Using Sensor Graphs for Monitoring the Effect on the Performance of the OTAGO Exercise Program in Older Adults.

The OTAGO exercise program is effective in decreasing the risk for falls of older adults. This research investigated if there is an indication that the OTAGO exercise program has a positive effect on the capacity and as well as on the performance in mobility. We used the data of the 10-months observational OTAGO pilot study with 15 (m = 1, f = 14) (pre-)frail participants aged 84.60 y (SD: 5.57 y). Motion sensors were installed in the flats of the participants and used to monitor their activity as a surrogate variable for performance. We derived a weighted directed multigraph from the physical sensor network, subtracted the weights of one day from a baseline, and used the difference in percent to quantify the change in performance. Least squares was used to compute the overall progress of the intervention (n = 9) and the control group (n = 6). In accordance with previous studies, we found indication for a positive effect of the OTAGO program on the capacity in both groups. Moreover, we found indication that the OTAGO program reduces the decline in performance of older adults in daily living. However, it is too early to conclude causalities from our findings because the data was collected during a pilot study.

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.

A technical platform for environments for ageing--lessons learned from three field studies.

The Lower Saxony Research Network "Design of Environments for Ageing" (GAL) studied possible applications of assistive technology for enabling older adults to live longer and independent in their own home. As part of this work, a technical platform was developed as a common technical basis for all assistive systems in the project. This article presents an overview of the architecture and core functionality of the technical platform, which in the first generation was developed for use in a laboratory setting, and in a second generation was extended for use in the project's field studies, i.e. prototype installations in end-users homes. The field studies' primary objective was the evaluation of the assistive technologies, that were developed within the overall project. However, these studies also confirmed that the fundamental concept of the technical platform is valid, and the prototypes continuously worked 24 h a day for several months. However, there were some problems related to lack of infrastructure in the older adults' homes and human factors such as inadvertent placement of objects across sensors' field of view, acceptance problems due to aesthetical reasons or simply communication problems, which show that making complex technologies work for users with little technical experience is well possible, but requires a careful consideration of the complete service chain and related "soft factors".

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.

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.