken für ein EEG-basiertes System zur Müdigkeitserkennung
(2019)
Fragestellung: Müdigkeit ist ein oft unterschätztes, aber dennoch großes Problem im Straßenverkehr. Von rund 2,5 Mio. Verkehrsunfällen 2015 in Deutschland, waren 2898 Unfälle, mit insgesamt 59 Toten (~1,7 % der Todesfälle), auf Übermüdung zurückzuführen. Schätzungen gehen von einer Dunkelziffer von bis zu 20 % aus. In einer ersten eigenen Studie wurde überprüft, ob ein mobiles EEG in einem Fahrsimulator Müdigkeitszustände zuverlässig erkennen kann. Die Erkennungsrate lag lediglich bei 61 %. Ziel dieser Arbeit ist, das verwendete Messsystem zu verbessern. Dazu wird die Genauigkeit durch eine Artefaktkorrektur und mit Hilfe von verfeinerten Qualitätsmetriken erhöht. Eine erkannte Übermüdung wird dem Fahrer dann in angemessener Weise angezeigt, so dass er entsprechend reagieren kann.
Patienten und Methoden: Die Independent Component Analysis (ICA) ist ein multivariates Verfahren, um mehrere Zufallsvariablen zu analysieren. Für die Entscheidung, ob ein Fahrer gerade müde oder wach ist, wird der erstellte Merkmalsvektor für jede Sequenz mit ICA klassifiziert. Dafür wird ein trainierter Machine-Learning-Algorithmus eingesetzt, der in der Lage ist, auch unbekannte Datensätze in Klassen einzuteilen. Um die benötigten Frequenzwerte zu erhalten, wurde für jeden EEG-Kanal eine Fourier Transformation durchgeführt. Der erstellte Merkmalsvektor wird im nächsten Schritt durch ein Künstliches Neuronales Netz klassifiziert. Für das Training werden vorab erstellte Merkmalsvektoren mit den Klassen „Wach“ und „Müde“ versehen. Diese Daten werden zufällig gemischt und im Verhältnis 2:1 in eine Trainings- und Testmenge geteilt. Das Experiment wurde mit acht Personen mit jeweils zweimal 45 min Testfahrt durchgeführt.
Ergebnisse: Der komplette Datensatz besteht aus 150.000 Signalwerten, welche zu ca. 7000 Sequenzen zusammengefasst werden. Durch die Anwendung der Qualitätsmetrik bleiben 4370 Sequenzen für das Training übrig. Bei invaliden Sequenzen aufgrund von EEG-Artefakten gibt es deutliche Unterschiede. Im „Wach“ Zustand werden dreimal so viele Sequenzen verworfen als im „Müde“ Zustand. Insgesamt werden bei wachen Probanden im Schnitt ca. 50 % der Sequenzen verworfen, bei Müden lediglich 25 %. Im Durchschnitt erreicht das System eine Erkennungsrate von 73 % für beide Zustände. Vergleicht man nun das Verhältnis von „Wach“ und „Müde“ und lässt „Leichte Müdigkeit“ außen vor, liegen die Ergebnisse bei über 90 %.
Schlussfolgerungen: Die Ergebnisse zeigen, dass die Aufmerksamkeit während des Experiments abnimmt bzw. die Müdigkeit zunimmt. Dies verdeutlichen zum einen subjektive und objektive Beobachtungen von Müdigkeitsanzeichen. Zum anderen lassen sich messbare und klassifizierbare Unterschiede im EEG Signal nachweisen. Die als Merkmale eingesetzten Theta-Wellen zeigten eine niedrigere Amplitude gegen Ende des Experiments. Die Erweiterung der binären Klassifizierung führt zu einer weiteren Stabilisierung der Ergebnisse. Artefaktkorrektur und Qualitätsmetriken steigern die Güte der Daten weiter. Die entwickelte Anwendung zur Müdigkeitserkennung ermittelt messbare Zeichen von Müdigkeit und kann eine gute Entscheidung über die Fahrtauglichkeit treffen.
Durch das stetige Wachstum an neuen Technologien und Möglichkeiten steht der Verschmelzung von Technologien mit dem Menschen kaum noch etwas im Wege. Die Untersuchung der Implantate und die damit verbundenen Risiken sind ein Teil dieser Arbeit. Von Bedeutung sind hier die Funktionsweise und die IT-Sicherheitsaspekte. Alle in dieser Arbeit dargestellten Implantate benötigen eine Kommunikation nach außen. Diese Kommunikationsmöglichkeit birgt Risiken, die nicht nur auf die Daten der Träger beschränkt sind, sondern auch gesundheitliche Risiken beinhalten.
Segmentierung von Polypen in Koloskopie-Bilddaten : eine Potentialanalyse von Deep-Learning-Methoden
(2018)
Kolorektale Karzinome haben eine hohe Sterblichkeitsrate, wenn sie spät entdeckt werden. Eine frühzeitige Entfernung von bösartigen Polypen im Magen-Darm-Trakt, die deren Vorstufen bilden, bietet jedoch hohe Überlebenschancen. Bei Darmspiegelungen werden gerade kleine Polypen aber recht häufig übersehen. Zuverlässige bildverarbeitende Systeme, die Polypen in einem Koloskopie-Frame nicht nur detektieren, sondern pixelgenau segmentieren, könnten Ärzten bei Darmkrebs-Screenings helfen. Diese Arbeit analysiert den aktuellen Stand der Segmentierung von Polypen im Gastrointestinaltrakt. Weiterführend wird untersucht, inwiefern die in letzter Zeit sehr erfolgreichen Methoden des Deep Learning hier Vorteile bieten.
Die Erholung unseres Körpers und Gehirns von Müdigkeit ist direkt abhängig von der Qualität des Schlafes, die aus den Ergebnissen einer Schlafstudie ermittelt werden kann. Die Klassifizierung der Schlafstadien ist der erste Schritt dieser Studie und beinhaltet die Messung von Biovitaldaten und deren weitere Verarbeitung. Das non-invasive Schlafanalyse-System basiert auf einem Hardware-Sensornetz aus 24 Drucksensoren, das die Schlafphasenerkennung ermöglicht. Die Drucksensoren sind mit einem energieeffizienten Mikrocontroller über einen systemweiten Bus mit Adressarbitrierung verbunden. Ein wesentlicher Unterschied dieses Systems im Vergleich zu anderen Ansätzen ist die innovative Art, die Sensoren unter der Matratze zu platzieren. Diese Eigenschaft erleichtert die kontinuierliche Nutzung des Systems ohne fühlbaren Einfluss auf das gewohnte Bett. Das System wurde getestet, indem Experimente durchgeführt wurden, die den Schlaf verschiedener gesunder junger Personen aufzeichneten. Die ersten Ergebnisse weisen auf das Potenzial hin, nicht nur Atemfrequenz und Körperbewegung, sondern auch Herzfrequenz zu erfassen.
Mammographie-Geräte werden in der Diagnostik von Mammakarzinomen eingesetzt. Die ursprüngliche Technik wurde in den letzten Jahren von analogen Röntgenfilmen zu digital integrierten Systemen weiterentwickelt. Durch die Tomosynthese, bei der in einem Schnittbildverfahren mehrere Schichten des Organismus untersucht werden können, können auch überlagerte Strukturen sichtbar gemacht werden. Um als adäquate Grundlage zur Diagnostik von malignen Tumoren dienen zu können, müssen einige qualitative Anforderungen erfüllt werden. Bisher gibt es wenig Literatur, die Anforderungen und den Aufbau solcher Geräte systematisch beschreiben. Im Rahmen dieser Arbeit werden auf Basis der Literatur und bestehender Systeme die qualitativen Anforderungen identifiziert. Der prinzipielle Aufbau solcher Systeme wird anhand der einzelnen Systembausteine in der semiformalen Notationssprache SysML gezeigt. Die grundlegende Funktionsweise eines tomosynthesefähigen Mammographie Gerätes wird in dieser Arbeit zusammenfassend und anhand der einzelnen Systembausteine beschrieben. Diese Arbeit dient der Vermittlung eines umfassenden Verständnisses für die digitale Mammographie, um als Grundlage für die Dokumentation von qualitativen Anforderungen dienen zu können.
This study describes a non-contact measuring and parameter identification procedure designed to evaluate inhomogeneous stiffness and damping characteristics of the annular ligament in the physiological amplitude and frequency range without the application of large static external forces that can cause unnatural displacements of the stapes. To verify the procedure, measurements were first conducted on a steel beam. Then, measurements on an individual human cadaveric temporal bone sample were performed. The estimated results support the inhomogeneous stiffness and damping distribution of the annular ligament and are in a good agreement with the multiphoton microscopy results which show that the posterior-inferior corner of the stapes footplate is the stiffest region of the annular ligament. This method can potentially help to establish a correlation between stiffness and damping characteristics of the annular ligament and inertia properties of the stapes and, thus, help to reduce the number of independent parameters in the model-based hearing diagnosis.
Due to the large interindividual variances and the poor optical accessibility of the ear, the specificity of hearing diagnostics today is severely restricted to a certain clinical picture and quantitative assessment. Often only a yes or no decision is possible, which depends strongly on the subjective assessment of the ENT physician. A novel approach, in which objectively obtainable, non invasive audiometric measurements are evaluated using a numerical middle ear model, makes it possible to make the hidden middle ear properties visible and quantifiable. The central topic of this paper is a novel parameter identification algorithm that combines inverse fuzzy arithmetic with an artificial neural network in order to achieve a coherent diagnostic overall picture in the comparison of model and measurement. Its usage is shown at a pathological pattern called malleus fixation where the upper ligament of the malleus is pathologically stiffened.
Type 1 diabetes is a chronic and a life threatening disease: an adjusted treatment and a proper management of the disease are crucial to prevent or delay the complications of diabetes. Although during the last decade the development of the artificial pancreas has presented great advances in diabetes care, the multiple daily injections therapy still represents the most widely used treatment option for type 1 diabetes. This work presents the proposal and first development stages of an application focused on guiding patients using the continuous glucose monitors and smart pens together with insulin and carbohydrates recommendations. Our proposal aims to develop a platform to integrate a series of innovative machine learning models and tools rigorously tested together with the use of the latest IoT devices to manage type 1 diabetes. The resulting system actually closes the loop, like the artificial pancreas, but in an intermittent way.
Due to the rising need for palliative care in Russia, it is crucial to provide timely and high-quality solutions for patients, relatives, and caregivers. A methodology for remote monitoring of patients in need of palliative care and the requirements will be developed for a hardware-software complex for remote monitoring of patients' health at home.
The potentials and opportunities created by digitized healthcare can be further customized through smart data processing and analysis using accurate patient information. This development and the associated new treatment concepts basing on digital smart sensors can lead to an increase in motivation by applying gamification approaches. This effect can also be used in the field of medical treatment, e.g. with the help of a digital spirometer combined with an app. In one of our exemplary applications, we show how to control an airplane within an app by breathing respectively inhaling and exhaling. Using this biofeedback within a game allows us to increase the motivation and fun for children that need to perform necessary exercises.