Effect of wearable sensor dynamics on physical activity estimates: A comparison between SCI vs. healthy individuals.

Accuracy of physical activity estimates predicted by activity monitoring technologies may be affected by device location, analysis algorithms, type of technology (i.e. wearable/stickable) and population demographics (disability) being studied. Consequently, the main purpose of this investigation was to study such sensor dynamics (i.e. effect of device location, type and population demographics on energy expenditure estimates) of two commercial activity monitors. It was hypothesized that device location, population studied (disability), choice of proprietary algorithm and type of technology used will significantly impact the accuracy of the predicted physical activity metrics. 10 healthy controls and eight individuals with spinal cord injury (SCI) performed structured activities in a laboratory environment. All participants wore, (i) three ActiGraph-G3TX's one each on their wrist, waist & ankle, (ii) a stickable activity monitor (Metria-IH1) on their upper-arm and (3) a Cosmed-K4B2 metabolic unit, while performing sedentary (lying), low intensity (walk 50 steps at self-speed) and vigorous activity (a 6 minute walk test). To validate the hypothesis, the energy expenditures (EE) predicted by ActiGraph-GT3X and Metria-IH1 were benchmarked with estimated EE per Cosmed K4B2 metabolic unit. To verify the step count accuracy predicted by ActiGraph-GT3X's and Metria-IH1, the manually calculated step count during the low intensity activity were compared to estimates from both devices. Results suggest that Metria-IH1 out-performed ActiGraph-GT3X in estimating EE during sedentary activity in both groups. The device location and population demographics, significantly affected the accuracy of predicted estimates. In conclusion, selecting activity monitor locations, analysis algorithm and choice of technology plays based on the movement threshold of population being studied can pave a better way for reliable healthcare decisions and data analytics in population with SCI.

Variability of peak shoulder force during wheelchair propulsion in manual wheelchair users with and without shoulder pain.

BACKGROUND: Manual wheelchair users report a high prevalence of shoulder pain. Growing evidence shows that variability in forces applied to biological tissue is related to musculoskeletal pain. The purpose of this study was to examine the variability of forces acting on the shoulder during wheelchair propulsion as a function of shoulder pain. METHODS: Twenty-four manual wheelchair users (13 with pain, 11 without pain) participated in the investigation. Kinetic and kinematic data of wheelchair propulsion were recorded for 3 min maintaining a constant speed at three distinct propulsion speeds (fast speed of 1.1 m/s, a self-selected speed, and a slow speed of 0.7 m/s). Peak resultant shoulder forces in the push phase were calculated using inverse dynamics. Within individual variability was quantified as the coefficient of variation of cycle to cycle peak resultant forces. FINDINGS: There was no difference in mean peak shoulder resultant force between groups. The pain group had significantly smaller variability of peak resultant force than the no pain group (P<0.01, η²=0.18). INTERPRETATION: The observations raise the possibility that propulsion variability could be a novel marker of upper limb pain in manual wheelchair users.