Brain Computer Interface (BCI) Technology for Stroke Hand Rehabilitation — ARTS-BCI  

Stroke Clinical Trial

Official title: ARTS-BCI: Advanced Brain Computer Interface (BCI) Technology for Wrist and Hand Rehabilitation After Stroke

Status Completed

Clinical Trial Summary

This study is carried out to find out if Brain Computer Interface (BCI) technology or BCI technology coupled with robotic technology using a Haptic Knob will benefit patients with arm paralysis after stroke. BCI uses EEG-based motor imagery to detect user's thinking abilities which control motor movement. Haptic Knob is a novel robotic device, which specifically trains the wrist and hand with intensive repetitions in a supported environment.

Clinical Trial Description

Physical therapy approaches are the de facto rehabilitation for stroke, which involve human therapists to assist stroke patients in recovering their motor ability. Modern rehabilitation technologies include robotics, functional electrical stimulation, transcranial magnetic stimulation and virtual reality. Robotic rehabilitation alleviates the labor-intensive aspects of physical rehabilitation by human therapists and could potentially improve the productivity of stroke rehabilitation. However, it is fundamentally based on movement repetition with visual feedback that helps stroke patients improve motor ability in their weak stroke-affected arms and legs. However, the robot is still able to move the weak part of the patient even if the patient is not attentive towards the training and thus the robotic training becomes a passive activity. In contrast, BCI-based robotic training works by ensuring active engagement by the hemiparetic patients in making a volitional movement. In addition, hemiplegic or locked-in stroke patients who do not have any motor power on the affected limbs are then able to engage and perform a volitional movement on these affected limbs.

BCI-based robotic rehabilitation fills this gap by detecting the motor intent of hemiplegic patients from the Electroencephalogram (EEG) signals to drive the robotic rehabilitation. This BCI-based robotic rehabilitation for stroke research project was jointly conducted by Tan Tock Seng Hospital (TTSH), National Neuroscience Institute (NNI) and Institute for Infocomm Research (I2R). Preliminary clinical trials performed at TTSH have shown that stroke patients can operate the BCI as effective as healthy subjects.

Specifically, this research project will address the following gaps in the area of rehabilitation for stroke:

1. Single-modal BCI - The current system employs a single modal non-invasive EEG-based BCI that detects motor intent using at least 2.5 seconds of EEG data. Hence, the research of an advanced multi-modal BCI such as synergizing near-infrared spectroscopy with EEG to yield a more responsive and effective BCI-based robotic rehabilitation system is proposed.

2. Standard therapy - The current system employs a standard therapy for all the stroke patients. However, physiotherapists and occupational therapists usually adopt a more individualized therapy for each stroke patients. Hence, research on an individualized therapy for each stroke patient according to his or her learning rate and neurological insult is proposed.

3. Only physiological rehabilitation - The current system only performs physiological rehabilitation of motor functions of stroke patients. Currently some validated scales for post-stroke depression such as Beck depression inventory, CES-D, Zung scale, State trait, HADS etc are difficult to administer in stroke patients who cannot participate with assessment due to impaired language or cognitive abilities. Hence an advanced BCI-based rehabilitation system that also detects the mental state of the stroke patient is proposed to cover both physiological and psychological rehabilitation.

4. Upper Limb rehabilitation - The current system which uses the clinically-proven MIT Manus robotic rehabilitation system, only performs upper limb rehabilitation for stroke patients in gross reach patterns. Human hand skills, in contrast, consist of more complex manipulation movement patterns which can be intervened by BCI-based robotic rehabilitation. Hence, an advanced BCI-based rehabilitation system that covers the hand function is proposed to cover the rehabilitation of the entire upper extremity. ;

Related Conditions & MeSH terms

• Stroke

• NCT number: NCT01287975
• Study type: Interventional
• Source: Tan Tock Seng Hospital
• Status: Completed
• Phase: N/A
• Start date: January 2011
• Completion date: June 2013