BACKGROUND: The effect of using robots to improve motor recovery has received increased attention, even though the most effective protocol remains a topic of study. OBJECTIVE: . The objective was to compare the training effects of treatments on the wrist joint of subjects with chronic stroke with aninteractive rehabilitation robot and a robot with continuous passive motion. METHODS: . This study was a single-blinded randomized controlled trial with a 3-month follow-up. Twenty-seven hemiplegic subjects with chronic stroke were randomly assigned to receive 20-session wrist training with a continuous electromyography (EMG)-driven robot (interactive group, n = 15) and a passive motion device (passive group, n = 12), completed within 7 consecutive weeks. Training effects were evaluated with clinical scores by pretraining and posttraining tests (Fugl-Meyer Assessment [FMA] and Modified Ashworth Score [MAS]) and with session-by-session EMG parameters (EMG activation level and co-contraction index). RESULTS: . Significant improvements in FMA scores (shoulder/elbow and wrist/hand) were found in the interactive group (P < .05). Significant decreases in the MAS were observed in the wrist and elbow joints for the interactive group and in the wrist joint for the passive group (P < .05). These MAS changes were associated with the decrease in EMG activation level of the flexor carpi radialis and the biceps brachii for the interactive group (P < .05). The muscle coordination on wrist and elbow joints was improved in the interactive groups in the EMG co-contraction indexes across the training sessions (P < .05). CONCLUSIONS: . The interactive treatment improved muscle coordination and reduced spasticity after the training for both the wrist and elbow joints, which persisted for 3 months. The passive mode training mainly reduced the spasticity in the wrist flexor.
RCT Entities:
BACKGROUND: The effect of using robots to improve motor recovery has received increased attention, even though the most effective protocol remains a topic of study. OBJECTIVE: . The objective was to compare the training effects of treatments on the wrist joint of subjects with chronic stroke with an interactive rehabilitation robot and a robot with continuous passive motion. METHODS: . This study was a single-blinded randomized controlled trial with a 3-month follow-up. Twenty-seven hemiplegic subjects with chronic stroke were randomly assigned to receive 20-session wrist training with a continuous electromyography (EMG)-driven robot (interactive group, n = 15) and a passive motion device (passive group, n = 12), completed within 7 consecutive weeks. Training effects were evaluated with clinical scores by pretraining and posttraining tests (Fugl-Meyer Assessment [FMA] and Modified Ashworth Score [MAS]) and with session-by-session EMG parameters (EMG activation level and co-contraction index). RESULTS: . Significant improvements in FMA scores (shoulder/elbow and wrist/hand) were found in the interactive group (P < .05). Significant decreases in the MAS were observed in the wrist and elbow joints for the interactive group and in the wrist joint for the passive group (P < .05). These MAS changes were associated with the decrease in EMG activation level of the flexor carpi radialis and the biceps brachii for the interactive group (P < .05). The muscle coordination on wrist and elbow joints was improved in the interactive groups in the EMG co-contraction indexes across the training sessions (P < .05). CONCLUSIONS: . The interactive treatment improved muscle coordination and reduced spasticity after the training for both the wrist and elbow joints, which persisted for 3 months. The passive mode training mainly reduced the spasticity in the wrist flexor.
Authors: Justin B Rowe; Vicky Chan; Morgan L Ingemanson; Steven C Cramer; Eric T Wolbrecht; David J Reinkensmeyer Journal: Neurorehabil Neural Repair Date: 2017-08 Impact factor: 3.919
Authors: Daniel K Zondervan; Renee Augsburger; Barbara Bodenhoefer; Nizan Friedman; David J Reinkensmeyer; Steven C Cramer Journal: Neurorehabil Neural Repair Date: 2014-10-01 Impact factor: 3.919
Authors: Sumner Norman; Mark Dennison; Eric Wolbrecht; Steven Cramer; Ramesh Srinivasan; David Reinkensmeyer Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2016-02-11 Impact factor: 3.802
Authors: Hossein Taheri; Justin B Rowe; David Gardner; Vicky Chan; David J Reinkensmeyer; Eric T Wolbrecht Journal: Conf Proc IEEE Eng Med Biol Soc Date: 2012