Frailty Assessment in Daily Living (FRAIL) - Assessment of ADL Performance of Frail Elderly with IMUs

Schmidle, Stephanie; Gulde, Philipp; Jansen, Bart; Herdegen, Sophie; Hermsdörfer, Joachim

doi:10.1007/978-3-030-60703-6_12

Cited by 2 publications

(3 citation statements)

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“…Hand dominance, however, was only assessed by verbal information without using standardized questionnaires like the Edinburgh Handedness Inventory (EHI) [65]. Lastly, as mentioned elsewhere [46], data were collected unilaterally in two highly complex bimanual ADL tasks. Therefore, an assessment of upper limb bimanual performance was not possible.…”

Section: Discussionmentioning

confidence: 99%

“…The gravitation was subtracted as a constant (see Discussion), and the signal was smoothed using a 420 ms local regression algorithm [50]. The analysis was based on kinematic parameters using acceleration data identified in our previous study [46]. Two additional parameters (Acceleration per Second (APS) and 95 th Percentile of Acceleration Peaks (MAX95)) were included to have supplementary parameters for energy expenditure and an outlier-robust measure of speed/intensity.…”

Section: Sensor-based Kinematic Parametersmentioning

confidence: 99%

“…Accordingly, we tested two different ADL in a group of seniors without or with different degrees of frailty. A report which mainly assessed the technical aspects of the approach in a sub-group of the participant has recently been published elsewhere [46].…”

Section: Introductionmentioning

confidence: 99%

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Kinematic analysis of activities of daily living performance in frail elderly

et al. 2022

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Background Frailty is accompanied by limitations of activities of daily living (ADL) and frequently associated with reduced quality of life, institutionalization, and higher health care costs. Despite the importance of ADL performance for the consequence of frailty, movement analyses based on kinematic markers during the performance of complex upper extremity-based manual ADL tasks in frail elderly is still pending. The main objective of this study was to evaluate if ADL task performance of two different tasks in frail elderlies can be assessed by an activity measurement based on an acceleration sensor integrated into a smartwatch, and further to what degree kinematic parameters would be task independent. Methods ADL data was obtained from twenty-seven elderly participants (mean age 81.6 ± 7.0 years) who performed two ADL tasks. Acceleration data of the dominant hand was collected using a smartwatch. Participants were split up in three groups, F (frail, n = 6), P (pre-frail, n = 13) and R (robust, n = 8) according to a frailty screening. A variety of kinematic measures were calculated from the vector product reflecting activity, agility, smoothness, energy, and intensity. Results Measures of agility, smoothness, and intensity revealed significant differences between the groups (effect sizes combined over tasks η2p = 0.18 – 0.26). Smoothness was particularly affected by frailty in the tea making task, while activity, agility, a different smoothness parameter and two intensity measures were related to frailty in the gardening task. Four of nine parameters revealed good reliability over both tasks (r = 0.44 – 0.69). Multiple linear regression for the data combined across tasks showed that only the variability of the magnitude of acceleration peaks (agility) contributed to the prediction of the frailty score (R2 = 0.25). Conclusion The results demonstrate that ADL task performance can be assessed by smartwatch-based measures and further shows task-independent differences between the three levels of frailty. From the pattern of impaired and preserved performance parameters across the tested tasks, we concluded that in persons with frailty ADL performance was more impaired by physiological deficiencies, i.e., physical power and endurance, than by cognitive functioning or sensorimotor control.

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Section: Discussionmentioning

confidence: 99%

Section: Sensor-based Kinematic Parametersmentioning

confidence: 99%