The reliability of side to side measurements of upper extremity activity levels in healthy subjects

Abstract

BackgroundIn both clinical and occupational settings, ambulatory sensors are becoming common for assessing all day measurements of arm motion. In order for the motion of a healthy, contralateral side to be used as a control for the involved side, the inherent side to side differences in arm usage must be minimal. The goal of the present study was to determine the reliability of side to side measurements of upper extremity activity levels in healthy subjects.MethodsThirty two subjects with no upper extremity pathologies were studied. Each subject wore a triaxial accelerometer on both arms for three and a half hours. Motion was assessed using parameters previously reported in the literature. Side to side differences were compared with the intraclass correlation coefficient, standard error of the mean, minimal detectable change scores and a projected sample size analysis.ResultsThe variables were ranked based on their percentage of minimal detectable change scores and sample sizes needed for paired t-tests. The order of these rankings was found to be identical and the top ranked parameters were activity counts per hour (MDC% = 9.5, n = 5), jerk time (MDC% = 15.8, n = 8) and percent time above 30 degrees (MDC% = 34.7, n = 9).ConclusionsIn general, the mean activity levels during daily activities were very similar between dominant and non-dominant arms. Specifically, activity counts per hour, jerk time, and percent time above 30 degrees were found to be the variables most likely to reveal significant difference or changes in both individuals and groups of subjects. The use of ambulatory measurements of upper extremity activity has very broad uses for occupational assessments, musculoskeletal injuries of the shoulder, elbow, wrist and hand as well as neurological pathologies.

Wrist activity monitor counts are correlated with dynamic but not static assessments of arm elevation exposure made with a triaxial accelerometer

“…The static parameters included the per cent time above a threshold elevation angle (308, 608 and 908; Svendsen et al 2004a) and the 50th, 90th and 99th percentiles of arm elevation (Hansson et al 2010). The dynamic parameters included the 50th, 90th and 99th percentiles of arm velocity (Svendsen et al 2004a), jerk time (Moller et al 2004) and a parameter similar to activity counts (Acuna et al 2010). Arm velocity was calculated by differentiating the elevation angle data set using the central difference method.…”

“…The subject was instructed to maintain a seated upright posture while holding a 1-kg weight. Direction was given to perform lateral trunk flexion, which resulted in a perpendicular orientation of the arm to the floor (Hansson et al 2006, Acuna et al 2010. During this alignment procedure, the triaxial accelerometer was connected to a computer so that the acceleration parameters could be observed in real time.…”

Usability Evaluation of a VibroTactile Feedback System in Stroke Subjects

“…Furthermore, our visual feedback needs longer data processes in order to “make sense” (arm usage); therefore, there is no need for direct visual feedback. Systems to train the upper extremity function with VT feedback in stroke patients have been previously developed (Kapur et al, 2009; Acuna et al, 2010; Bark et al, 2011; Hung et al, 2015). It is known that intensive training after stroke has a positive effect in clinical outcome, but the effect of VT feedback on arm function is unclear (Hung et al, 2015).…”

Us'em: The user-centered design of a device for motivating stroke patients to use their impaired arm-hand in daily life activities

“…The choice of feedback was based on results from studies by de Niet et al [31] and Acuna et al [32]. They showed that in normal persons, the activity levels that are measured with accelerometers are similar for the dominant and nondominant arm during daily life activities, while in stroke survivors the affected arm shows a significantly lower activity level [31].…”