Sensor-Derived Physical Activity Parameters Can Predict Future Falls in People with Dementia

Abstract

Background: There is a need for simple clinical tools that can objectively assess the fall risk in people with dementia. Wearable sensors seem to have the potential for fall prediction; however, there has been limited work performed in this important area. Objective: To explore the validity of sensor-derived physical activity (PA) parameters for predicting future falls in people with dementia. To compare sensor-based fall risk assessment with conventional fall risk measures. Methods: This was a cohort study of people with confirmed dementia discharged from a geriatric rehabilitation ward. PA was quantified using 24-hour motion-sensor monitoring at the beginning of the study. PA parameters (percentage of walking, standing, sitting, and lying; duration of single walking, standing, and sitting bouts) were extracted using specific algorithms. Conventional assessment included performance-based tests (Timed Up and Go Test, Performance-Oriented Mobility Assessment, 5-chair stand) and questionnaires (cognition, ADL status, fear of falling, depression, previous faller). Outcome measures were fallers (at least one fall in the 3-month follow-up period) versus non-fallers. Results: 77 people were included in the study (age 81.8 ± 6.3; community-dwelling 88%, institutionalized 12%). Surprisingly, fallers and non-fallers did not differ on any conventional assessment (p = 0.069-0.991), except for ‘previous faller' (p = 0.006). Interestingly, several PA parameters discriminated between the groups. The ‘walking bout average duration', ‘longest walking bout duration' and ‘walking bout duration variability' were lower in fallers, compared to non-fallers (p = 0.008-0.027). The ‘standing bout average duration' was higher in fallers (p = 0.050). Two variables, ‘walking bout average duration' [odds ratio (OR) 0.79, p = 0.012] and ‘previous faller' (OR 4.44, p = 0.007) were identified as independent predictors for falls. The OR for a ‘walking bout average duration' <15 s for predicting fallers was 6.30 (p = 0.020). Combining ‘walking bout average duration' and ‘previous faller' improved fall prediction (OR 7.71, p < 0.001, sensitivity/specificity 72%/76%). Discussion: Results demonstrate that sensor-derived PA parameters are independent predictors of the fall risk and may have higher diagnostic accuracy in persons with dementia compared to conventional fall risk measures. Our findings highlight the potential of telemonitoring technology for estimating the fall risk. Results should be confirmed in a larger study and by measuring PA over a longer period of time.

Gait parameters and characteristics associated with increased risk of falls in people with dementia: a systematic review

“…See Appendix A1 published as supplementary material online attached to the electronic version of this paper at https://www.cambridge.org/core/journals/international-psychogeriatrics. Ten articles met the inclusion criteria (Camicioli and Licis, 2004;Eriksson et al, 2008;Allan et al, 2009;Pellfolk et al, 2009;, Taylor et al, 2012Schwenk et al, 2014;Gietzelt et al, 2014). Figure 1 shows a flow diagram of the article selection process.…”

Quantification of Daily Physical Activity and Sedentary Behavior of Claudicating Patients

“…These findings suggest that a failure of the neuromusculoskeletal system at any level may be responsible for the pattern of activity/inactivity seen in both PAD and dementia patient populations. 29,30 Future work should evaluate the type of activities in these short periods of walking in association with symptoms and muscle oxygenation and blood flow. This type of work can provide insight into the pathophysiologic mechanisms operating in PAD and claudication and the way they operate to produce the symptoms and limitations that are well known for our patients.…”

User-Oriented Evaluation of a Robotic Rollator That Provides Navigation Assistance in Frail Older Adults with and without Cognitive Impairment

“…The navigation system enabled CI participants to complete section 2 faster and with a substantially smaller number of stops, indicating that the directional audio cues provided by the navigation system at critical waypoints led to less interrupted and smoother walking routes in CI users on this section. As more interrupted walking patterns were reported to be associated with a higher risk of falling in CI people [41], the navigation assistance provided by an RR might contribute to increase safety during wayfinding of CI users in unknown environments. On section 2, positive effects of the MOBOT-provided navigation assistance were observed; however, not only in the CI group but also among the total sample that was MOBOT-assisted in navigation.…”