Louis Kälble, Tereza Tykalova, David Zogala, Petr Dusek, Jan Rusz, Michal Novotny
{"title":"新生帕金森病眼睑运动的自动分析","authors":"Louis Kälble, Tereza Tykalova, David Zogala, Petr Dusek, Jan Rusz, Michal Novotny","doi":"10.1038/s41531-025-01021-z","DOIUrl":null,"url":null,"abstract":"<p>This study presents an automated, objective method for eyelid movement assessment in de-novo Parkinson’s disease(PD) using a one-dimensional camera setup during monologue. These measurements were related to Dopamine Transporter Single Photon Emission Tomography and clinical scores. State-of-the-art computer-vision technologies and deep-learning neural networks were utilized to measure fourteen eyelid movement markers describing blinking and eyelid kinematics. Video-recordings were collected from a total of 120 de-novo patients with PD and 55 healthy controls. Abnormal blinking was present in 38% of PD, indicated by a reduced blink rate (<i>p</i> < 0.001), an increased inter-blink interval (<i>p</i> < 0.001), and an increased rigidity of the palpebral aperture (<i>p</i> < 0.001). The classification experiment reached an area under the curve of 0.81 on a blinded test set. The blink rate correlated with the loss of nigral dopaminergic neurons (r = 0.35, <i>p</i> < 0.001). These findings suggest eyelid movement markers as strong reflections of striatal dopaminergic activity levels, underscoring the method’s potential as a reliable early PD biomarker.</p>","PeriodicalId":19706,"journal":{"name":"NPJ Parkinson's Disease","volume":"75 1","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automatic analysis of eyelid movement in de-novo Parkinson’s disease\",\"authors\":\"Louis Kälble, Tereza Tykalova, David Zogala, Petr Dusek, Jan Rusz, Michal Novotny\",\"doi\":\"10.1038/s41531-025-01021-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This study presents an automated, objective method for eyelid movement assessment in de-novo Parkinson’s disease(PD) using a one-dimensional camera setup during monologue. These measurements were related to Dopamine Transporter Single Photon Emission Tomography and clinical scores. State-of-the-art computer-vision technologies and deep-learning neural networks were utilized to measure fourteen eyelid movement markers describing blinking and eyelid kinematics. Video-recordings were collected from a total of 120 de-novo patients with PD and 55 healthy controls. Abnormal blinking was present in 38% of PD, indicated by a reduced blink rate (<i>p</i> < 0.001), an increased inter-blink interval (<i>p</i> < 0.001), and an increased rigidity of the palpebral aperture (<i>p</i> < 0.001). The classification experiment reached an area under the curve of 0.81 on a blinded test set. The blink rate correlated with the loss of nigral dopaminergic neurons (r = 0.35, <i>p</i> < 0.001). These findings suggest eyelid movement markers as strong reflections of striatal dopaminergic activity levels, underscoring the method’s potential as a reliable early PD biomarker.</p>\",\"PeriodicalId\":19706,\"journal\":{\"name\":\"NPJ Parkinson's Disease\",\"volume\":\"75 1\",\"pages\":\"\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NPJ Parkinson's Disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1038/s41531-025-01021-z\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Parkinson's Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41531-025-01021-z","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Automatic analysis of eyelid movement in de-novo Parkinson’s disease
This study presents an automated, objective method for eyelid movement assessment in de-novo Parkinson’s disease(PD) using a one-dimensional camera setup during monologue. These measurements were related to Dopamine Transporter Single Photon Emission Tomography and clinical scores. State-of-the-art computer-vision technologies and deep-learning neural networks were utilized to measure fourteen eyelid movement markers describing blinking and eyelid kinematics. Video-recordings were collected from a total of 120 de-novo patients with PD and 55 healthy controls. Abnormal blinking was present in 38% of PD, indicated by a reduced blink rate (p < 0.001), an increased inter-blink interval (p < 0.001), and an increased rigidity of the palpebral aperture (p < 0.001). The classification experiment reached an area under the curve of 0.81 on a blinded test set. The blink rate correlated with the loss of nigral dopaminergic neurons (r = 0.35, p < 0.001). These findings suggest eyelid movement markers as strong reflections of striatal dopaminergic activity levels, underscoring the method’s potential as a reliable early PD biomarker.
期刊介绍:
npj Parkinson's Disease is a comprehensive open access journal that covers a wide range of research areas related to Parkinson's disease. It publishes original studies in basic science, translational research, and clinical investigations. The journal is dedicated to advancing our understanding of Parkinson's disease by exploring various aspects such as anatomy, etiology, genetics, cellular and molecular physiology, neurophysiology, epidemiology, and therapeutic development. By providing free and immediate access to the scientific and Parkinson's disease community, npj Parkinson's Disease promotes collaboration and knowledge sharing among researchers and healthcare professionals.