Jens Spehr

The Lower Saxony research network design of environments for ageing: towards interdisciplinary research on information and communication technologies in ageing societies

Worldwide, ageing societies are bringing challenges for independent living and healthcare. Health-enabling technologies for pervasive healthcare and sensor-enhanced health information systems offer new opportunities for care. In order to identify, implement and assess such new information and communication technologies (ICT) the ‘Lower Saxony Research Network Design of Environments for Ageing’ (GAL) has been launched in 2008 as interdisciplinary research project. In this publication, we inform about the goals and structure of GAL, including first outcomes, as well as to discuss the potentials and possible barriers of such highly interdisciplinary research projects in the field of health-enabling technologies for pervasive healthcare. Although GALs high interdisciplinarity at the beginning slowed down the speed of research progress, we can now work on problems, which can hardly be solved by one or few disciplines alone. Interdisciplinary research projects on ICT in ageing societies are needed and recommended.

Defining the user requirements for wearable and optical fall prediction and fall detection devices for home use

One of the major problems in the development of information and communication technologies for older adults is user acceptance. Here we describe the results of focus group discussions that were conducted with older adults and their relatives to guide the development of assistive devices for fall detection and fall prevention. The aim was to determine the ergonomic and functional requirements of such devices and to include these requirements in a user-centered development process. A semi-structured interview format based on an interview guide was used to conduct three focus group discussions with 22 participants. The average age was 75 years in the first group, 68 years in the second group and 50 years in the third group (relatives). Overall, participants considered a fall prediction system to be as important as a fall detection system. Although the ambient, unobtrusive character of the optical sensor system was appreciated, wearable inertial sensors were preferred because of their wide range of use, which provides higher levels of security. Security and mobility were two major reasons for people at risk of falling to buy a wearable and/or optical fall prediction and fall detection device. Design specifications should include a wearable, non-stigmatising sensor at the users wrist, with an emergency option in case of falling.

Monitoring systems for the support of home care.

In this article, the design of a system for the ambient, unobtrusive and automatic monitoring of Activities of Daily Living (ADL) is described. In the context of the growing imbalance between (potentially young) caregivers and (most often older) people receiving care, technical monitoring systems may help to organise care more efficiently and to identify degrading abilities very early to trigger preventive measures. To improve the acceptance of the system described in this article, the selection process of the sensors to be integrated into the flat or to be worn by the older people has been steered by the results of focus group interviews with older people, their relatives and professional caregivers. The interviews revealed that these people would in general accept such systems, but security, mobility and communication aspects have to be clearly and appropriately addressed. In an experimental study the recognition rate of the activity ‘preparation and intake of food or beverages’ has been measured with two age groups (6 subjects, age between 25 and 40/mean 30 years and 5 subjects, age between 72 and 84/mean 75.3 years). The food preparation was detected with a sensitivity of 74.7% and a specificity of 84.2% using a vision sensor.

Information and communication technologies for promoting and sustaining quality of life, health and self-sufficiency in ageing societies – outcomes of the Lower Saxony Research Network Design of Environments for Ageing (GAL)

Many societies across the world are confronted with demographic changes, usually related to increased life expectancy and, often, relatively low birth rates. Information and communication technologies (ICT) may contribute to adequately support senior citizens in aging societies with respect to quality of life and quality and efficiency of health care processes. For investigating and for providing answers on whether new information and communication technologies can contribute to keeping, or even improving quality of life, health and self-sufficiency in ageing societies through new ways of living and new forms of care, the Lower Saxony Research Network Design of Environments for Ageing (GAL) had been established as a five years research project, running from 2008 to 2013. Ambient-assisted living (AAL) technologies in personal and home environments were especially important. In this article we report on the GAL project, and present some of its major outcomes after five years of research. We report on major challenges and lessons learned in running and organizing such a large, inter- and multidisciplinary project and discuss GAL in the context of related research projects. With respect to research outcomes, we have, for example, learned new knowledge about multimodal and speech-based human–machine-interaction mechanisms for persons with functional restrictions, and identified new methods and developed new algorithms for identifying activities of daily life and detecting acute events, particularly falls. A total of 79 apartments of senior citizens had been equipped with specific “GAL technology”, providing new insights into the use of sensor data for smart homes. Major challenges we had to face were to deal constructively with GAL’s highly inter- and multidisciplinary aspects, with respect to research into GAL’s application scenarios, shifting from theory and lab experimentation to field tests, and the complexity of organizing and, in our view, successfully managing such a large project. Overall it can be stated that, from our point of view, the GAL research network has been run successfully and has achieved its major research objectives. Since we now know much more on how and where to use AAL technologies for new environments of living and new forms of care, a future focus for research can now be outlined for systematically planned studies, scientifically exploring the benefits of AAL technologies for senior citizens, in particular with respect to quality of life and the quality and efficiency of health care.

Hierarchical pose estimation for human gait analysis

Articulated structures like the human body have many degrees of freedom. This makes an evaluation of the configurations likelihood very challenging. In this work we propose new linked hierarchical graphical models which are able to efficiently evaluate likelihoods of articulated structures by sharing visual primitives. Instead of evaluating all configurations of the human body separately we take advantage of the fact that different configurations of the human body share body parts, and body parts, in turn, share visual primitives. A hierarchical Markov random field is used to integrate the sharing of visual primitives in a probabilistic framework. We propose a scalable hierarchical representation of the human body and show that this representation is especially well suited for human gait analysis from a frontal camera perspective. Furthermore, the results of the evaluation on a gait dataset show that sharing primitives substantially accelerates the evaluation and that our hierarchical probabilistic framework is a robust method for scalable detection of the human body.

Using the shadow as a single feature for real-time monocular vehicle pose determination

In this work we propose a way to detect vehicles in monocular camera images and determine their position and orientation on the ground plane relative to the camera. The camera does not need to be stationary which allows the method to be used in mobile applications. Its results can therefore serve as an input to advanced driver assistance systems (ADAS). The single feature used is the shadow beneath the vehicles. We implemented a real-time applicable method to detect these shadows under strongly varying conditions and determine the corresponding vehicle pose. Finally we evaluate our results by comparing them to ground truth data.

Hierarchical scene understanding for intelligent vehicles

One of the main tasks of intelligent vehicles is the extraction of information from the vehicles surroundings and the understanding of the extracted information. The understanding of the environment allows the vehicle to drive autonomously or to support the driver in difficult or dangerous situations. In this paper we propose a vision-based hierarchical interpretation approach. First, we consider one single physical camera as a set of virtual sensors, where each virtual sensor gathers a type of 3d information. Then, the 3d information of this set is converted to high-level information that allows further reasoning. The interpretation is based on a hierarchical scene representation, where objects are recognized using nonparametric belief propagation. To demonstrate this approach we adopted the scene understanding to a parking spot finding application and show that it is real-time applicable and reliable even for multiple camera (on-board) systems.

Human Behavior Analysis

Due to the wide range of applications human action recognition and its representation is a popular research topic. The aim of action recognition is to automatically identify the action of a person based on some kind of sensor data. In this monograph, we focus on vision sensors that provide a stream of images over time. Detection of human actions or activities based on a video stream is challenging mainly due to the following two processing steps. First, the person has to be detected within the images and its pose has to be estimated, which is very complex due to themany degrees of freedom of the human body (see Chap. 6). In the context of action recognition the pose estimation step is often replaced by the calculation of a motion descriptor.

Hierarchical Graphical Models

The goal of the proposed hierarchical graphical models is to recognize various instances of different object classes in images, image sequences or other scene representations like e.g. occupancy grid maps. The term “object” in this context is used as a general term representing visual objects, visual parts, visual features, visual primitives, but also activities, actions or motion primitives. In the following we will regard two different kinds of hierarchies:A compositional hierarchy and a similarity hierarchy. In compositional hierarchies the structure of a parent node is defined by its children, where edges define the spatial or spatiotemporal relation between the parent and the children nodes. In this manner complex high-level nodes can be recursively defined based on simple low-level features. Similarity hierarchies, on the other hand, describe similarities among objects, and among parts. In this work, they will be combined with a coarse-to-fine search by means of scale space representation. They are used to increase the robustness of the representation as well as the overall runtime performance.

Human Pose Estimation

The aim of human pose estimation is to detect and estimate the configuration of the articulation structure of a person. Human pose estimation has become a popular research topic including a wide range of approaches. Marker-based approaches, for example, are one of the most precise methods, but they need special markers attached to the human body. In this work we concentrate on monocular vision-based approaches, which are not using additional means like markers. We are also not using other common methods like foreground-background segmentation or temporal tracking in order to guarantee that our approach is independent of the quality of such methods.