Sensor Measures of Symmetry Quantify Upper Limb Movement in the Natural Environment Across the Lifespan

Abstract

Knowledge of upper limb activity in the natural environment is critical for evaluating the effectiveness of rehabilitation services. Wearable sensors allow efficient collection of these data and have the potential to be less burdensome than self-report measures of activity. Sensors can capture many different variables of activity and daily performance, many of which could be useful in identifying deviation from typical movement behavior or measuring outcomes from rehabilitation interventions. Although it has potential, sensor measurement is just emerging, and there is a lack of consensus regarding which variables of daily performance are valid, sensitive, specific, and useful. We propose that symmetry of full-day upper limb movement is a key variable. We describe here that symmetry is valid, robustly observed within a narrow range across the lifespan in typical development, and shows evidence of being different in populations with neuromotor impairment. Key next steps include the determination of sensitivity, specificity, minimal detectable change, and minimal clinically important change/difference. This information is needed to determine whether an individual belongs to the typical or atypical group, whether change has occurred, and whether that change is beneficial.

Keywords: Rehabilitation; Upper extremity.

Figure 1.

Conceptual issues surrounding sensor-based measures. Pie chart showing that performance quantified by self-report often does not match performance quantified by wearable sensors (data from Waddell et al., 2018). The data indicate that 50% of the sample under-reported and 17% over-reported upper limb activity compared to the sensor values. Only 33% were considered accurate, with self-report and sensor values within 10% of each other.

Figure 2.

Examples of sensor variables with wide vs. narrow distributions. Symbols represent sample means, with error bars at ± 1 SD and arrows at the minimum and maximum values observed. 2A: Hours of use is a variable with a wide distribution in typical adult populations (open symbols, data from Bailey et al., 2013 and 2015^,) and a wide distribution in persons with stroke (closed symbols, data from Bailey et al., 2015). 2B: The use ratio, however, is a variable with a narrow distribution in typical adult and infant populations (open symbols, infant data from Trujillo-Priego et al., 2017). As is characteristic of infant data, the range from minimum to maximum is a bit wider than in adults. The wide distribution of use ratio values in the stroke population (closed symbols) includes people who have normal daily activity (the most mildly affected) and some who have almost no daily activity (the most severely affected).