Implementation of Magnetic Pulse Shape Stimulation Device Suitable for Cerebral Cortical Modification of Alzheimer"s Disease
Source abstract
Abstract
In general, when a brain neural stimulation device is used in brain disease or dementia, it does not reflect the pathophysiology, because regardless of the brain disease state, it stimulates only the motor cortex. In particular, it is necessary to be more cautious about the reactivity, plasticity, and connectivity of brain diseases and the dementia-related cortex. The brain neural stimulation device affects the distance and intensity of the stimulus coil from the initial brain axis of Alzheimer’s Disease (AD). The volume of cerebrospinal fluid increased by cortical hyperactivity and cerebral atrophy changes the characteristics of the brain tissue, and the current induced in the magnetic stimulation device has a negative effect. The stimulation site is biochemically and metabolically invaded by areas other than the motor cortex. Changes in the motor cortex cause problems later on. The present research confirms the cerebral state in real time by the EEG sensor that grasps the cerebral state, and the EMG sensor that can grasp the nerve conduction state, for the treatment suitable for the modified cortical form of the brain disease patient. The optimal stimulation therapy pulse and optimal pulse-forming device suitable for lesion-modified cerebral morphology were used. EEG and EMG are monitored in real time by cell phones, computers, and the web to implement the neural stimulation device of therapy pulse suitable for the modified cerebral cortex. In addition, stimulation coils can be replaced or added depending on the performance and capacity of the power source device, and control of the pulse shaping device, in order to implement a therapy pulse corresponding to the modified cortical morphology of the brain disease patient.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Neurological disorders and treatments · EEG and Brain-Computer Interfaces · Neuroscience and Neural Engineering
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References
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