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|Title:||Interactive exoskeleton robotic knee system for lower limb rehabilitation||Authors:||Ockenfeld, Corinna Ursula||Advisors:||Zhang, Ming (BME)||Keywords:||Robotics.
Cerebrovascular disease -- Patients -- Rehabilitation.
|Issue Date:||2016||Publisher:||The Hong Kong Polytechnic University||Abstract:||Stroke is one of the leading causes for long-term disabilities worldwide. About 80% of stroke survivors experience a hemiparesis, causing weakness or the inability to move one side of the body. This can cause difficulties in performing tasks of the daily living such as walking (Dobkin, 1997). As a result, gait recovery is one of the major objectives in patients post-stroke. Besides conventional therapy approaches (e.g. Bobath, Brunnstrom method, Proprioceptive neuromuscular facilitation), task-specific training and robot assisted gait training have shown to be a promising field in restoring gait functions over the last few years (Wevers et al. 2009)(Mehrholz et al. 2013). Task-specific training, however, has been criticized for being a rather intense training approach, allowing only a selective population of stroke survivors with higher level of balance, motor control and sufficient walking ability to join the training (Wevers et al. 2009). Robot-assisted gait training on the other hand, is able to provide training to patients with moderate to severe level of disability. However, most of the existing devices fail to incorporate the voluntary intension of the user, adapt to individual walking speed or environmental changes during walking (e.g. stair climbing, slopes). This study aimed to: (1) develop an exoskeleton robotic system for lower limb rehabilitation after stroke, (2) develop a new control algorithm which is able to adapt to different walking environments, (3) conduct a pilot trial and evaluate the efficacy and feasibility of a task-specific lower limb training protocol using the exoskeleton knee robot. For those purposes, we proposed the development of an exoskeleton knee robot which is able to sense the user's individual walking speed, and adapt to environmental changes (e.g. sit-to-stand movement, stair ascent, stair descent, over-ground walking) to cater task-specific gait rehabilitation training. The device is one rotational Degree-of-Freedom (DOF) exoskeleton knee robot with a servo motor to assist the knee flexion during the swing phase and an electromagnetic knee lock to support the stance phase and sit-to-stand movement. The device is equipped with real-time motion and force sensors to sense the user's voluntary intention and synchronize the control of motor and knee lock system during ambulation.
A preliminary study with 3 healthy subjects and 1 stroke survivor was conducted to provide information about linear acceleration, joint angle, and walking speeds during different ambulation tasks (e.g. over-ground walking, stair ascent and stair descent). Afterwards, a pilot study with 10 stoke subjects (5 male, 5 female, aged 58.1±9.9 years old) was conducted. Each subject enrolled in this study received 20 sessions of 1-hour robotic gait training over a period of 4 weeks. All subjects wore the exoskeleton robot knee and were required to complete the following tasks: 2 sets of 10 minutes of continuous over-ground walking, 10 minutes of stair walking on a therapeutic staircase, and 2 sets of 20 times sit-to-stand movement. Gait recovery was assessed prior and post intervention by the following clinical outcome measures: Functional Ambulation Category (FAC), 6-minute walk test (6MWT) and 10-meter walk test (10MWT), Berg Balance Scale (BBS), Modified Ashworth Scale (MAS), and Fugl-Meyer Assessment for the lower extremity (FMA-LE). The results showed that patients participated in this study gained significant improvement in walking independency FAC (p≤0.025), reduced spasticity MAS (p≤0.037), and increased walking distance 6MWT (p≤0.005). Performance parameters during the training compared the mean walking distance, gait speed and number of climbed stairs in 10 minutes at baseline and last session. The results showed a statistically significant improvement in gait speed (p≤0.001), walking distance (p≤0.001) and number of walked stairs (p≤0.001) in 10 minutes. Subjects were able to maintain or further improve their lower limb functions in the 6-month follow-up, demonstrated by FAC (p≤0.034), MAS (p≤0.012), FMA-LE (p≤0.028), and 6MWT (p≤0.013). These results suggest the potential efficacy and feasibility of using the exoskeleton knee robot system in a clinical setting for lower limb rehabilitation post-stroke. However, a larger clinical trial is needed to verify the findings. In the future, we would like to explore the possibility of using the exoskeleton robot knee as a complement to task-specific training, rather than a stand-alone lower limb rehabilitation approach.
|Description:||PolyU Library Call No.: [THS] LG51 .H577P BME 2016 Ockenfeld
xx, 230 pages :color illustrations
|URI:||http://hdl.handle.net/10397/60367||Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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