禪定研究之受測者監控系統─人體位移動態分析

Abstract

本篇論文提出了一個利用標記的方法(marker-based method)來偵測身體的動作，藉由在受測者身體上容易產生動作的部位貼上明顯的標記點(marker)，並分析這些標記點在實驗進行中的移動軌跡，以代表受測者在實驗中身體各部位的動作情形。而此分析結果將可與腦電波訊號 (Electroencephalograph, EEG) 研究互相結合，由於腦電波訊號很容易受到身體動作的影響，所以本論文的分析結果將可以作為腦電波訊號分析研究的參考。 本論文同時探討身體動作與腦電波訊號之基準線飄移(baseline drift)情形的關聯，本論文將利用分頻AR模型(subband AR model)將腦電波訊號作解讀，並萃取出其中有基準線飄移的時段，與身體動作偵測的結果作比對，以探討受測者身體動作與腦電波基準線飄移兩者的相互關聯性。

This thesis proposes a marker-based method in order to detect the human body’s motion. We attach the clear markers to the subject’s body, and analyze the motion trajectories of these markers during the experiment. The analytical results can represent the motion of subject, and they will be combined with the electroencephalograph (EEG) research. It is because that the EEG signals are easily affected by the human body’s motion, the motion detection results of this thesis can provide a consultation for the EEG researches. This thesis also discusses the relation between the body’s motion and the baseline drift of the EEG signals. This thesis proposes the EEG interpretation based on subband features quantified by AR model, and then extracts the baseline drift durations. Finally, we combine the motion detection results and the baseline drift durations to confer the relation.