Cornelia Schneider

Evaluating GPS sampling rates for pedestrian assistant systems

Abstract In recent years, assistant systems have come to widespread use and support people in various situations e.g. in getting from A to B. For quite a time also assistant systems with special attention to older people have been developed. For example, in case of cognitive impairments where autonomous living indoors as well as outdoors is affected, assistant systems can be valuable aids. First attempts for outdoor assistance with GPS-based location systems offering the possibility to define geo-fences for raising an alert if a known area is left have been made. The quality of these systems is largely dependent on the precision of localisation which among others is influenced by the sampling rate. This paper reports on an empirical study under real world conditions to determine a suitable GPS sampling rate for movement analysis of (cognitively impaired) pedestrians. The work considers GPS measurement and interpolation errors as well as track losses as a result of low sampling rates. For the study, GPS data for different environmental settings and movement scenarios for sampling rates of 1, 2, 3, 4, 5, 10, 15, 20 and 25 s has been collected. The impact of sampling rates on movement parameters like track length and speed has been empirically measured. Additionally, the influence of smoothing approaches on data quality and whether downsampling of data has the same effect as recording with corresponding lower sampling rate has been studied. Results show that across all tested scenarios a sampling rate of 3–5 s seems to be appropriate with respect to speed and track length. Additionally, it can be argued that smoothing improves data quality of highly sampled data (up to 4 s). With downsampling, outliers are less in comparison to data sampled at the corresponding sampling rate.

Sarkopenie vorbeugen durch Bewegung im betreuten Wohnen

Sarkopenie, ubersetzt die Fleischarmut (griech. sarka = Fleisch, penia = Mangel, Armut), meint den altersbedingten und normalen Verlust an Skelettmuskelmasse, sofern keine Erkrankung oder eine strenge Diat als Ursachen vorliegen. Bei einem uber der Alters- und Geschlechtsnorm liegenden Verlust der Muskelmasse kommt es jedoch zu einem deutlichen Verlust der Funktionskapazitat des Herzkreislauf- und Stoffwechselsystems, was sich im Alltag in einer Abnahme der Kraftfahigkeit und Reduzierung der Gehgeschwindigkeit ausern kann.

Selection and Assessment of Activity Trackers for Enthusiastic Seniors.

A large percentage of older people do not achieve the recommended levels of health related activities. The planned CARIMO system addresses this problem and offers services and applications which motivate older users to do exercises and thus, improve their health. As additional incentive, an activity tracker is planned to be integrated in the CARIMO system. The paper describes the three-step process we defined to select a suitable device. First, available activity trackers were analysed according to a predefined criteria catalogue. Best ranked trackers were evaluated with a respect to usability and technical requirements. The Samsung Gear Fit2 offered a high range of functionality and was best ranked according to the usability evaluation. So, we finally decided to integrate the Samsung Gear Fit2 in the CARIMO system.

A Framework for Evaluating Stay Detection Approaches

In recent years, sensors of mobile devices are increasingly used in the research field of Active and Assisted Living (AAL), in particular, for movement analysis. Questions, such as where users typically stay (and for how long), where they have been or where they will most likely be going to, are of utmost importance for implementing smart AAL services. Due to the plethora of application scenarios and varying requirements, the challenge is the identification of an appropriate stay detection approach. Thus, this paper presents a comprehensive framework covering the entire process from data acquisition, pre-processing, parameterization to evaluation so that it can be applied to evaluate various stay detection methods. Additionally, ground truth data as well as application field data are used within the framework. The framework has been validated with three different spatio-temporal clustering approaches (time-based/incremental clustering, extended density based clustering, and a mixed method approach). Using the framework with ground truth data and data from the AAL field, it can be concluded that the time-based/incremental clustering approach is most suitable for this type of AAL applications. Furthermore, using two different datasets has proven successful as it provides additional data for selecting the appropriate method. Finally, the way the framework is designed it might be applied to other domains such as transportation, mobility, or tourism by adapting the pre-selection criteria.