Article

Robots designed for rehabilitation of the upper extremity after
stroke facilitate high rates of repetition during practice of movements and
record precise kinematic data, providing a method to investigate motor recovery
profiles over time. OBJECTIVE: To determine how motor recovery profiles during
robotic interventions provide insight into improving clinical gains. METHODS: A
convenience sample (n = 22), from a larger randomized control trial, was taken of
chronic stroke participants completing 12 sessions of arm therapy. One group
received 60 minutes of robotic therapy (Robot only) and the other group received
45 minutes on the robot plus 15 minutes of translation-to-task practice (Robot +
TTT). Movement time was assessed using the robot without powered assistance.
Analyses (ANOVA, random coefficient modeling [RCM] with
2-term exponential
function) were completed to investigate changes across the intervention, between
sessions, and within a session. RESULTS: Significant improvement (P < .05) in
movement time across the intervention (pre vs post) was similar between the
groups but there were group differences for changes between and within sessions
(P < .05). The 2-term exponential function revealed a fast and slow component of
learning that described performance across consecutive blocks. The RCM identified
individuals who were above or below the marginal model. CONCLUSIONS: The expanded
analyses indicated that changes across time can occur in different ways but
achieve similar goals and may be influenced by individual factors such as initial
movement time. These findings will guide decisions regarding treatment planning
based on rates of motor relearning during upper extremity stroke robotic
interventions.
CI - (c) The Author(s) 2015.

Langue : ANGLAIS