Brain Computer Interface (BCI) Technology for Stroke Hand Rehabilitation "ARTS-BCI"
Completed
Phase N/A Results N/AUpdate History
28 Feb '18 |
The Summary of Purpose was updated. New
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.
Old
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.
The description was updated. New
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.
Old
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.
The gender criteria for eligibility was updated to "All." The eligibility criteria were updated. New
Inclusion Criteria:
1. Aged 21-80 years with first-ever clinical stroke, within 1-24 months onset.
2. Stroke type: ischemic or haemorhagic.
3. Fugl-Meyer motor score of the upper limb range from 10-50 or
4. Motor power MRC grade 3-5 in shoulder abductors and elbow flexors, and 0-3 in wrist
dorsiflexors and finger flexors
5. Ability to pay attention and maintain supported sitting for 1 hour continuously.
6. Able to give own consent and understand simple instructions
7. Fulfills BCI and Haptic knob physical screening trial.
Exclusion Criteria:
1. Functional status: severe aphasia or inattention, unstable medical conditions which
may affect participation (e.g. unresolved sepsis, postural hypotension, end stage
renal failure) or anticipated life expectancy of <1 year due to malignancy or
neurodegenerative disorder)
2. Hemispatial neglect (visual or sensory) or severe visual impairment despite visual
aids.
3. Epilepsy, severe depression or psychiatric disorder.
4. Recurrent stroke
5. Skull defect as this would affect physical fit of EEG cap interface.
6. Local arm factors: Severe spasticity Modified Ashworth scale >2 in any region, visual
analogue scale (VAS score) >4/10, fixed joint contracture , patients with poor skin
conditions, infections or eczema which may potentially be worsened by robotic shell
contact.
Old
Inclusion Criteria:
1. Aged 21-80 years with first-ever clinical stroke, within 1-24 months onset.
2. Stroke type: ischemic or haemorhagic.
3. Fugl-Meyer motor score of the upper limb range from 10-50 or
4. Motor power MRC grade 3-5 in shoulder abductors and elbow flexors, and 0-3 in wrist
dorsiflexors and finger flexors
5. Ability to pay attention and maintain supported sitting for 1 hour continuously.
6. Able to give own consent and understand simple instructions
7. Fulfills BCI and Haptic knob physical screening trial.
Exclusion Criteria:
1. Functional status: severe aphasia or inattention, unstable medical conditions which
may affect participation (e.g. unresolved sepsis, postural hypotension, end stage
renal failure) or anticipated life expectancy of <1 year due to malignancy or
neurodegenerative disorder)
2. Hemispatial neglect (visual or sensory) or severe visual impairment despite visual
aids.
3. Epilepsy, severe depression or psychiatric disorder.
4. Recurrent stroke
5. Skull defect as this would affect physical fit of EEG cap interface.
6. Local arm factors: Severe spasticity Modified Ashworth scale >2 in any region, visual
analogue scale (VAS score) >4/10, fixed joint contracture , patients with poor skin
conditions, infections or eczema which may potentially be worsened by robotic shell
contact.
|
13 Mar '14 |
A location was updated in Singapore. New The overall status was removed for Tan Tock Seng Hospital Rehabilitation Centre. |
11 May '13 |
The eligibility criteria were updated. New
Inclusion Criteria:
1. Aged 21-80 years with first-ever clinical stroke, within 1-24 months onset.
2. Stroke type: ischemic or haemorhagic.
3. Fugl-Meyer motor score of the upper limb range from 10-50 or
4. Motor power MRC grade 3-5 in shoulder abductors and elbow flexors, and 0-3 in wrist
dorsiflexors and finger flexors
5. Ability to pay attention and maintain supported sitting for 1 hour continuously.
6. Able to give own consent and understand simple instructions
7. Fulfills BCI and Haptic knob physical screening trial.
Exclusion Criteria:
1. Functional status: severe aphasia or inattention, unstable medical conditions which
may affect participation (e.g. unresolved sepsis, postural hypotension, end stage
renal failure) or anticipated life expectancy of <1 year due to malignancy or
neurodegenerative disorder)
2. Hemispatial neglect (visual or sensory) or severe visual impairment despite visual
aids.
3. Epilepsy, severe depression or psychiatric disorder.
4. Recurrent stroke
5. Skull defect as this would affect physical fit of EEG cap interface.
6. Local arm factors: Severe spasticity Modified Ashworth scale >2 in any region, visual
analogue scale (VAS score) >4/10, fixed joint contracture , patients with poor skin
conditions, infections or eczema which may potentially be worsened by robotic shell
contact.
Old
Inclusion Criteria:
1. Aged 21-80 years with first-ever clinical stroke, within 1-24 months onset.
2. Stroke type: ischemic or haemorrhagic.
3. Fugly-Meyer motor score of the upper limb range from 10-50 or
4. Motor power MRC grade 3-5 in shoulder abductors and elbow flexors, and 0-3 in wrist
dorsiflexors and finger flexors
5. Ability to pay attention and maintain supported sitting for 1 hour continuously.
6. Able to give own consent and understand simple instructions
7. Fulfills BCI and Haptic knob physical screening trial.
Exclusion Criteria:
1. Functional status: severe aphasia or inattention, unstable medical conditions which
may affect participation (e.g. unresolved sepsis, postural hypotension, end stage
renal failure) or anticipated life expectancy of <1 year due to malignancy or
neurodegenerative disorder)
2. Hemispatial neglect (visual or sensory) or severe visual impairment despite visual
aids.
3. Epilepsy, severe depression or psychiatric disorder.
4. Recurrent stroke
5. Skull defect as this would affect physical fit of EEG cap interface.
6. Local arm factors: Severe spasticity Modified Ashworth scale >2 in any region, visual
analogue scale (VAS score) >4/10, fixed joint contracture , patients with poor skin
conditions, infections or eczema which may potentially be worsened by robotic shell
contact.
|
26 Jun '12 |
A location was updated in Singapore. New The overall status was removed for Tan Tock Seng Hospital Rehabilitation Centre. |
View Trial Locations
Recruitment
- Enrollment: 21
- Gender: All
- Minimum Age: 21 Years
- Accepts Healthy Volunteers: No
- 1 location, 1 country
Principal Investigator
- Karen SG Chua, MD
Tan Tock Seng Hospital