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.

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.

State and trait of finger tapping performance in multiple sclerosis.

Finger tapping tests have been shown feasible to assess motor performance in multiple sclerosis (MS) and were observed to be strongly associated with the estimated clinical severity of the disease. Therefore, tapping tests could be an adequate tool to assess disease status in MS. In this study we examined potential influencing factors on a maximum tapping task with the whole upper-limb for 10 s in 40 MS patients using linear mixed effects modelling. Patients were tested in three sessions with two trials per body-side per session over the course of 4-27 days of inpatient rehabilitation. Tested factors were the expanded disability scale (EDSS) score, laterality of MS, age, sex, hand dominance, time of day, session, trial (first or second), time between sessions, and the reported day form. A second model used these factors to examine the self-reported day form of patients. Linear mixed effects modelling indicated the tapping test to have a good inter-trial (proportional variance < 0.01) and inter-session reliability (non-significant; when controlling for time between sessions), an influence of hand-dominance (proportional variance 0.08), to be strongly associated with the EDSS (eta2 = 0.22, interaction with laterality of MS eta2 = 0.12) and to be not associated with the reported day form. The model explained 87% (p < 0.01) of variance in tapping performance. Lastly, we were able to observe a positive effect of neurologic inpatient rehabilitation on task performance obvious from a significant effect of the time between sessions (eta2 = 0.007; longer time spans between sessions were associated with higher increments in performance). Day form was only impacted by EDSS and the time of the day (p < 0.01, R2 = 0.57, eta2TIME = 0.017, eta2EDSS = 01.19). We conclude that the tapping test is a reliable and valid assessment tool for MS.