This research aims to integrate and develop a novel Brain-Computer Interface (BCI) controlled soft robotic glove, evaluate the ability of the glove in achieving common hand grasping postures and to assess the efficacy of the glove in assisting stroke patients with completing functional tasks. The BCI-controlled soft robotic glove utilizes patients' user intent to deliver specific electroencephalographic patterns that can trigger robot-assisted hand movement to the affected hand.
Hand motor impairment is very common after a stroke. These impairments include difficulty moving and coordinating the hands and fingers, which inhibits stroke patients from being able to perform daily functional tasks independently, resulting in a reduced quality of life. More than half of people with upper limb impairment after stroke will still have problems many months to years after their stroke. Therefore, improving hand function is a core element of rehabilitation. Many possible interventions have been developed; these may involve different exercises or training, specialist equipment or techniques, or they could take the form of a drug (pill or injection) given to help hand movement. There is limited evidence that suggests the following interventions may be effective: constraint-induced movement therapy, mental practice, mirror therapy,interventions for sensory impairment, virtual reality and a relatively high dose of repetitive task practice. Current hand rehabilitation robotic devices are typically driven by rigid linkages or joints, which subject the patient's fingers into a single plane of motion that will feel unnatural and uncomfortable. On top of that,these devices belong to the class of continuous passive motion (CPM) devices that only promote hand range-of-motion, but do not require the patient to play a semi-active role in performing the hand exercises. Furthermore, there is a huge demand for solutions assisting stroke patients with using the densely paralyzed hand to perform activities of daily living (ADL) in real life, which is not available at present. Most of the hand rehabilitation robotic devices available in the market cannot assist paralyzed hand to carry out ADL. To develop an assistive device to solve this unmet need, we decided to combine BCI technology with the wearable soft robotic glove, which enables actuation of paralyzed hand by motor imagery.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
18 sessions (3 times per week for a total of 6 weeks) of 1.5 hours each training (60 minutes of BCI Robot and 30 minutes of the standard hand therapy). Session 1-3. Peg game: Lateral movement of gears/cups Session 4-6. Moving cups onto a shelf: Elevation process for the arm, small cups to be used. Session 7-9. Carrying of basket: Heavier load to be used, patient to hold the basket by the handles at the side, not by its base. Session 10-12. Opening bottle + pouring into a cup: Training of ADL Session 13-15. Eating: Use of a modified spoon to train ADL Session 16-18. Box and blocks: Precise index finger and thumb control
18 sessions (3 times per week for a total of 6 weeks) of 1.5 hours each training (60 minutes of Passive Robot and 30 minutes of the standard hand therapy).The procedure will include the following: Session 1-18: Continuous passive motion
National University Hospital
Singapore, Singapore
Action Research Arm Test
It assesses a client's ability to handle objects differing in size, weight and shape and therefore can be considered to be an arm-specific measure of activity limitation
Time frame: 30 minutes
Fugl-Meyer Assessment
It is designed to assess motor functioning, balance, sensation and joint functioning.
Time frame: 20 minutes
Grip Strength Test
The purpose of this test is to measure the maximum isometric strength of the hand and forearm muscles.
Time frame: 5 minutes
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Purpose
DEVICE_FEASIBILITY
Masking
SINGLE
Enrollment
11