利用虛擬實境場景誘發之暈車生理現象探討

Abstract

本論文主要探討暈車所引發的生理現象以及其形成的原因。本研究當中使用環繞式虛擬實境場景以及動態六軸平台做為引發暈車的實驗設備，希望透過同時對受測者提供接近於現實生活中的視覺以及動態體感刺激來誘發暈車生理現象。有別於以往的研究只提供單一(視覺或體感)刺激，使用本論文所提出之誘發方式，將更能明確找出暈車在腦中的傳導機制。此外，利用腦電波訊號(EEG)的高時間解析度特性，本論文亦透過一個連續式的撥桿，讓受測者可以不受打擾的回報當時的暈眩程度。所擷取的暈詢程度指標則被使用於與腦波以及心電圖特徵訊號之間的關聯性探討。由心電圖的研究成果之中可以發現，在暈眩時所造成的心電變化，有可能是同時受到交感以及附交感神經所影響，而且這些HRV指標與暈眩程度之間的關聯度並非是線性的關係。在EEG的研究成果之中可以發現，透過獨立成分分析所分離出的部分腦區訊號變化與暈眩程度有很高的關聯度。最後更透過coherence分析方法，找出各腦區與暈眩指標在時間軸上的關聯性，從而找出暈車在腦波所產生的連續時間影響。

This study investigates subjects’ physiological responses related to motion-sickness using a virtual-reality-based driving simulator on a motion platform with six degrees of freedom, which provides both visual and vestibular stimulations to induce motion-sickness in a manner that is close to that in daily life. The degree of motion-sickness was simultaneously and continuously reported by the subjects using an onsite joystick, providing non-stop behavioral references to the recorded biomedical signals. This study assesses the temporal relationship between heart rate variability (HRV) and the level of motion sickness (MS). Compared to the baseline (low MS) session, the low-frequency (LF, 0.04–0.15Hz) and the ratio of low- to high- frequency (LF/HF) components of HRVs increased significantly, while the HF (0.15–0.4Hz) component decreased when the self-report MS level increased. This finding is consistent with a perception-driven autonomic response of the cardiovascular system. Moreover, adaptive neural fuzzy inference system (ANFIS) was used to assess and model the relation between the HRV indices and MS severity. The results of this study showed that a combination of LF and HF indices and their ratio was strongly correlated with changes of the subjective ratings of MS, suggesting that MS may affect the combination of the sympathovagal interactions. Subjects’ brain dynamics associated with motion sickness were measured using a 32-channel EEG system. The acquired EEG signals were parsed by independent component analysis (ICA) into maximally independent processes. The decomposition enables the brain dynamics that are induced by the motion of the platform and motion-sickness to be disassociated. Five MS-related brain processes with equivalent dipoles located in the left motor, the parietal, the right motor, the occipital and the occipital midline areas were consistently identified across the subjects. The parietal and motor components exhibited significant alpha power suppression in response to vestibular stimuli, while the occipital components exhibited MS-related power augmentation in mainly theta and delta bands; the occipital midline components exhibited a broadband power increase. Further, time series cross-correlation analysis was employed to evaluate relationships between the spectral changes associated with different brain processes and the degree of motion-sickness. According to our results, it is suggested both visual and vestibular stimulations should be used to induce motion-sickness in brain dynamic studies.