Movement artefact removal from NIRS signal using multi-channel IMU data.
Movement artefact removal from NIRS signal using multi-channel IMU data.
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DOI：
10.1186/s12938-018-0554-9
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发表时间：
2018-09-10
影响因子：
3.9
通讯作者：
Bai O
中科院分区：
文献类型：
--
作者：
Siddiquee MR;Marquez JS;Atri R;Ramon R;Perry Mayrand R;Bai O
近红外光谱（NIRS）的非侵入性使其成为人体各部位血氧测量的广泛接受的方法。该方法的主要挑战之一在于成功去除检测到的信号中的运动伪影。在这方面，包含加速度计、陀螺仪和磁力计的多通道惯性测量单元（IMU）可以用于比仅使用加速度计更好地对运动伪影进行建模，因此，可以更准确地去除运动伪影。研制了一种可穿戴式双通道连续波近红外光谱系统，该系统采用了由加速度计、陀螺仪和磁力计组成的惯性测量单元（IMU）传感器，可沿着记录近红外光谱信号，同时利用IMU记录运动伪影相关信号。4名健康受试者自愿记录NIRS信号。在前两名受试者的记录过程中，通过敲击附近的光电二极管传感器，在其中一个NIRS通道中模拟运动伪影。利用运动伪影的IMU数据，通过自回归外生输入法估计出噪声信号中的伪影，并与噪声信号相减，去除近红外光谱信号中的伪影。信噪比（SNR）的改善被用来评估运动伪影去除过程的性能。比较了仅使用加速度计、加速度计和陀螺仪以及来自IMU传感器的加速度计、陀螺仪和磁力计数据的运动伪影估计和去除的性能，以估计NIRS阅读中的伪影。对于其余两个受试者，通过自然运动伪影影响记录NIRS信号，并使用仅加速度计、加速度计和陀螺仪以及来自IMU传感器的加速度计、陀螺仪和磁力计数据比较伪影去除的结果，以估计NIRS阅读中的伪影。定量和定性的结果表明，SNR的改善增加的IMU通道的数量在伪影估计中使用，和有大约5-11 dB的SNR增加时，使用九个通道的IMU数据，而不是只使用三个通道的加速度计数据。从自然运动中去除伪影还表明，陀螺仪和磁力计传感器与加速度计的组合提供了对运动伪影的更好的估计和去除，这通过在NIRS信号中发生运动伪影之前、期间和之后HbO 2和Hb水平的最小变化来揭示。通过使用来自集成IMU传感器的加速度计、陀螺仪和磁记录器信号，可以比仅使用加速度计信号更准确地估计和去除NIRS中的运动伪影。
The non-invasive nature of near-infrared spectroscopy (NIRS) makes it a widely accepted method for blood oxygenation measurement in various parts of the human body. One of the main challenges in this method lies in the successful removal of movement artefacts in the detected signal. In this respect, multi-channel inertia measurement unit (IMU) containing accelerometer, gyroscope and magnetometer can be used for better modelling of movement artefact than using accelerometer only, which as a result, movement artefact can be more accurately removed. A wearable two-channel continuous wave NIRS system, incorporating an IMU sensor which contain accelerometer, gyroscope and magnetometer in it, was developed to record NIRS signal along with the simultaneous recording of movement artefacts related signal using the IMU. Four healthy subjects volunteered in the recording of the NIRS signals. During the recording from the first two subject, movement artefacts were simulated in one of the NIRS channels by tapping the photodiode sensor nearby. The corresponding IMU data for the simulated movement artefacts were used to estimate the artefacts in the corrupted signal by autoregressive with exogenous input method and subtracted from the corrupted signal to remove the artefacts in the NIRS signal. Signal-to-noise ratio (SNR) improvement was used to evaluate the performance of the movement artefacts removal process. The performance of the movement artefacts estimation and removal were compared using accelerometer only, accelerometer and gyroscope, and accelerometer, gyroscope and magnetometer data from IMU sensor to estimate the artefact in NIRS reading. For the remaining two subjects the NIRS signal was recorded by natural movement artefacts impact and the results of artefacts removal was compared using accelerometer only, accelerometer and gyroscope, and accelerometer, gyroscope and magnetometer data from IMU sensor to estimate the artefact in NIRS reading. The quantitative and qualitative results revealed that the SNR improvement increases with the number of IMU channels used in the artefacts estimation, and there were approximately 5–11 dB increase in SNR when nine channel IMU data were used rather than using only three channel accelerometer data only. The artefact removal from natural movements also demonstrated that the combination of gyroscope and magnetometer sensors with accelerometer provided better estimation and removal of the movement artefacts, which was revealed by the minimal change of the HbO2 and Hb level before, during and after movement artefacts occurred in the NIRS signal. The movement artefacts in NIRS can be more accurately estimated and removed by using accelerometer, gyroscope and magnetograph signals from an integrated IMU sensor than using accelerometer signal only.
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影响因子：
5.4
作者：
Boser, BE;Howe, RT
通讯作者：
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影响因子：
24
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通讯作者：
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通讯作者：
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