ABSTRACT
Life-space is a promising method for estimating older adults' functional status. However, traditional life-space measures are costly and time consuming because they often rely on active subject participation. This study assesses the feasibility of using the global positioning system (GPS) function of smart phones to generate life-space indicators. We first evaluated the location accuracy of smart phone collected GPS points versus those acquired by a commercial GPS unit. We then assessed the specificity of the smart phone processed life-space information against the traditional diary method. Our results suggested comparable location accuracy between the smart phone and the standard GPS unit in most outdoor situations. In addition, the smart phone method revealed more comprehensive life-space information than the diary method, which leads to higher and more consistent life-space scores. We conclude that the smart phone method is more reliable than traditional methods for measuring life-space. Further improvements will be required to develop a robust application of this method that is suitable for health-related practices.
ABSTRACT
OBJECTIVES: To describe a system that uses off-the-shelf sensor and telecommunication technologies to continuously measure individual lifespace and activity levels in a novel way. DESIGN: Proof of concept involving three field trials of 30, 30, and 21 days. SETTING: Omaha, Nebraska, metropolitan and surrounding rural region. PARTICIPANTS: Three participants (48-year-old man, 33-year-old woman, and 27-year-old male), none with any functional limitations. MEASUREMENTS: Cellular telephones were used to detect in-home position and in-community location and to measure physical activity. Within the home, cellular telephones and Bluetooth transmitters (beacons) were used to locate participants at room-level resolution. Outside the home, the same cellular telephones and global positioning system (GPS) technology were used to locate participants at a community-level resolution. Physical activity was simultaneously measured using the cellular telephone accelerometer. RESULTS: This approach had face validity to measure activity and lifespace. More importantly, this system could measure the spatial and temporal organization of these metrics. For example, an individual's lifespace was automatically calculated across multiple time intervals. Behavioral time budgets showing how people allocate time to specific regions within the home were also automatically generated. CONCLUSION: Mobile monitoring shows much promise as an easily deployed system to quantify activity and lifespace, important indicators of function, in community-dwelling adults.