Relationships between accelerometry and general compensatory movements of the upper limb after stroke

Abstract

Background Standardized assessments are used in rehabilitation clinics after stroke to measure restoration versus compensatory movements of the upper limb. Accelerometry is an emerging tool that can bridge the gap between in- and out-of-clinic assessments of the upper limb, but is limited in that it currently does not capture the quality of a person’s movement, an important concept to assess compensation versus restoration. The purpose of this analysis was to characterize how accelerometer variables may reflect upper limb compensatory movement patterns after stroke. Methods This study was a secondary analysis of an existing data set from a Phase II, single-blind, randomized, parallel dose–response trial (NCT0114369). Sources of data utilized were: (1) a compensatory movement score derived from video analysis of the Action Research Arm Test (ARAT), and (2) calculated accelerometer variables quantifying time, magnitude and variability of upper limb movement from the same time point during study participation for both in-clinic and out-of-clinic recording periods. Results Participants had chronic upper limb paresis of mild to moderate severity. Compensatory movement scores varied across the sample, with a mean of 73.7 ± 33.6 and range from 11.5 to 188. Moderate correlations were observed between the compensatory movement score and each accelerometer variable. Accelerometer variables measured out-of-clinic had stronger relationships with compensatory movements, compared with accelerometer variables in-clinic. Variables quantifying time, magnitude, and variability of upper limb movement out-of-clinic had relationships to the compensatory movement score. Conclusions Accelerometry is a tool that, while measuring movement quantity, can also reflect the use of general compensatory movement patterns of the upper limb in persons with chronic stroke. Individuals who move their limbs more in daily life with respect to time and variability tend to move with less movement compensations and more typical movement patterns. Likewise, individuals who move their paretic limbs less and their non-paretic limb more in daily life tend to move with more movement compensations at all joints in the paretic limb and less typical movement patterns.

Determinants of Different Aspects of Upper-Limb Activity after Stroke

“…However, full-body motion capture suits are less suitable for long-term measurements than bilateral wrist sensors. Therefore, sensor measures from wrist-worn accelerometry that do not only reflect quantity but also the quality of UL activity might be interesting to distinguish compensation versus restoration [ 15 ]. It was recently shown that persons who move the ULs more often and with more variability tend to move with fewer compensations [ 15 ].…”

“…Lastly, next to the contribution to and intensity of UL activity, there is the variability of UL movement, quantified by the variation ratio. Although this variable has been explored to a lower extent [ 4 ], it may be important in assessing daily life UL activity as it is correlated with movement quality [ 15 ]. It seems that individuals who move the UL more in daily life in terms of time and variability tend to move with fewer compensations [ 15 ].…”

Sensor-Based Categorization of Upper Limb Performance in Daily Life of Persons With and Without Neurological Upper Limb Deficits

“…The second most complex model included 9 UL performance variables, excluding the three variables calculated from the 30Hz data that are proposed to measure quality of UL activity (6, 24-26) (see Table 1). These variables were removed because they are more complex to calculate, have not been validated in clinical populations (22), and did not add relevant information to the analysis. For the 7 and 5 input variable models, the decision was made to maintain at least one performance variable from each of the other four aspects of UL performance (duration, magnitude, variability and symmetry) to capture the dimensionality of UL performance in daily life.…”

“…These variables collectively inform clinician scientists about the real-world activity performance. The numerous variables calculated from accelerometers measure different aspects of UL performance, such as: (1) duration (7,20); (2) magnitude (12,21,22); (3) variability (12,23); (4) symmetry or laterality (3,7,9); and (5) quality of movement (6,(24)(25)(26). Each UL performance variable conveys slightly different information about the collective nature of UL use, with a single variable providing only part of the picture (6).…”

Detection of Typical Compensatory Movements during Autonomously Performed Exercises Preventing Low Back Pain (LBP)

“…Moreover, they found that out-of-clinic measurements had stronger relationships with compensatory movements compared with in-clinic measurements. [ 25 ]…”