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基于時(shí)序卷積網(wǎng)絡(luò )的早期帕金森多模態(tài)檢測系統
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淮安市第二人民醫院信息科

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江蘇省高等學(xué)校基礎科學(xué)(自然科學(xué))研究重大項目(22KJA120002),徐州市科技計劃項目(KC21182),徐州市科技計劃項目(KC22224)


Early Parkinson"s Multimodal Detection System Based on Temporal Convolutional Networks
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    摘要:

    帕金森病是最常見(jiàn)的神經(jīng)退行性疾病之一,其臨床特征與其他神經(jīng)退行性疾病有重疊,且缺乏明確的病理機制,導致早期診斷檢測困難、誤診率高等問(wèn)題;為了研究有效的早期帕金森病檢測方法,深入探索帕金森病發(fā)展的時(shí)間特征規律,并提高早期帕金森病預測、分析和診斷決策的準確性,設計了一種基于時(shí)序卷積網(wǎng)絡(luò )的早期帕金森病多模態(tài)檢測系統,為及時(shí)發(fā)現早期帕金森病提供輔助診斷依據;該系統利用語(yǔ)音、步態(tài)和受試者自測數據,采用多元線(xiàn)性池化方法進(jìn)行多模態(tài)融合,結合時(shí)間卷積網(wǎng)絡(luò )和參數共享方式,以提高系統的檢測精度并降低過(guò)擬合風(fēng)險;實(shí)驗測試結果顯示,基于時(shí)序卷積網(wǎng)絡(luò )的早期帕金森病檢測系統的準確率達到96.22%,在多項評估指標上優(yōu)于傳統的帕金森檢測模型,展現出良好的早期帕金森聯(lián)合檢測效果。

    Abstract:

    Parkinson's disease is one of the most common neurodegenerative diseases, with clinical features overlapping with other neurodegenerative diseases and a lack of precise pathological mechanisms, leading to difficulties in early diagnosis and high misdiagnosis rates.; In order to study effective early detection methods for Parkinson's disease, deeply explore the temporal characteristics of Parkinson's disease development, and improve the accuracy of early Parkinson's disease prediction, analysis, and diagnostic decision-making, a multimodal detection system for early Parkinson's disease based on temporal convolutional networks was designed, providing an auxiliary diagnostic basis for the timely detection of early Parkinson's disease; The system utilizes speech, gait, and subject self-test data, adopts multiple linear pooling methods for multimodal fusion, and combines time convolutional networks and parameter sharing methods to improve the detection accuracy of the system and reduce overfitting risks; The results of ablation and comparative experiments show that the accuracy of the early Parkinson's disease detection system based on temporal convolutional networks reaches 96.22%, which is superior to traditional Parkinson's detection models in multiple evaluation indicators and demonstrates good early Parkinson's joint detection performance.

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周希武,楊明昭,胡殿雷.基于時(shí)序卷積網(wǎng)絡(luò )的早期帕金森多模態(tài)檢測系統計算機測量與控制[J].,2024,32(6):71-77.

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  • 收稿日期:2024-04-15
  • 最后修改日期:2024-05-07
  • 錄用日期:2024-05-08
  • 在線(xiàn)發(fā)布日期: 2024-06-18
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