Validity of wearable actimeter computation of total energy expenditure during walking in post-stroke individuals.

BACKGROUND: Recent studies reported that wearable sensor devices show low validity for assessing the amount of energy expenditure in individuals after stroke. OBJECTIVE: We aimed to evaluate the validity of energy expenditure calculation based on the product of energy cost and walked distance estimated by wearable devices in individuals after hemispheric stroke. METHODS: We recruited individuals with hemispheric stroke sequelae who were able to walk without human assistance. The participants wore a tri-axial accelerometer (Actigraph GT3x) and a pedometer (ONStep 400) on the unaffected hip in addition to a respiratory gas exchange analyzer (METAMAX 3B) during 6min of walking at their self-selected walking speed and mode. The energy expenditure was calculated from the product of energy cost measured by the METAMAX 3B and the distance estimated by wearable devices. It was compared to the energy expenditure measured by the METAMAX 3B and the energy expenditure values recorded by the devices according to the manufacturer's algorithms. The validity was investigated by Bland-Altman analysis (mean bias [MB], root mean square error [RMSE], limits of agreement [95%LoA]), and Pearson correlation analysis (r). RESULTS: We included 26 participants (mean [SD] age 64.6 [14.8] years). With the pedometer, the energy expenditure calculated from the product of energy cost and walked distance showed high accuracy and agreement with METAMAX 3B values (MB=-1.6kcal; RMSE=4.1kcal; 95%LoA=-9.9; 6.6kcal; r=0.87, P<0.01) but low accuracy and agreement with Actigraph GT3x values (MB=15.7kcal; RMSE=8.7kcal; 95%LoA=-1.3; 32.6kcal; r=0.44, P=0.02) because of poorer estimation of walked distance. With the pedometer, this new method of calculation strongly increased the validity parameter values for estimating energy expenditure as compared with the manufacturer's algorithm. CONCLUSIONS: This new method based on the energy cost and distance estimated by wearable devices provided better energy expenditure estimates for the pedometer than did the manufacturer's algorithm. The validity of this method depended on the accuracy of the sensor to measure the distance walked by an individual after stroke.

Impact of online visual feedback on motor acquisition and retention when learning to reach in a force field.

When subjects learn a novel motor task, several sources of feedback (proprioceptive, visual or auditory) contribute to the performance. Over the past few years, several studies have investigated the role of visual feedback in motor learning, yet evidence remains conflicting. The aim of this study was therefore to investigate the role of online visual feedback (VFb) on the acquisition and retention stages of motor learning associated with training in a reaching task. Thirty healthy subjects made ballistic reaching movements with their dominant arm toward two targets, on 2 consecutive days using a robotized exoskeleton (KINARM). They were randomly assigned to a group with (VFb) or without (NoVFb) VFb of index position during movement. On day 1, the task was performed before (baseline) and during the application of a velocity-dependent resistive force field (adaptation). To assess retention, participants repeated the task with the force field on day 2. Motor learning was characterized by: (1) the final endpoint error (movement accuracy) and (2) the initial angle (iANG) of deviation (motor planning). Even though both groups showed motor adaptation, the NoVFb-group exhibited slower learning and higher final endpoint error than the VFb-group. In some condition, subjects trained without visual feedback used more curved initial trajectories to anticipate for the perturbation. This observation suggests that learning to reach targets in a velocity-dependent resistive force field is possible even when feedback is limited. However, the absence of VFb leads to different strategies that were only apparent when reaching toward the most challenging target.