Integrating motion sensing and wearable, modular high-density diffuse optical tomography: preliminary results
Integrating motion sensing and wearable, modular high-density diffuse optical tomography: preliminary results
复制标题
集成运动传感和可穿戴、模块化高密度漫射光学断层扫描：初步结果
DOI：
10.1117/12.2527197
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Brigadoi S
中科院分区：
文献类型：
--
作者：
Brigadoi S
下一代漫射光学成像系统将由可穿戴和无光纤设备组成，以利用漫射光学成像相对于其他功能性神经成像技术的优势，满足用户在现实环境中获取数据的需求。最近，伦敦大学学院的研究提出了一种新颖的模块化高密度漫射光学断层扫描（DOT）系统，该系统通过重建拇指到手指延伸任务的运动皮层上的激活图像进行了验证。然而，真正的问题是，这些无纤维系统是否可以在受试者进行真实活动时使用，也就是说，它们是否可以在参与者运动时提供可靠的信号。将运动传感器集成到模块化可穿戴电子设备中很简单。在这项研究中，我们在参与者进行不同的运动时获取DOT和运动传感器数据。在一次采集中，只采集加速度计数据，而在第二次采集中，采集了所有9轴数据（加速度计、陀螺仪和磁力计数据）。结果表明，来自运动传感器的加速度数据不足以在执行主动运动（例如步行）时检测运动伪影，因为全局运动掩盖了任何细微的运动伪影。相反，通过结合加速度计和陀螺仪数据，即使在行走过程中，也可以检测到运动伪影，也就是当全局运动存在时。然而，即使使用完整的数据配置，也不能检测到所有类型的运动伪影（例如，眉毛扬起）。需要进一步的研究来阐明这一重要的研究问题。
The next generation of diffuse optical imaging systems will consist of wearable and fiber-less devices, to exploit the advantages of diffuse optical imaging over other functional neuroimaging techniques and meet the needs of users to acquire data in real-world settings. Recently, research at UCL gave rise to a novel, modular high-density diffuse optical tomography (DOT) system that was validated by reconstructing activation images over the motor cortex of a thumb-to-finger extension task. The real question, however, is whether these fiber-less systems can be employed whilst the subject performs real-world activities, that is, whether they can provide reliable signals during participant motion. Integrating motion sensors into modular wearable electronics is straightforward. In this study we acquired DOT and motion sensor data whilst participants performed different activities involving motion. In one acquisition, only accelerometer data were acquired while in the second acquisition, all 9-axis of data (accelerometer, gyroscope and magnetometer data) were acquired. Results demonstrated that acceleration data from motion sensors is not enough to detect motion artifacts whilst performing active movement (eg, walking), since the global motion obscures any subtle motion artifact. Conversely, by combining accelerometer and gyroscope data it seems possible to detect motion artifacts even during walking, that is when a global motion is present. However, not all types of motion artifacts (eg, eyebrow raising) could be detected even with this full data configuration. Further studies are required to shed light on this important research question.