Chapter User Experience Results of Setting Free a Service Robot for Older Adults at Home

The chapter presents the analysis of user trials where, for the first time, a service robot was set free in the home of users. Different to previous studies there was no pre-specified schedule of tasks to execute. The goal was to show that useful functionalities for users can also be achieved with the low-cost components of the Hobbit robot. With the one-arm mobile service robot Hobbit we provided users with a service robot running basic robot functionalities such as navigation, grasping objects from the floor, emergency handling, entertainment, fitness and communication functions. Users could freely select what to do over the three-week trials in homes in three European countries. Users have been questioned on what functionality would help them to stay longer at home and live independently. Results provide better insights of what users want than in pre-set scenarios, where many of the factors we encountered do not show up. Good examples are the need to have robots navigate autonomously at home, grasping objects from the floor is a highly valued function, and the robot needs to adapt locations depending on the daily liking of the users who move much more freely at home than in pre-set scenarios

Glycogen Storage Disease Type Ia:Current Management Options, Burden and Unmet Needs

Glycogen storage disease type Ia (GSDIa) is caused by defective glucose-6-phosphatase, a key enzyme in carbohydrate metabolism. Affected individuals cannot release glucose during fasting and accumulate excess glycogen and fat in the liver and kidney, putting them at risk of severe hypoglycaemia and secondary metabolic perturbations. Good glycaemic/metabolic control through strict dietary treatment and regular doses of uncooked cornstarch (UCCS) is essential for preventing hypoglycaemia and long-term complications. Dietary treatment has improved the prognosis for patients with GSDIa; however, the disease itself, its management and monitoring have significant physical, psychological and psychosocial burden on individuals and parents/caregivers. Hypoglycaemia risk persists if a single dose of UCCS is delayed/missed or in cases of gastrointestinal intolerance. UCCS therapy is imprecise, does not treat the cause of disease, may trigger secondary metabolic manifestations and may not prevent long-term complications. We review the importance of and challenges associated with achieving good glycaemic/metabolic control in individuals with GSDIa and how this should be balanced with age-specific psychosocial development towards independence, management of anxiety and preservation of quality of life (QoL). The unmet need for treatment strategies that address the cause of disease, restore glucose homeostasis, reduce the risk of hypoglycaemia/secondary metabolic perturbations and improve QoL is also discussed.</p

Inclusion of service robots in the daily lives of frail older users: a step-by-step definition procedure on users' requirements

The implications for the inclusion of robots in the daily lives of frail older adults, especially in relation to these population needs, have not been extensively studied. The “Multi-Role Shadow Robotic System for Independent Living” (SRS) project has developed a remotelycontrolled, semi-autonomous robotic system to be used in domestic environments. The objective of this paper is to document the iterative procedure used to identify, select and prioritize user requirements. Seventy-four requirements were identified by means of focus groups, individual interviews and scenario-based interviews. The list of user requirements, ordered according to impact, number and transnational criteria, revealed a high number of requirements related to basic and instrumental activities of daily living, cognitive and social support and monitorization, and also involving privacy, safety and adaptation issues. Analysing and understanding older users’ perceptions and needs when interacting with technological devices adds value to assistive technology and ensures that the systems address currently unmet needs

Current concepts in the prevention of pathogen transmission via blood/plasma-derived products for bleeding disorders

The pathogen safety of blood/plasma-derived products has historically been a subject of significant concern to the medical community. Measures such as donor selection and blood screening have contributed to increase the safety of these products, but pathogen transmission does still occur. Reasons for this include lack of sensitivity/specificity of current screening methods, lack of reliable screening tests for some pathogens (e.g. prions) and the fact that many potentially harmful infectious agents are not routinely screened for. Methods for the purification/inactivation of blood/plasma-derived products have been developed in order to further reduce the residual risk, but low concentrations of pathogens do not necessarily imply a low level of risk for the patient and so the overall challenge of minimising risk remains. This review aims to discuss the variable level of pathogenic risk and describes the current screening methods used to prevent/detect the presence of pathogens in blood/plasma-derived products

Enabling Autonomous Robotic Grasping based on Topographic Features

Abweichender Titel laut Übersetzung der Verfasserin/des VerfassersZsfassung in dt. SpracheUsed in industry in manufacturing chains for decades, robots are nowadays entering their way into private households. Their functionality is still limited to vacuum cleaning or mowing the lawn. One of the reason why no universally usable robot- butler has reached marketability, is the limited capability of robot-interaction with its environment, in specific object manipulation and grasping. This thesis presents a novel approach to tackle the open grasping problem by learning suitable grasps from Topographic Features. Factors increasing grasp complexity such as unknown objects, incomplete object surface data and visually not segmentable object piles are thereby taken into account. An integrated system for grasping is presented, capable for grasping known and unknown single objects, as well as objects from piles or in cluttered scenes, given a point cloud. The method is based on the topography of a given scene and abstracts grasp-relevant structures to enable machine learning techniques for grasping tasks. A description of the Topographic Features, -Height Accumulated Features- (HAF) and their extension, -Symmetry Height Accumulated Features- (SHAF) is given, and the approach is motivated. The grasp quality is investigated using an F-score metric. The gain and the expressive power of HAF is demonstrated by comparing its trained classifier to one that resulted from training on simple height grids. An efficient way to calculate HAF is presented. A description is given how the trained grasp classifier is used to explore the whole grasp space and a heuristic to find the most robust grasp is introduced. This thesis describes how to use the approach to adapt the robotic hand opening width before grasping. In robotic experiments different aspects of the system are demonstrated on four robot platforms: A Schunk 7-DOF arm, a PR2, the mobile service robot Hobbit and a Kuka LWR arm. Tasks to grasp single objects, autonomously unload a box, clear the table and tidy up the floor were performed. Thereby it is shown that the approach is easily adaptable and robust with respect to different robotic hands. As part of the experiments the algorithm was compared to a state-of-the-art method and showed significant improvements. Concrete examples are used to illustrate the benefit of the approach compared to established grasp approaches. Finally, advantages of the symbiosis between the approach presented and object recognition are shown.Used in industry in manufacturing chains for decades, robots are nowadays entering their way into private households. Their functionality is still limited to vacuum cleaning or mowing the lawn. One of the reason why no universally usable robot- butler has reached marketability, is the limited capability of robot-interaction with its environment, in specific object manipulation and grasping. This thesis presents a novel approach to tackle the open grasping problem by learning suitable grasps from Topographic Features. Factors increasing grasp complexity such as unknown objects, incomplete object surface data and visually not segmentable object piles are thereby taken into account. An integrated system for grasping is presented, capable for grasping known and unknown single objects, as well as objects from piles or in cluttered scenes, given a point cloud. The method is based on the topography of a given scene and abstracts grasp-relevant structures to enable machine learning techniques for grasping tasks. A description of the Topographic Features, -Height Accumulated Features- (HAF) and their extension, -Symmetry Height Accumulated Features- (SHAF) is given, and the approach is motivated. The grasp quality is investigated using an F-score metric. The gain and the expressive power of HAF is demonstrated by comparing its trained classifier to one that resulted from training on simple height grids. An efficient way to calculate HAF is presented. A description is given how the trained grasp classifier is used to explore the whole grasp space and a heuristic to find the most robust grasp is introduced. This thesis describes how to use the approach to adapt the robotic hand opening width before grasping. In robotic experiments different aspects of the system are demonstrated on four robot platforms: A Schunk 7-DOF arm, a9

network analysis for detection of insurance fraud in health insurance

Arbeit an der Bibliothek noch nicht eingelangt - Daten nicht geprüftAbweichender Titel nach Übersetzung der Verfasserin/des VerfassersDurch Versicherungsbetrug entsteht in der Versicherungswirtschaft jährlich ein großer finanzieller und reputativer Schaden. Dabei ist der Nachweis von Versicherungsbetrug oft nur sehr schwer bzw. unter hohem Aufwand möglich. Methoden, die das Aufspüren von betrügerischem Verhalten erleichtern sind deshalb sehr gefragt. Diese Arbeit beschäftigt sich konkret mit Versicherungsbetrug in der gesetzlichen Krankenversicherung. Studien zufolge sind dort vor allem Dienstleister des Gesundheitsbereichs die Haupttäter. Das in dieser Arbeit vorgestellte Modell, versucht mit Hilfe von Graphen- und Netzwerkanalyse betrügerisches Verhalten von Anbietern ausfindig zu machen. Im Modell wird ein zu untersuchender Anbieter mit jenen verglichen, die bereits dem Versicherungsbetrug überführt worden sind. Der Vergleich bezieht sich neben dem Verschreibungsverhalten von Medikamenten und Behandlungen auch auf den Standort eines Anbieters. Gleichzeitig wird der Vergleich aber auch mit Anbietern durchgeführt, die noch aktiv an der gesetzlichen Krankenversicherung teilnehmen. Die so gewonnenen Ähnlichkeiten dienen als Eingabewerte für verschiedene binäre Klassifikationsalgorithmen. Diese ermitteln für einen zu untersuchenden Anbieter, ob dieser ein verdächtiges Verhalten aufweist. Ziel dieser Arbeit ist es, das Modell zu erörtern und die dazugehörige Theorie durchzuarbeiten. Im praktischen Teil wird anschließend die Performance der drei binären Klassifikationsalgorithmen Entscheidungsbaum, Random Forest und neuronales Netzwerk miteinander verglichen. Außerdem werden verschiedene Ähnlichkeitsmaße verwendet, um so eine optimale Konfiguration für diese Anwendung zu finden. Als Resultat hat sich gezeigt, dass ein neuronales Netzwerk zusammen mit der verbesserte Wurzel-Kosinus-Ähnlichkeit das beste Ergebnis liefert. In der Praxis kann dieses Ergebnis als eine Vorauswahl von Anbietern verwendet werden, bei denen es sich lohnt, genauere Nachforschungen anzustellen.Insurance fraud causes great financial and reputational damage in the insurance industry every year. At the same time, the detection of insurance fraud is often very difficult or requires a great deal of effort. Methods that facilitate the detection of fraudulent behavior are therefore in great demand. This master thesis deals specifically with insurance fraud in the federal health insurance sector. According to studies, service providers are the main perpetrators. The model presented in this thesis, attempts to detect fraudulent behavior of providers using graph and network analysis. In the model, a provider under investigation is compared to those who have already been convicted of insurance fraud. The comparison is based on a providers location in addition to prescribing behavior for medications and treatments. At the same time the comparison is also made with providers who are still actively participating in the public health insurance system. The similarities thus obtained serve as input values for various binary classification algorithms. These determine for a provider under investigation whether it exhibits suspicious behavior. The aim of this paper is to discuss the model and to work through the associated theory. In the practical part, the performance of the three binary classification algorithms decision tree, random forest and neural network is then compared. Furthermore, different similarity measures are used in order to find an optimal configuration for this application. As a result, it has been shown that a neural network together with the improved sqrt-cosine similarity gives the best result. In practice, this result can be used as a preselection of providers where it is necessary to do more detailed research.6

Grasping Objects From the Floor in Assistive Robotics: Real World Implications and Lessons Learned

This paper presents a system enabling a mobile robot to autonomously pick-up objects a human is pointing at from the oor. The system does not require object models and is designed to grasp unknown objects. The robot decides by itself if an object is suitable for grasping by considering measures of size, position and the environment suitability. The implementation is built on the second prototype of the home care robot Hobbit, thereby verifying that complex robotic manipulation tasks can be performed with economical hardware. The presented system was already tested in real apartments with elderly people. We highlight this by discussing the additional complexity for complete autonomous behavior in apartments compared with tests in labs.This work was supported in part by the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant 288146, HOBBIT, in part by the Spanish Ministry of Science, Innovation and Universities through the project COGDRIVE - Arti cial Intelligence Techniques and Assistance to Autonomous Navigation under Grant DPI2017-86915-C3-3-R, in part by the RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub, under Grant S2018/NMT-4331, in part by the Programas de Actividades ICD en la Comunidad de Madrid, and in part by the Structural Funds of the EU.Peer reviewe

Robot Navigation in Domestic Environments: Experiences Using RGB-D Sensors in Real Homes

Future home and service robots will require advanced navigation and interaction capabilities. In particular, domestic environments present open challenges that are hard to identify by conducting controlled tests in home-like settings: there is the need to test and evaluate navigation in the actual homes of users. This paper presents the experiences of operating a mobile robot with manipulation capabilities and an open set of tasks in extensive trials with real users, in their own homes. The main difficulties encountered are the requirement to move safely in cluttered 3D environments, the problems related to navigation in narrow spaces, and the need for an adaptive rather than fixed way to approach the users. We describe our solutions based on RGB-D perception and evaluate the integrated system for navigation in real home environments, pointing out remaining challenges towards more advanced commercial solutions.This work has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No 288146.Peer reviewe

Chapter User Experience Results of Setting Free a Service Robot for Older Adults at Home

The chapter presents the analysis of user trials where, for the first time, a service robot was set free in the home of users. Different to previous studies there was no pre-specified schedule of tasks to execute. The goal was to show that useful functionalities for users can also be achieved with the low-cost components of the Hobbit robot. With the one-arm mobile service robot Hobbit we provided users with a service robot running basic robot functionalities such as navigation, grasping objects from the floor, emergency handling, entertainment, fitness and communication functions. Users could freely select what to do over the three-week trials in homes in three European countries. Users have been questioned on what functionality would help them to stay longer at home and live independently. Results provide better insights of what users want than in pre-set scenarios, where many of the factors we encountered do not show up. Good examples are the need to have robots navigate autonomously at home, grasping objects from the floor is a highly valued function, and the robot needs to adapt locations depending on the daily liking of the users who move much more freely at home than in pre-set scenarios