{"id":2394,"date":"2022-04-28T15:49:13","date_gmt":"2022-04-28T19:49:13","guid":{"rendered":"https:\/\/jwonglab.com\/?page_id=2394"},"modified":"2022-05-03T22:53:50","modified_gmt":"2022-05-04T02:53:50","slug":"projects","status":"publish","type":"page","link":"https:\/\/jwonglab.com\/index.php\/projects\/","title":{"rendered":"Projects"},"content":{"rendered":"

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Precision deep brain stimulation for Parkinson\u2019s disease using AI <\/h2>\n\t <\/div>
This NIH funded project seeks to use deep learning AI techniques to decipher the imaging characteristics of the basal ganglia and correlate the volumetric data with clinical outcomes after DBS implantation. We will develop a predictive algorithm to identify the ideal DBS brain lead location based on user specified parameters.<\/div><\/div>
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Physiology, Imaging and Modeling of Essential Tremor <\/h2>\n\t <\/div>
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Deep brain stimulation (DBS) is a neuromodulatory therapy that is effective in a subset of well selected essential tremor (ET) patients. However, as many as 1\/5 of patients may initially improve, but then steadily worsen following the operation. The investigators developed a technique to study a variety of alternative stimulation methods without the use of an invasive repeat surgical intervention.<\/p>\n

The electrophysiological effects of non-conventional DBS differ from traditional DBS, however the physiological differences in the setting of human tremor remain largely unknown. This study plans to explore gaps in knowledge of neuromodulation and will collect and contribute essential information to the underlying mechanism of action of DBS. The hypothesis of this project centers around active biphasic stimulation providing a wider therapeutic window and a lower adverse event profile as compared to conventional DBS.<\/p>\n

ClinicalTrials.gov Identifier: NCT03811405<\/p>\n

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