Thomas Frenken

Precise assessment of self-selected gait velocity in domestic environments

A novel approach to precise and reliable computation of self-selected gait velocity in domestic environments based on the measurements of a laser range scanner is presented. The computation does not require a priori knowledge of the environment. The sensor is part of an ambient assessment system under development which is meant to objectively measure and compare capacity and performance in mobility. Possible application fields may be early detection or differential diagnosis in dementia and assessment of fall risk. Regarding the challenges of future health systems due to the demographic change delaying need of care or preventing falls in dementia can help decrease costs while increasing perceived quality of life for people concerned and their carers. Within this paper we present our theoretic concept and algorithm for computing self-selected gait velocity utilizing measurement from a laser range scanner. Results of an experiment show that the laser range scanner delivers precise measurement and in the future may be used for absolutely unobtrusive analysis of spatio-temporal parameters of gait even in demented people.

Modeling individual healthy behavior using home automation sensor data: Results from a field trial

A technical system for unobtrusive presence measurement and two novel models for describing user behavior in domestic environments are presented. Within the developed models user behavior is either described as the probability of being present at a certain location within an environment at a certain time on a day of the week or being present at a location for a certain number of times with a certain duration. The models are called timeslot-based and duration-based. Both models have been applied to presence information gathered by a technical system using home automation sensors. The system was installed into two flats of older people during a field trial for eight months. Results of the experiment show that the two models can be applied to describe individual user behavior. The influence of data structure and model quality on the detection of anomalies and the generation of alarms is discussed. On the long-term, the approach aims at detecting cutbacks in self-care ability and changes in health state by autonomously learning typical user behavior from presence information in a spatial model and by detecting untypical behavior, called anomalies, and generating alarms for caretakers. Such automatic assessment of self-care ability and health state is required in order to meet the increased challenges imposed to the decreasing number of care personal during the progress of the demographic change.

3DLC: A Comprehensive Model for Personal Health Records Supporting New Types of Medical Applications

Motivated by the demographic change, many new medical applications are installed in the users home environment. These applications make use of ambient sensors, enabling new forms of medical care. Personal Health Records (PHRs) are an instrument for the storage, presentation and communication of health related data provided by these applications. But there are still open issues regarding the cooperation between PHRs and the new applications. On the basis of two medical application scenarios, we developed a new model which defines the appropriate level of abstraction of data generated by medical applications to be stored inside the PHR. The model also determines which part of these data is relevant for the clinical decision making process, and how these data should be communicated to physicians. This paper describes the 3DLC model, which uses three dimensions (clinical decision, frequency and context dependence) to determine the type of the data. We further introduce a prototype PHR system that is able to fulfil the requirements of our scenarios.

A mobile robot for self-selected gait velocity assessments in assistive environments: a robotic driven approach to bring assistive technologies into established homes

This paper presents a novel idea on how mobile robots can be used to implement mobility assessments in home environments. The demographic change leads to an increasing demand of care, especially for elderly people. Falls are one major problem due to hospital stays, slow recovery time, and subsequent impairments. Assisting technologies from the field of Ambient Assisted Living could offer new diagnostic approaches and provide home assistance. Installing required technologies in a home environment is often difficult and costly. Here, mobile robots provide a new solution to bring sensors and actors into the home environment without any installation. Especially laser range scanners for robot navigation provide several possibilities to perform mobility assessments at home. In this paper results of a self-selected gait velocity assessment done with the aid of a laser range scanner are presented. The results show that it is possible to use a laser range scanner to compute the movement trajectory of a person and several parameters of gait. This offers new possibilities to transfer clinical assessment into the home environment. Mobility assessments in the domestic environment could be used for early and more objective detection of impairments and gait disorders.

Performing gait analysis within the timed up & go assessment test: comparison of aTUG to a marker-based tracking system

Results from a technical validation of the aTUG (ambient Timed Up & Go) system are presented. The approach’s gait analysis capabilities were compared to a gold standard: SIMI Motion, a marker-based motion tracking system. Seven people participated and computation of step length and step duration happened with a median error of 3 cm (IQR 3 cm) respectively 0.08 s (IQR 0.07 s). These results show that aTUG has a measurement precision which is sufficient for use in clinical gait analysis and enables the use of the device without a gold standard, i.e. in hospitals outside laboratories or in the homes of patients. aTUG is an approach and system that utilizes only ambient sensor technologies to support the execution of geriatric mobility assessment tests and to perform a gait analysis simultaneously. Such capabilities are strongly demanded in order to support physicians in executing the geriatric assessment tests frequently and objectively in professional and domestic environments. The latter may enable more early prevention and more sustainable rehabilitation.

Criteria for Quality and Safety while Performing Unobtrusive Domestic Mobility Assessments Using Mobile Service Robots

A new concept for safely performing and qualitatively evaluating assessments in domestic unsupervised environments, especially when utilizing mobile service robots, is presented. The presented approach is based on the idea that classical geriatric assessments, especially from the domain of mobility, may be divided in components which happen naturally throughout the day in domestic environments. Those components are measured separately and are recombined to com-plete assessment tests later on. In order for physicians to decide how reliable assessment results from the domestic do-main are, we define technical quality criteria for the components of the Timed Up&Go assessment test. The approach is evaluated within an experiment in a living lab utilizing sensors, especially a laser range scanner, equipped with a mobile robot. Results show that the presented approach may be used to separate sensor measurements promising good assess-ment results from those containing insufficient data. Additionally, using mobile robots to perform assessments in domestic environments holds the potential danger for the inhabitant to stumble over the robot. Therefore, the paper also evaluates the aspect of inhabitants’ safety during domestic assessments based on the experiment’s data. A novel approach to navigate safely using the previously presented approach of optimal observation lots (OOL) is presented.

Towards Pervasive Mobility Assessments in Clinical and Domestic Environments

This paper provides an overview of current research and open problems in sensor-based mobility analysis. It is focused on geriatric assessment tests and the idea to provide easier and more objective results by using sensor technologies. A lot of research has been done in the field of measuring personal movement/mobility by technical approaches but there are few developments to measure a complete geriatric assessment test. Such automated tests can very likely offer more accurate, reliable and objective results than currently used methods. Additionally, those tests may reduce costs in public health systems as well as set standards for comparability of the tests. New sensor technologies and initiatives for data standardization in health processes offer increased possibilities in system development. This paper will highlight some open problems that still exist to bring automated mobility assessment tests into pervasive clinical and domestic use.

Functional Assessment in Elderlies’ Homes: Early Results from a Field Trial

Early results from a field trial regarding the assessment of functional status relevant to self-care ability in domestic environments are presented. A previously developed technical system for unobtrusively recording location information using home automation data was installed in the homes of five participants aged 64–84 years over a period of partially more than nine month. The recordings are manually evaluated to check whether items of geriatric assessment tests relevant to self-care ability can be assessed using the sensor recordings. The evaluation is a preliminary step to develop an automatic assessment algorithm and to develop a model for mapping domestic assessment results to result scales of clinical assessment tests. The mapping is required since most clinical assessment tests are not suitable for execution in domestic environments and thus new approaches are required which do also account for the difference between performance and capacity in functional abilities as proposed within WHO’s ICF.

Working with a domestic assessment system to estimate the need of support and care of elderly and disabled persons: results from field studies

This article describes the results of field studies performed over a period between five months and 24 months. The objectives of these studies were to collect long-term real-life data to evaluate how these data can be mapped to items on standardized assessment tests and which presentation method is most suitable to inform caregivers about critical situations and changes in health or care needs. A Home-monitoring system which uses modern sensor technologies was developed for and used in these field studies. It was installed in living environments of seven people (three who were not in need of care, two in need of care, and two with mental disabilities). The data were generated by sensor data acquisition and questionnaire reporting. Four types of data analysis and representation were evaluated to support caregivers. Results show that sensor data can be used to determine information directly or indirectly, which can be mapped to relevant assessment items and presented with different degrees of granularity. It is also feasible to determine and present additional information of potential interest which cannot be directly mapped to any assessment item. Sensor data can also be displayed in a live view. This live data representation led to a decrease in the caregivers’ workload when assessed according to the German version of the Perceived Stress Questionnaire.

Enhancing Mobile Robots’ Navigation through Mobility Assessments in Domestic Environments

A new concept to enhance mobile robot navigation in domestic environments by the use of mobility assessment data is presented. The concept is part of our overall approach to enabling more precise and reliable mobility assessment by the use of a mobile monitoring platform i.e. a mobile service robot equipped with a laser range scanner. We are basing our new approach on our previous work on the application of the potential field method to mobility trend analysis and the precise measurements of human movement trajectories by a laser range scanner. The enhancements to the robot’s navigation enable more precise assessment results while ensuring to not hinder or endanger the human. While navigating the robot moves from one to another observation location and tries to avoid the user’s movement paths whenever possible. Additionally, it adapts its own driving speed to the human’s. We call these secure observation locations which provide better assessment results Optimal Observation Lots (OOL). The concept’s algorithm, which was only implemented partially yet, contributes to our ultimate goal to develop an ’‘off the shelf” robot that is placed in the user’s home and is able to find its own observation spots and movement paths without further pre-programmed knowledge of the environment.