Ignite Creation Date:
2024-10-26 @ 3:42 PM
Last Modification Date:
2024-10-26 @ 3:42 PM
Study NCT ID:
NCT06642519
Status:
NOT_YET_RECRUITING
Last Update Posted:
None
First Post:
2024-10-11
Brief Title:
Brain-Machine Interface for Freezing of Gait
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Adaptive Cortical Neuromodulation Using a Brain-machine Interface to Treat Freezing of Gait in Parkinsons Disease
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-10
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Gait problems in Parkinsons disease PD especially freezing of gait FOG greatly affect quality of life While deep brain stimulation DBS is a highly effective treatment for many motor symptoms of PD it is less effective for or can even worsen gait issues The primary motor cortex M1 plays a crucial role in the network that controls gait particularly in initiating movement Changes in local field potentials LFPs from the subthalamic nucleus STN are associated with different aspects of gait However detecting abnormal brain activity related to FOG requires a method called electrocorticography ECoG which has revealed that during FOG there is increased beta-gamma phase amplitude coupling PAC in the M1
Brain-machine interfaces BMIs have shown promise in understanding motor functions by decoding brain activity It is believed that BMIs could provide both accurate indicators of FOG and targeted treatments for it in PD
Our objectives are to use a high-density ECoG-based BMI to both record and stimulate brain activity during real-world gait and FOG in PD patients who are undergoing standard DBS procedures Our goals are to improve our understanding of the brains role in FOG and normal gait in PD and to develop new treatments based on cortical stimulation
Aim 1 - Identify gait biomarkers brain activity from the M1SMA cortex during different phases of walking and during FOG episodes both with and without medication will be recorded Machine learning will be used to identify the brain patterns linked to FOG
Aim 2 - Use cortical stimulation to stop FOG Cortical stimulation and its effects on leg and trunk movements will be studied by measuring muscle activity movement and posture during different states such as resting standing walking and during FOG episodes The type of stimulation which is most effective at stopping FOG will be identified
Brain-machine interfaces BMIs have shown promise in understanding motor functions by decoding brain activity It is believed that BMIs could provide both accurate indicators of FOG and targeted treatments for it in PD
Our objectives are to use a high-density ECoG-based BMI to both record and stimulate brain activity during real-world gait and FOG in PD patients who are undergoing standard DBS procedures Our goals are to improve our understanding of the brains role in FOG and normal gait in PD and to develop new treatments based on cortical stimulation
Aim 1 - Identify gait biomarkers brain activity from the M1SMA cortex during different phases of walking and during FOG episodes both with and without medication will be recorded Machine learning will be used to identify the brain patterns linked to FOG
Aim 2 - Use cortical stimulation to stop FOG Cortical stimulation and its effects on leg and trunk movements will be studied by measuring muscle activity movement and posture during different states such as resting standing walking and during FOG episodes The type of stimulation which is most effective at stopping FOG will be identified
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None