JMIR Publications

ABSTRACT

Background:

On-body wearable sensors have been used to predict adverse outcomes such as hospitalizations or fall, thereby enabling clinicians to develop better intervention guidelines and personalized models of care to prevent harmful outcomes. In our previous work, we introduced a generic remote patient monitoring framework (Sensing At-Risk Population) that draws on the classification of human movements using a 3-axial accelerometer and the extraction of indoor localization using BLE beacons, in concert. Utilizing the same framework, the current work addresses the longitudinal analyses of a group of patients in a skilled nursing facility. We try to investigate if the metrics derived from a remote patient monitoring system comprised of physical activity and indoor localization sensors, and their association with therapist assessments, provide additional insight into the recovery process of rehabilitation patients.

Objective:

(a) To observe longitudinal changes of sensor-based physical activity and indoor localization features of skilled nursing patients receiving rehabilitation, (b) to investigate if the sensor-based longitudinal changes can complement patients changes captured by therapist assessments over the course of rehabilitation in the skilled nursing facility.

Methods:

From June 2016 to November 2017, patients were recruited after admission to a subacute rehabilitation center in Los Angeles. Longitudinal cohort study of skilled nursing facility patients were followed over the course of 21 days. At the time of discharge from the skilled nursing facility, the patients were either readmitted to the hospital for continued care or discharged to a community setting. Longitudinal study of the physical therapy, occupational therapy and sensor-based data assessments was performed. Generalized Linear Mixed Model was used to find associations between functional measures with sensor-based features. Occupational therapy (OT) and physical therapy (PT) assessments were performed at the time of admission and once a week during the skilled nursing facility admission.

Results:

Of 110 individuals in the analytic sample with mean (SD) age 79.4 (5.9), 79 were female and 31 male. The energy intensity of an individual while in the therapy area was positively associated with transfer activities (β=0.22;SE=0.08;p<.05). Sitting energy intensity showed positive association with transfer activities (β=0.16;SE=0.07;p<.05). Lying down energy intensity was negatively associated with hygiene activities (β=-0.27;SE=0.14;p<.05). The interaction of sitting energy intensity with time (β=-0.13;SE=.06;p<.05) was associated with toileting activities.

Conclusions:

This study demonstrates that a combination of indoor localization and physical activity tracking produces a series of features, a subset of which can provide crucial information to the storyline of daily and longitudinal activity patterns of skilled nursing patients receiving rehabilitation. The findings suggest that detecting physical activity changes within locations may offer some insight into better characterizing patients progress or decline.