血液透析過程伴隨體液移除、血液組成與循環狀態的持續變化，但臨床抽血及生命徵象多屬時點式紀錄，較難呈現治療期間的連續生理變化。本研究建立一套以非侵入式漫反射光譜為基礎的光學特徵分析流程，以6 Hz取樣頻率量測手指末梢500–750 nm連續光譜，經系統校正及人工類神經網路反算後取得吸收係數時間序列，並建立五項穩態光學指標及二十八項定態小波轉換動態時頻指標。分析資料包含成大醫院139位血液透析患者，另以風典診所79位患者進行外部場域檢查；統計方法包含Pearson相關、偽發現率校正、主成分分析（principal component analysis，PCA）及探索性K-means分群。結果顯示，540–580 nm平均吸收強度與血紅素及血球容積比呈正相關，兩項吸收比值時間序列的均方根值則與兩者呈負相關，顯示平均吸收背景與時間波動可提供互補的血液組成相關資訊。動態分析中，四類光學時間序列的D2相對能量均與心率呈負相關，且其中三類與收縮壓呈正相關；部分D4及D5相對能量則與心率呈正相關，反映不同血液動力背景下頻帶能量比例的重新配置。穩態PCA保留三個主成分並形成四種探索性光學型態，惟群間分離有限且其中一群樣本數較少；動態PCA保留五個主成分，形成兩種具有良好重複抽樣穩定性的時頻配置，但群間臨床參數差異未通過偽發現率校正。外部資料保留部分穩態血液組成關聯、比值型動態波動與血液組成關聯，以及D2相對能量與收縮壓的相同方向，但D2與心率的關聯未穩定重現。綜合而言，本研究建立由穩態吸收背景與動態時頻配置構成的雙層光學分析架構，可作為血液透析患者短時間連續光學觀察與臨床生理資料整合的探索性基礎。

This study developed a noninvasive diffuse reflectance spectroscopy framework to characterize short-term optical changes during hemodialysis. Fingertip spectra acquired at 6 Hz over 500–750 nm were calibrated and converted by artificial neural network-based inversion into absorption coefficient time series, from which five static and 28 stationary wavelet transform time-frequency indicators were derived. Data from 139 patients at National Cheng Kung University Hospital were analyzed, and 79 patients from Feng-Dian Clinic were used for cross-site assessment. The mean absorption coefficient over 540–580 nm was positively associated with hemoglobin and hematocrit, whereas the root mean square values of two absorption-ratio time series were negatively associated with both variables. D2 relative energy was negatively associated with heart rate and positively associated with systolic blood pressure, while selected D4/D5 relative energies were positively associated with heart rate. Principal component analysis identified four static optical patterns and two dynamic time-frequency configurations. Several association directions were preserved externally, although the D2–heart rate relationship was not consistently reproduced. Overall, this framework provides an exploratory basis for integrating static and dynamic optical information with physiological data in hemodialysis..

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