File
Lin JH1,2, Hu GJ1, Ran J1, Chen LY1, Zhang X1, Zhang YX3
1Yangzhi Affiliated Rehabilitation Hospital of Tongji University, Rehabilitation Therapy, Shanghai, China, 2University of Sydney, Faculty of Health Sciences, Sydney, Australia, 3University of Auckland, Department of Exercise Sciences, Auckland, New Zealand
Background: Walking disability is one of the major consequences following stroke. Sufficient evidence has shown that repeated task-specific walking training is crucial to restore safe functional walking ability. Locomat is a robotic exoskeleton providing guidance force and bodyweight support to facilitate intensive walking training for people with stroke. Although the Locomat has been reported to be effective in improving walking performance following stroke, the effects of varying levels of guidance force and bodyweight support on the muscle activity pattern remain unclear.
Purpose: To compare the effects of different combination of guidance force and bodyweight support on muscle activation patterns in people with stroke.
Methods: A cross-sectional study design was employed. Participants walked in the Locomat with different levels of guidance force (40% or 70%) and bodyweight support (30% or 50%). The walking conditions were randomly selected with a 3-minute break between trials. Participants then walked in a treadmill at the same speed (1.2 m/s). Surface electromyography (EMG) of tibialis anterior, vastus medialis oblique, vastus lateralis oblique, rectus femoris, medial gastrocnemius, biceps femoris and gluteus medius were recorded. The EMG data was processed by a 20Hz high-pass filter and rectified. A 4Hz low-pass filter was applied afterwards. Then the root-mean-square envelope of the EMG signal was calculated using a moving window (100ms). The amplitude of EMG envelope during Locomat walking was normalised with respect to the maximal amplitude during treadmill walking. The mean EMG amplitude of each condition was calculated. A series of two-way analysis of variance with repeated measures were performed to determine the effects of guidance force and bodyweight support on the level of muscle activity. The alpha level was set at 0.05.
Results: Fifteen people with chronic stroke participated in this study (female n=1; age 46.1 ± 11.1 yr). The increase of bodyweight support reduced the amplitude of muscle activity of vastus medialis oblique (p = 0.022), vastus lateralis oblique (p = 0.031) and gluteus medius (p = 0.009). Tibialis Anterior demonstrated higher activity level with 40% guidance force compared to 70% guidance force. Interaction effects between bodyweight support and guidance force demonstrated that when bodyweight support reduced, the reduction of guidance force increase the activity level of vastus lateralis oblique (p = 0.048) and biceps femoris (p = 0.049).
Conclusion(s): The results show that bodyweight support and guidance force provided by Locomat generally reduce the muscle activity during walking. It is also suggested that the effects on modulating muscle activity level depend on specific setting of the training parameters.
Implications: The findings of this study provide evidence of the effects of training settings and their combinations on the muscle activity. To optimize the training outcome, clinicians should take those effects into consideration when designing a walking training plan with Locomat for people with stroke.
Keywords: Surface electromyography, Stroke, Locomat
Funding acknowledgements: The present study was supported by Shanghai Disabled Persons' Federation (K2016029).
Purpose: To compare the effects of different combination of guidance force and bodyweight support on muscle activation patterns in people with stroke.
Methods: A cross-sectional study design was employed. Participants walked in the Locomat with different levels of guidance force (40% or 70%) and bodyweight support (30% or 50%). The walking conditions were randomly selected with a 3-minute break between trials. Participants then walked in a treadmill at the same speed (1.2 m/s). Surface electromyography (EMG) of tibialis anterior, vastus medialis oblique, vastus lateralis oblique, rectus femoris, medial gastrocnemius, biceps femoris and gluteus medius were recorded. The EMG data was processed by a 20Hz high-pass filter and rectified. A 4Hz low-pass filter was applied afterwards. Then the root-mean-square envelope of the EMG signal was calculated using a moving window (100ms). The amplitude of EMG envelope during Locomat walking was normalised with respect to the maximal amplitude during treadmill walking. The mean EMG amplitude of each condition was calculated. A series of two-way analysis of variance with repeated measures were performed to determine the effects of guidance force and bodyweight support on the level of muscle activity. The alpha level was set at 0.05.
Results: Fifteen people with chronic stroke participated in this study (female n=1; age 46.1 ± 11.1 yr). The increase of bodyweight support reduced the amplitude of muscle activity of vastus medialis oblique (p = 0.022), vastus lateralis oblique (p = 0.031) and gluteus medius (p = 0.009). Tibialis Anterior demonstrated higher activity level with 40% guidance force compared to 70% guidance force. Interaction effects between bodyweight support and guidance force demonstrated that when bodyweight support reduced, the reduction of guidance force increase the activity level of vastus lateralis oblique (p = 0.048) and biceps femoris (p = 0.049).
Conclusion(s): The results show that bodyweight support and guidance force provided by Locomat generally reduce the muscle activity during walking. It is also suggested that the effects on modulating muscle activity level depend on specific setting of the training parameters.
Implications: The findings of this study provide evidence of the effects of training settings and their combinations on the muscle activity. To optimize the training outcome, clinicians should take those effects into consideration when designing a walking training plan with Locomat for people with stroke.
Keywords: Surface electromyography, Stroke, Locomat
Funding acknowledgements: The present study was supported by Shanghai Disabled Persons' Federation (K2016029).
Topic: Neurology: stroke; Robotics & technology
Ethics approval required: Yes
Institution: Yangzhi Affiliated Rehabilitation Hospital of Tongji University
Ethics committee: The Research Ethics Committee
Ethics number: YZ-2016-020
All authors, affiliations and abstracts have been published as submitted.
