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 η²_p = 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.

The effects of speed of execution on upper-limb kinematics in activities of daily living with respect to age

In this study, 26 young, 16 older adults ≤ 66a, and 22 older adults ≥ 67a were examined in a set of neuropsychological tests and the kinematics in two different activities of daily living (ADL) were assessed. Half of the participants performed the ADL in a natural speed, the other half as fast as possible. The performance in the Trail Making Task B revealed an increased slope after 67 years of age. When executed in a natural speed, ADL kinematics were comparable. When executed as fast as possible, almost all kinematic parameters showed significant group and speed differences and revealed group × speed interactions. Models of multiple linear regression predicting ADL trial durations showed similar strategies in the young and older adults < 67a. Factors were the general movement speed, the travelled path lengths, and the simultaneous use of both hands. In the older adults ≥ 67a, factors were the general movement speed, the travelled path length, and the activity level (during the task execution). A principal component analysis supported these findings by revealing two underlying components: movement strategy and age-dependent decline in primarily executive functions, where the ADL trial duration had comparable loadings on both components. These results in association with the accelerated decline in executive functions found in the oldest group suggest that deterioration of ADL with age is particularly caused by specific age-dependent changes in cognitive capacities.

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.

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.

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.

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.

The association of upper limb sensorimotor capacity, everyday inpatient behavior, and the effects of neurorehabilitation in persons with multiple sclerosis and stroke: a mixed-design study

BACKGROUND

Quantifying and monitoring the sensorimotor state of persons with neurological disease by means of wearables in everyday life has been shown to be a promising approach. To date, the impact of physical activity volumes in fixed epoch approaches has been limiting the feasibility of kinematic analyses of everyday life upper limb use.

METHODS

Using acceleration and angular velocity signals from wrist-worn sensors, we collected data of healthy controls (n = 12) as well as persons with multiple sclerosis (n = 17) or stroke (n = 14) during everyday life during inpatient neurorehabilitation. An activity recognition algorithm was used to avoid physical activity volume dependencies that come with epoch-based approaches. Behavioral kinematics were compared between samples and associated with clinical test performance. Further, changes of sensorimotor capacity and behavioral kinematics during neurorehabilitation (n = 15) were analyzed.

RESULTS

Physical activity volume independence was achieved. Persons with neurological disease showed less activities and longer activity durations. Further, a PCA suggested three underlying components, namely: behavior, neurological state, and physical state. Components scores were lower (worse) for persons with neurological disease, except for behavior. However, component scores of persons with neurological disease showed great variability in all dimensions. Changes in sensorimotor capacity were partially associated with changes in behavioral kinematics, but effects of neurorehabilitation were mostly seen in outcomes associated with the physical state component.

CONCLUSIONS

Persons with neurological disease showed neurological impairments as well as declines in the physical condition, which can to some extent be seen in behavioral kinematics. Neurorehabilitation appeared to rather affect the physical than the neurological state. By the novel approach using an activity recognizer instead of fixed epochs, it was possible show traces of sensorimotor capacity, as assessed by clinical tests, in kinematics of everyday life behavior.