Background Critical illness myopathy (CIM) and polyneuropathy (CIP) are a common complication of critical illness. Both cause intensive-care-unit-acquired (ICU-acquired) muscle weakness (ICUAW) which increases morbidity and delays rehabilitation and recovery of activities of daily living such as walking ability. Focused physical rehabilitation of people with ICUAW is, therefore, of great importance at both an individual and a societal level. A recent systematic Cochrane review found no randomised controlled trials (RCT), and thus no supporting evidence, for physical rehabilitation interventions for people with defined CIP and CIM to improve activities of daily living. Therefore, the aim of our study is to compare the effects of an additional physiotherapy programme with systematically augmented levels of mobilisation with additional in-bed cycling (as the parallel group) on walking and other activities of daily living.

Background Critical illness myopathy (CIM) and polyneuropathy (CIP) are a common complication of critical illness. Both cause intensive-care-unit-acquired (ICU-acquired) muscle weakness (ICUAW) which increases morbidity and delays rehabilitation and recovery of activities of daily living such as walking ability. Focused physical rehabilitation of people with ICUAW is, therefore, of great importance at both an individual and a societal level. A recent systematic Cochrane review found no randomised controlled trials (RCT), and thus no supporting evidence, for physical rehabilitation interventions for people with defined CIP and CIM to improve activities of daily living. Therefore, the aim of our study is to compare the effects of an additional physiotherapy programme with systematically augmented levels of mobilisation with additional in-bed cycling (as the parallel group) on walking and other activities of daily living.

Background: Maintaining independence in instrumental activities of daily living (IADL) is crucial for older adults. This study explored the association between cognitive and functional performance in general and in single IADL domains. Also, risk factors for developing IADL impairment were assessed. Methods: Here, 3,215 patients aged 75–98 years were included. Data were collected during home visits. Results: Cognitive functioning was associated with IADL both cross-sectionally and longitudinally. Regarding the single IADL domains cross-sectionally, executive functioning was especially associated with shopping, while episodic memory was associated with responsibility for own medication. Conclusion: Reduced performance in neuropsychological tests is associated with a greater risk of current and subsequent functional impairment.

Due to the continuous ageing of our society, both the care and the health sector will encounter challenges in maintaining the quality of human care and health standards. While the number of people with diseases such as dementia and physical illness will be rising, we are simultaneously recording a lack of medical personnel such as caregivers and therapists. One possible approach that tackles the described problem is the employment of technical assistance systems that support both medical personnel and elderly living alone at home. This thesis presents approaches to provide assistance for these target groups. In this work, algorithms that are integrated in prototypical assistance systems for vision-based human daily activity, mobility and motion analysis have been developed. The developed algorithms process 3-D point clouds as well as skeleton joint positions to generate meta information concerning activities and the mobility of elderly persons living alone at home. Such type of information was not accessible so far and is now available for monitoring. By generating this meta information, a basis for the detection of long-term and short-term health changes has been created. Besides monitoring meta information, mobilisation for maintaining physical capabilities, either ambulatory or at home, is a further focus of this thesis. Algorithms for the qualitative assessment of physical exercises were therefore investigated. Thereby, motion sequences in the form of skeleton joint trajectories as well as the heat development in active muscles were considered. These algorithms enable an autonomous physical training under the supervision of a virtual therapist even at home. / Aufgrund der voranschreitenden Überalterung unserer Gesellschaft werden sowohl der Pflege- als auch der Gesundheitssektor vor enorme Herausforderungen gestellt. Während die Zahl an vorrangig altersbedingten Erkrankungen, wie Demenz oder physische Erkrankungen des Bewegungsapparates, weiterhin zunehmen wird, stagniert die Zahl an medizinischem Fachpersonal, wie Therapeuten und Pflegekräften. An dieser Stelle besteht das Ziel, die Qualität medizinischer Leistungen auf hohem Niveau zu halten und dabei die Einhaltung von Pflege- und Gesundheitsstandards sicherzustellen. Ein möglicher Ansatz hierfür ist der Einsatz technischer Assistenzsysteme, welche sowohl das medizinische Personal und Angehörige entlasten als auch ältere, insbesondere allein lebende Menschen zu Hause unterstützen können. Die vorliegende Arbeit stellt Ansätze zur Unterstützung der genannten Zielgruppen vor, die prototypisch in Assistenzsystemen zur visuellen, kamerabasierten Analyse von täglichen Aktivitäten, von Mobilität und von Bewegungen bei Trainingsübungen integriert sind. Die entwickelten Algorithmen verarbeiten dreidimensionale Punktwolken und Gelenkpositionen des menschlichen Skeletts, um sogenannte Meta-Daten über tägliche Aktivitäten und die Mobilität einer allein lebenden Person zu erhalten. Diese Informationen waren bis jetzt nicht verfügbar, können allerdings für den Patienten selbst, für medizinisches Personal und Angehörige aufschlussreich sein, denn diese Meta-Daten liefern die Grundlage für die Detektion kurz- und langfristiger Veränderungen im Verhalten oder in der Mobilität, die ansonsten wahrscheinlich unbemerkt geblieben wären. Neben der Erfassung solcher Meta-Informationen liegt ein weiterer Fokus der Arbeit in der Mobilisierung von Patienten durch angeleitetes Training, um ihre Mobilität und körperliche Verfassung zu stärken. Dabei wurden Algorithmen zur qualitativen Bewertung und Vermittlung von Korrekturhinweisen bei physischen Trainingsübungen entwickelt, die auf Trajektorien von Gelenkpositionen und der Wärmeentwicklung in Muskeln beruhen. Diese Algorithmen ermöglichen aufgrund der Nachahmung eines durch den Therapeuten gegebenen Feedbacks ein autonomes Training.