Florida International University, Miami, FL, 33174, USA.
Biomed Eng Online. 2018 Sep 10;17(1):120. doi: 10.1186/s12938-018-0554-9.
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 HbO 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.
近红外光谱（NIRS）的非侵入性使其成为人体各部位血氧测量广泛接受的方法。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）可用于更好地对运动伪影进行建模，优于仅使用加速度计，从而更准确地去除运动伪影。
开发了一种可穿戴的双通道连续波 NIRS 系统，该系统结合了包含加速度计、陀螺仪和磁力计的 IMU 传感器，用于记录 NIRS 信号以及使用 IMU 同时记录相关运动伪影信号。四名健康受试者自愿参与 NIRS 信号记录。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。使用自回归外生输入方法，根据对应的 IMU 数据来估计伪影，并从受污染的信号中减去以去除 NIRS 信号中的伪影。使用信噪比（SNR）改善来评估运动伪影去除过程的性能。使用仅加速度计、加速度计和陀螺仪以及 IMU 传感器的加速度计、陀螺仪和磁力计数据来估计 NIRS 读数中的伪影，比较了运动伪影估计和去除的性能。对于其余两名受试者，通过自然运动伪影的影响记录 NIRS 信号，并比较仅使用加速度计、加速度计和陀螺仪以及 IMU 传感器的加速度计、陀螺仪和磁力计数据来估计 NIRS 读数中的伪影的结果。
定量和定性结果表明，随着用于伪影估计的 IMU 通道数量的增加，SNR 改善增加，当使用九个通道的 IMU 数据而不是仅使用三个通道的加速度计数据时，SNR 增加约 5-11dB。从自然运动中去除伪影也表明，加速度计、陀螺仪和磁力计传感器的组合提供了更好的运动伪影估计和去除，这体现在 NIRS 信号中运动伪影发生之前、期间和之后 HbO 和 Hb 水平的最小变化。
与仅使用加速度计信号相比，使用集成的 IMU 传感器的加速度计、陀螺仪和磁力计信号可以更准确地估计和去除 NIRS 中的运动伪影。
