Outside the Laboratory Assessment of Upper Limb Laterality in Patients With Stroke: A Cross-Sectional Study.

BACKGROUND: The rehabilitation of upper limb sensorimotor performance after stroke requires the assessment of daily use, the identification of key levels of impairment, and monitoring the course of recovery. It needs to be answered, how laboratory-based assessments and everyday behavior are connected, which dimension of metrics, that is, volume, intensity, or quality, is most sensitive to reduced function, and what sensor, that is, gyroscope or accelerometer, is best suited to gather such data. METHODS: Performance in laboratory-based sensorimotor tests, as well as smartwatch-derived kinematic data of everyday life relative upper limb activity, during 1 day of inpatient neurorehabilitation (Germany, 2022) of 50 patients with stroke, was cross-sectionally assessed and resulting laterality indices (performance ratios) between the limbs were analyzed using ANCOVAs and principal component analysis. RESULTS: Laboratory-based tests revealed the strongest laterality indices, followed by smartwatch-based (intensity>quality>volume) metrics. Angular velocity-based metrics revealed higher laterality indices than acceleration-based ones. Laterality indices were overall well associated; however, a principal component analysis suggested upper limb impairments to be unidimensional. CONCLUSIONS: Our findings suggest that the use of sensors can deliver valid information of stroke-related laterality. It appeared that commonly used metrics that estimate the volume of use (ie, energy expenditure) are not the most sensitive. Especially reached intensities could be well used for monitoring, because they are more dependent on the performance of the sensorimotor system and less on confounders like age. The unidimensionality of the upper limb laterality suggests that an impaired limb with reduced movement quality and the inability to reach higher intensities will be used less in everyday life, especially when it is the nondominant side.

The relationship between self-reported physical frailty and sensor-based physical activity measures in older adults - a multicentric cross-sectional study.

BACKGROUND: The decline in everyday life physical activity reflects and contributes to the frailty syndrome. While especially self-reported frailty assessments have the advantage of reaching large groups at low costs, little is known about the relationship between the self-report and objective measured daily physical activity behavior. The main objective was to evaluate whether and to what extent a self-reported assessment of frailty is associated with daily physical activity patterns. METHODS: Daily activity data were obtained from 88 elderly participants (mean 80.6 ± 9.1 years) over up to 21 days. Acceleration data were collected via smartwatch. According to the results of a self-report frailty questionnaire, participants were retrospectively split up into three groups, F (frail, n = 43), P (pre-frail, n = 33), and R (robust, n = 12). Gait- and activity-related measures were derived from the built-in step detector and acceleration sensor and comprised, i.a., standard deviation of 5-s-mean amplitude deviation (MADstd), median MAD (MADmedian), and the 95th percentile of cadence (STEP95). Parameters were fed into a PCA and component scores were used to derive behavioral clusters. RESULTS: The PCA suggested two components, one describing gait and one upper limb activity. Mainly gait related parameters showed meaningful associations with the self-reported frailty score (STEP95: R2 = 0.25), while measures of upper limb activity had lower coefficients (MADmedian: R2 = 0.07). Cluster analysis revealed two clusters with low and relatively high activity in both dimensions (cluster 2 and 3). Interestingly, a third cluster (cluster 1) was characterized by high activity and low extent of ambulation. Comparisons between the clusters showed significant differences between activity, gait, age, sex, number of chronic diseases, health status, and walking aid. Particularly, cluster 1 contained a higher number of female participants, whose self-reports tended towards a low health status, the frequent use of a walking aid, and a higher score related to frailty questions. CONCLUSIONS: The results demonstrate that subjective frailty assessments may be a simple first screening approach. However, especially older women using walking aids may classify themselves as frail despite still being active. Therefore, the results of self-reports may be particularly biased in older women.

Going beyond PA: Assessing sensorimotor capacity with wearables in multiple sclerosis-a cross-sectional study.

BACKGROUND: Wearable technologies are currently clinically used to assess energy expenditure in a variety of populations, e.g., persons with multiple sclerosis or frail elderly. To date, going beyond physical activity, deriving sensorimotor capacity instead of energy expenditure, is still lacking proof of feasibility. METHODS: In this study, we read out sensors (accelerometer and gyroscope) of smartwatches in a sample of 90 persons with multiple sclerosis over the course of one day of everyday life in an inpatient setting. We derived a variety of different kinematic parameters, in addition to lab-based tests of sensorimotor performance, to examine their interrelation by principal component, cluster, and regression analyses. RESULTS: These analyses revealed three components of behavior and sensorimotor capacity, namely clinical characteristics with an emphasis on gait, gait-related physical activity, and upper-limb related physical activity. Further, we were able to derive four clusters with different behavioral/capacity patterns in these dimensions. In a last step, regression analyses revealed that three selected smartwatch derived kinematic parameters were able to partially predict sensorimotor capacity, e.g., grip strength and upper-limb tapping. CONCLUSIONS: Our analyses revealed that physical activity can significantly differ between persons with comparable clinical characteristics and that assessments of physical activity solely relying on gait can be misleading. Further, we were able to extract parameters that partially go beyond physical activity, with the potential to be used to monitor the course of disease progression and rehabilitation, or to early identify persons at risk or a sub-clinical threshold of disease severity.

Kinematic analysis of activities of daily living performance in frail elderly.

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.

Influence of stance width on standing balance in healthy older adults.

Posturography is an objective way to systematically interpret postural control. Recent evidence suggests self-selected stance width when conducting posturography in healthy young participants, as it is easy to perform yet standardized. It is unclear, if this is similarly applicable to healthy older adults which can better serve as comparison group for persons with specific impairments, like Parkinson's disease, who might have problems with set foot distances. The aim of this study was to investigate the influence of different stance widths on a set of parameters in healthy older adults. Twenty-four healthy elderly (65.6 ± 5.0 years, BMI 26.2 ± 4.5 kg/m2) participated in the study. Posturographic measurement consisted of two tests (body sway, BS; limits of stability, LoS) each assessed in five stance widths on a force platform. A series of time domain and frequency domain parameters, such as BS and LoS range, sample entropy, mean velocity, and balance functional reserve were calculated. Anthropometric parameters and self-selected stance width (mean 17.7 ± 4.7 cm) showed positive correlation. One-way repeated measures MANOVA revealed significant differences between all parameters and foot positions. Except for sample entropy in A-P dimension, univariate analysis showed significant effects of stance widths on the parameters with stronger effects on M-L dimensions. Outcomes acquired in self-selected stance width provide comparable results to standardized stance widths 20 and 30 cm. The recommendation of self-selected stance width can be adopted to older healthy subjects. Furthermore, it reflects a natural stance and includes individual body composition.