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 and/or measuring outcomes from rehabilitation interventions. While it has potential, sensor measurement is just emerging and there is a lack of consensus on 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 or not change has occurred, and whether or not that change is beneficial.

Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field

“…While individuals with stroke represent a substantial portion of the world-wide physical rehabilitation population, there are many other clinical populations that could benefit from the ability to capture motor performance in daily life. Given the heterogeneity of physical rehabilitation populations, it is highly likely that different clinical populations will need different wearable-derived variables for clinical decision-making [ 99 ]. Important sensor variables developed for one population may not be clinically relevant for another population.…”

Actigraphic Measurement of the Upper Limbs for the Prediction of Ischemic Stroke Prognosis: An Observational Study

“…Other groups evaluated upper limb movement symmetry in stroke patients and found correlations between the symmetry and the motor impairment [ 19 , 20 ]. The concept of symmetry and asymmetry used in these studies is based on a function of uni-or triaxial accelerations [ 19 , 20 ], and the ratio between upper limb movement is based on the total time of activity over 24 h [ 21 ]. Moreover, these studies evaluated non-bedridden patients with both hemorrhagic and ischemic stroke, with certain selective clinical severity standards (patients with no upper limb movement were excluded), and with different time frames from the index event [ 19 , 20 ].…”

A step toward the future of seamless measurement with wearable sensors in pediatric populations with neuromuscular diseases

“…Use of wearable sensors to capture upper limb performance in healthy children is also emerging . Data from a recent cohort of 176 typically developing children and adolescents (0–17 years old) wearing accelerometers on both wrists for up to four periods of 24 hours each can serve as a referent sample from which we can start to compare pediatric patient populations .…”

“…At any age, a great deal of variability is present across the population, which fits with our common life experiences of ourselves and others. Despite the variability in measures of hours or magnitude, a clear consistency across the lifespan is that the right and left upper limbs are equally selected and active during daily life (ie, activity symmetry) . Ratio measures that reflect the symmetry of activity across the limbs will likely be the first variables from wearable sensors that could be deployed clinically to identify potential motor disorders, delays, and interventions …”

“…Wearable sensor methodology faces several important challenges going forward. First, outcome variables from sensors and algorithms must be be rigorously evaluated to ensure that the variables extracted are the most relevant measures for each patient population . Sensor variables that are clinically relevant for one population may not be clinically relevant for another.…”