Elderly residents in independent living facilities are frail, typically vulnerable to decline, and often require some nursing care.
The use of technology such as nonwearable sensors to monitor their activity levels can provide earlier detection of changes like reduced activity in an elder’s apartment and alert providers to intervene earlier.
However, when given the opportunity to interpret data collected from these sensors, elder residents and family members, unlike providers, had difficulty interpreting clinical data and graphs.
They also experienced information overload and did not understand terminology, according to Gregory L. Alexander, PhD, and researchers from the Sinclair School of Nursing.
To detect motion, location, falls, and functional activity, a variety of passive infrared sensors were installed in the apartments of 34 residents of an independent living facility.
The sensors can track if the resident spends some time during the day in the kitchen and uses the stove, is frequently up and out of bed during the night using the bathroom, and, while in bed, experiences some periods of restlessness.
Once the data from the sensors were collected, the researchers used a data-sensor interface with the capability to illustrate sensor data in different formats such as histograms, line graphs, and pie charts.
Three scenarios using actual resident data were developed to present to four groups of users: elderly residents, their family members, registered nurses, and physicians.
The situations depicted in the scenarios involved hospitalization after an acute illness at home, a period when a resident was not feeling well and had decreased activity, and a restless resident moving back and forth at night between bed and a chair to get more comfortable.
Each of the participants, after being given training on the user interface, was given the three scenarios to complete by using the sensor data interface.
Although elderly residents and their families experienced some difficulties interpreting the data, all four groups found the interface useful for identifying activity levels of the residents.
The researchers concluded that the effectiveness of clinical information systems to provide useful information for clinical decision making is dependent on the usability of the system, data presentations, the match between the real world of end users and the system, and the satisfaction of users during interactions.
Read the full report in Alexander et al. (2011). Passive sensor technology interface to assess elder activity in independent living. Nursing Research, 60(5), 318-325.