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Older citizens experience a large number of falls and hospitalizations per year throughout the world. These intervening health events (IHEs) such as falls/injuries, illnesses, hospitalizations, are strong precipitants of disability in older adults. They are episodic in nature, extremely difficult to study, and require continuous and long-term monitoring. Wearable technologies with remote capabilities are an ideal solution for capturing information before and after such events. This work presents the ROAMM campaign platform for harnessing sensor and interface capabilities on smart wearables to provide customizable, affordable, and versatile health monitoring that leads to practical remote-based interventions. The platform is flexible, efficient, and scalable for concurrently running multiple studies, each of which consists of patient-reported outcomes, ecological momentary assessments and mental health-related patient responses. Additionally, the system is able to capture and derive ecological, momentary assessments of pain with concurrent mobility tracking that allows life-space mobility ascertainment. The platform supports multiple watches, and we show implementations on both the Samsung Galaxy and Apple series of smartwatches.
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The Temporal Relationship Between Ecological Pain and Life-Space Mobility in Older Adults With Knee Osteoarthritis: A Smartwatch-Based Demonstration Study
Background Older adults who experience pain are more likely to reduce their community and life-space mobility (ie, the usual range of places in an environment in which a person engages). However, there is significant day-to-day variability in pain experiences that offer unique insights into the consequences on life-space mobility, which are not well understood. This variability is complex and cannot be captured with traditional recall-based pain surveys. As a solution, ecological momentary assessments record repeated pain experiences throughout the day in the natural environment. Objective The aim of this study was to examine the temporal association between ecological momentary assessments of pain and GPS metrics in older adults with symptomatic knee osteoarthritis by using a smartwatch platform called Real-time Online Assessment and Mobility Monitor. Methods Participants (n=19, mean 73.1 years, SD 4.8; female: 13/19, 68%; male: 6/19, 32%) wore a smartwatch for a mean period of 13.16 days (SD 2.94). Participants were prompted in their natural environment about their pain intensity (range 0-10) at random time windows in the morning, afternoon, and evening. GPS coordinates were collected at 15-minute intervals and aggregated each day into excursion, ellipsoid, clustering, and trip frequency features. Pain intensity ratings were averaged across time windows for each day. A random effects model was used to investigate the within and between-person effects. Results The daily mean pain intensities reported by participants ranged between 0 and 8 with 40% reporting intensities ≥2. The within-person associations between pain intensity and GPS features were more likely to be statistically significant than those observed between persons. Within-person pain intensity was significantly associated with excursion size, and others (excursion span, total distance, and ellipse major axis) showed a statistical trend (excursion span: P=.08; total distance: P=.07; ellipse major axis: P=.07). Each point increase in the mean pain intensity was associated with a 3.06 km decrease in excursion size, 2.89 km decrease in excursion span, 5.71 km decrease total distance travelled per day, 31.4 km2 decrease in ellipse area, 0.47 km decrease ellipse minor axis, and 3.64 km decrease in ellipse major axis. While not statistically significant, the point estimates for number of clusters (P=.73), frequency of trips (P=.81), and homestay (P=.15) were positively associated with pain intensity, and entropy (P=.99) was negatively associated with pain intensity. Conclusions In this demonstration study, higher intensity knee pain in older adults was associated with lower life-space mobility. Results demonstrate that a custom-designed smartwatch platform is effective at simultaneously collecting rich information about ecological pain and life-space mobility. Such smart tools are expected to be important for remote health interventions that harness the variability in pain symptoms while understanding their impact on life-space mobility.
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- Award ID(s):
- 1750192
- PAR ID:
- 10213931
- Date Published:
- Journal Name:
- JMIR mHealth and uHealth
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2291-5222
- Page Range / eLocation ID:
- e19609
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.2196/19609
