Lena Dasenbrock

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.

Multimodal activity monitoring for home rehabilitation of geriatric fracture patients--feasibility and acceptance of sensor systems in the GAL-NATARS study.

Background: Demographic change will lead to a diminishing care workforce faced with rising numbers of older persons in need of care, suggesting meaningful use of health-enabling technologies, and home monitoring in particular, to contribute to supporting both the carers and the persons in need. Objectives: We present and discuss the GAL-NATARS study design along with first results regarding technical feasibility of long-term home monitoring and acceptance of different sensor modalities. Methods: Fourteen geriatric participants with mobility-impairing fractures were recruited in three geriatric clinics. Following inpatient geriatric rehabilitation, their homes were equipped with ambient sensor components for three months. Additionally, a wearable accelerometer was employed. Technical feasibility was assessed by system and component downtimes, technology acceptance by face-to-face interviews. Results: The overall system downtime was 6%, effected by two single events, but not by software failures. Technology acceptance was rated very high by all participants at the end of the monitoring periods, and no interference with their social lives was reported. Discussion and conclusions: Home-monitoring technologies were well-accepted by our participants. The information content of the data still needs to be evaluated with regard to clinical outcome parameters as well as the effect on the quality of life before recommending large-scale implementations.

Technology Supported Geriatric Assessment

Healthy aging is a core societal aim especially regarding the demographic change. But with aging, functional decline can occur and this is a major challenge for health care systems. For the evaluation of the health of older adults and the identification of early changes associated with functional and cognitive decline, clinical geriatric assessments are a well-established approach. Ideally, the assessments should take place at home of the older adults or even in their daily life, to get an unbiased functional status. Therefore, we introduce a technology supported geriatric assessment as an intermediate step to a home-assessment or in future to sensor-based-assessments in daily life. Beside various ambient sensors, a sensor belt is used during the assessments and for 1 week in the participants’ daily life. We discuss the suitability of our measuring devices for an ambient home-assessment and evaluate the sensors in comparison to valid measurements. Thereby, we show that light barrier measurements achieve a high sensitivity and a good correlation to manual measurements through study nurses or physical therapists.

Stair Climb Power Measurements via Inertial Measurement Units - Towards an Unsupervised Assessment of Strength in Domestic Environments.

In order to initiate interventions at an early stage of functional decline and thus, to extend independent living, the early detection of changes in functional ability is important. The Stair Climb Power Test (SCPT) is a standard test in geriatric assessments for strength as one of the essential components of functional ability. This test is also well suited for regular and frequent power measurements in daily life since the activity of climbing stairs is usually frequently performed. We introduce an automated assessment of the SCPT based on inertial measurement units (IMU) in a study of 83 participants aged 70-87 years. For power evaluations of the lower extremities, the activity of climbing stairs was automatically classified via machine learning and the power was calculated based on the test duration and covered height. Climbing stairs was correctly classified in 93% of the cases. We also achieved a good correlation of the power calculations with the conventional stop watch measurements with a mean deviation of 2.35%. The system’s sensitivity to detect the transition towards frailty has been confirmed. Furthermore, we discussed the general suitability of the automated stair climb power algorithm in unsupervised, standardized

Understanding Jump Landing as an Oscillating System: A Model-based Approach of Balance and Strength Analyses.

Counter movement jumps (CMJ) are well-suited to measure the muscle power and balance. Since it has been clarified that well accepted CMJ amplification-based balance measures (such as TTS or CoP) are significantly influenced by algorithmic, and measurement settings and thus, measurement results have limited meaningfulness among force platforms, we introduce a new model-based approach measuring the postural stability. In this, during the landing and recovery phases after vertical jumps, the lower extremities can be represented by an oscillating system and the corresponding transfer function is described by a second-order delay (PT2)

A novel approach for discovering human behavior patterns using unsupervised methods

BackgroundAs is well known, elderly people gradually lose the ability of self-care. The decline can be reflected in changes in their daily life behavior. A solution to assess their health status is to design sensor-enhanced living environments to observe their behavior, in which unobtrusive sensors are usually used. With respect to information extraction from the dataset collected by means of these kinds of sensors, unsupervised methods have to be relied on for practical application. Under the assumption that human lifestyle is associated with health status, this study intends to propose a novel approach to discover behavior patterns using unsupervised methods.MethodsTo evaluate the feasibility of this approach it was applied to datasets collected in the GAL-NATARS study. The study is part of the Lower Saxony research network Design of Environments for Aging (GAL) and conducted in subjects’ home environments. The subjects recruited in GAL-NATARS study are older people (age ≥ 70 years), who are discharged from hospital to live alone again at their homes after treatment of a femoral fracture.ResultsThe change of lifestyle regularity is measured. By analyzing the correlation between the extracted information and medical assessment results of four subjects, two of them exhibited impressive association and the other two showed less association.ConclusionsThe approach may provide complementary information for health assessment; however, the dominant relationship between the change of behavior patterns and the health status has to be shown and datasets from more subjects must be collected in future studies.LimitationsMerely environmental data were used and no wearable sensor for activity detection or vital parameter measurement is taken into account. Therefore, this cannot comprehensively reflect reality.ZusammenfassungHintergrundDass ältere Menschen allmählich Selbstsorgekompetenzen verlieren, ist weithin bekannt. Der allmähliche Verlust kann sich in Veränderungen des Verhaltens im Alltagsleben widerspiegeln. Eine Möglichkeit zur Überprüfung ihres gesundheitlichen Zustands ist die Entwicklung sensorgestützter Lebensumfelder, um ihr Verhalten zu beobachten. Dabei werden in der Regel unauffällige Sensoren verwendet. Im Hinblick auf die Extrahierung von Informationen aus den so gesammelten Datensätzen verlässt man sich für die praktische Anwendung auf nichtsupervidierte Methoden. Ausgehend von der Annahme, dass Lifestyle und Gesundheitszustand miteinander zusammenhängen, zielt diese Studie auf einen innovativen Ansatz, Verhaltensmuster mit nichtsupervidierten Methoden zu detektieren.MethodenUm die Machbarkeit dieses Ansatzes zu evaluieren wurde er auf die in der GAL-NATARS-Studie generierten Datensätze angewendet; vom niedersächsischen Forschungsnetzwerk Design of Environments for Aging (GAL) wird diese Studie im Wohnumfeld der Probanden durchgeführt. Die allein lebenden Probanden der GAL-NATARS-Studie waren ≥ 70 Jahre alt und nach stationärer Behandlung einer Femurfraktur wieder in ihr häusliches Umfeld entlassen worden.ErgebnisseGemessen wurden die Veränderungen in der Regelmäßigkeit des Lebensstils. Bei 4 Probanden wurden die extrahierten Informationen und die Ergebnissen des medizinischen Assessments miteinander korreliert: Bei 2 von ihnen zeigte sich ein eindrucksvoller Zusammenhang, bei den anderen beiden fand sich weniger Assoziation.SchlussfolgerungenZwar kann der untersuchte Ansatz zusätzliche Informationen für das medizinische Assessment liefern, doch die dominante Beziehung zwischen den Änderungen in Verhaltensmustern und dem Gesundheitszustand ist noch darzustellen. In künftigen Studien müssen noch mehr Patientendatensätze gesammelt werden.EinschränkungenVerwendet werden lediglich Umweltdaten, keine Daten von tragbaren Sensoren zur Registrierung von Aktivität bzw. Vitalparametern. Daher können die Ergebnisse die Wirklichkeit nicht umfassend wiedergeben.

Towards an Automated Unsupervised Mobility Assessment for Older People Based on Inertial TUG Measurements

One of the most common assessments for the mobility of older people is the Timed Up and Go test (TUG). Due to its sensitivity regarding the indication of Parkinson’s disease (PD) or increased fall risk in elderly people, this assessment test becomes increasingly relevant, should be automated and should become applicable for unsupervised self-assessments to enable regular examinations of the functional status. With Inertial Measurement Units (IMU) being well suited for automated analyses, we evaluate an IMU-based analysis-system, which automatically detects the TUG execution via machine learning and calculates the test duration. as well as the duration of its single components. The complete TUG was classified with an accuracy of 96% via a rule-based model in a study with 157 participants aged over 70 years. A comparison between the TUG durations determined by IMU and criterion standard measurements (stopwatch and automated/ambient TUG (aTUG) system) showed significant correlations of 0.97 and 0.99, respectively. The classification of the instrumented TUG (iTUG)-components achieved accuracies over 96%, as well. Additionally, the system’s suitability for self-assessments was investigated within a semi-unsupervised situation where a similar movement sequence to the TUG was executed. This preliminary analysis confirmed that the self-selected speed correlates moderately with the speed in the test situation, but differed significantly from each other.

A Model-Based Approach for Jump Analyses Regarding Strength and Balance

To identify the functional decline as related to aging, geriatric assessments are an established instrument. Within such assessments, the functional ability is evaluated and consists of the three major components: strength, mobility, and balance. Counter movement jumps (CMJ) are well-suited to test these three essential elements of functional ability within a single assessment item. Since common balance measures have been shown to be significantly prone to algorithmic and technical variations, a robust alternative method is required. Thus, we introduce a model-based approach for balance and strength analyses, where the human lower extremities are modeled as an oscillating system during the phase of landing and recovery after a vertical jump. In the System and Control Technology, a transfer function of an oscillating system is described by a second-order delay element (PT2-element), which is characterized by the parameters natural frequency and damping. We analyze the jumps of 30 participants (70–87 years) regarding their jump phases and the mentioned parameters. A linear correlation between jump power and jump height, which are sensitive indicators of the muscle performance and the strength could be confirmed. While a correlation between jump power and spring constant could be observed, a significant relationship between the balance ability and natural frequency could not be identified.