JMIR Publications

ABSTRACT

Background:

Since Global Positioning System (GPS) measurement is getting more precise and affordable, health research has a trend to measure mobility objectively using GPS sensors. Available systems, however, often lack data security and means of adaptation and rely on an internet connection.

Objective:

To overcome these issues, we aimed to develop and test an easy-to-use, easy-to-adapt, and offline working application by utilization of smartphone sensors (GPS, accelerometry) for the quantification of mobility parameters.

Methods:

An android app, a server backend, and a specialized analysis pipeline have been developed (development substudy). Parameters of mobility by the study team members were extracted from the recorded GPS data using existing and newly developed algorithms. Test measurements were performed with participants to complete a reliability test (accuracy substudy). Usability was examined by interviewing community-dwelling older adults after one week of device use, followed by an iterative app design process (usability substudy).

Results:

After development, the app had no runtime or build-time errors and worked under suboptimal conditions, such as narrow streets and rural areas. The developed algorithms reach high accuracy (97.4% correctness, F1-Score 0.975) in distinguishing dwelling periods from moving intervals. The usability was piloted with older adults and showed low barriers and easy implementation into daily routines.

Conclusions:

Based on accuracy analyses and users' experience with the proposed system for GPS assessments, the developed algorithm showed great potential for app-based estimation of mobility in diverse health research contexts, including mobility patterns of community-dwelling older adults living in rural areas.