Are we ready for automated deep brain stimulation programming?

IF 3.1 3区医学 Q2 CLINICAL NEUROLOGY

Parkinsonism & related disorders Pub Date : 2025-02-21 DOI:10.1016/j.parkreldis.2025.107347

Eric R Cole, Svjetlana Miocinovic

{"title":"Are we ready for automated deep brain stimulation programming?","authors":"Eric R Cole, Svjetlana Miocinovic","doi":"10.1016/j.parkreldis.2025.107347","DOIUrl":null,"url":null,"abstract":"<p><p>Deep brain stimulation (DBS) requires individualized programming of stimulation parameters, a time-consuming process performed manually by clinicians with specialized training. This process limits DBS accessibility, delays treatment, and constrains the potential for next-generation technology to improve patient outcomes. This review describes technological advancements that could automate DBS programming, focusing on Parkinson's disease biomarkers that can provide objective outcome measurement and algorithms that can quickly and automatically identify optimal DBS settings. We first define key performance criteria for an automated programming system, including effectiveness, efficiency, and ease of use, and then describe and evaluate each component with respect to these criteria. We conclude that the state of current research provides a strong foundation for developing automated DBS programming. The primary remaining obstacle lies in identifying and deploying the best combination of available techniques that will overcome the high entry barrier needed for wide-scale clinical deployment and adoption.</p>","PeriodicalId":19970,"journal":{"name":"Parkinsonism & related disorders","volume":" ","pages":"107347"},"PeriodicalIF":3.1000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Parkinsonism & related disorders","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.parkreldis.2025.107347","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Deep brain stimulation (DBS) requires individualized programming of stimulation parameters, a time-consuming process performed manually by clinicians with specialized training. This process limits DBS accessibility, delays treatment, and constrains the potential for next-generation technology to improve patient outcomes. This review describes technological advancements that could automate DBS programming, focusing on Parkinson's disease biomarkers that can provide objective outcome measurement and algorithms that can quickly and automatically identify optimal DBS settings. We first define key performance criteria for an automated programming system, including effectiveness, efficiency, and ease of use, and then describe and evaluate each component with respect to these criteria. We conclude that the state of current research provides a strong foundation for developing automated DBS programming. The primary remaining obstacle lies in identifying and deploying the best combination of available techniques that will overcome the high entry barrier needed for wide-scale clinical deployment and adoption.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Parkinsonism & related disorders 医学-临床神经学

CiteScore

6.20

自引率

4.90%

发文量

292

审稿时长

39 days

期刊介绍： Parkinsonism & Related Disorders publishes the results of basic and clinical research contributing to the understanding, diagnosis and treatment of all neurodegenerative syndromes in which Parkinsonism, Essential Tremor or related movement disorders may be a feature. Regular features will include: Review Articles, Point of View articles, Full-length Articles, Short Communications, Case Reports and Letter to the Editor.