Functional near-infrared spectroscopy (fNIRS) is an optical non-invasive neuroimaging technique that allows participants to move relatively freely. However, head movements frequently cause optode movements relative to the head, leading to motion artifacts (MA) in the measured signal. Here, we propose an improved algorithmic approach for MA correction that combines wavelet and correlation-based signal improvement (WCBSI). We compare its MA correction accuracy to multiple established correction approaches (spline interpolation, spline-Savitzky–Golay filter, principal component analysis, targeted principal component analysis, robust locally weighted regression smoothing filter, wavelet filter, and correlation-based signal improvement) on real data. Therefore, we measured brain activity in 20 participants performing a hand-tapping task and simultaneously moving their head to produce MAs at different levels of severity. In order to obtain a “ground truth” brain activation, we added a condition in which only the tapping task was performed. We compared the MA correction performance among the algorithms on four predefined metrics (R, RMSE, MAPE, and ΔAUC) and ranked the performances. The suggested WCBSI algorithm was the only one exceeding average performance (p < 0.001), and it had the highest probability to be the best ranked algorithm (78.8% probability). Together, our results indicate that among all algorithms tested, our suggested WCBSI approach performed consistently favorably across all measures.

Participant movement is a major source of artifacts in functional near-infrared spectroscopy (fNIRS) experiments. Mitigating the impact of motion artifacts (MAs) is crucial to estimate brain activity robustly. Here, we suggest and evaluate a novel application of the nonlinear Hammerstein–Wiener model to estimate and mitigate MAs in fNIRS signals from direct-movement recordings through IMU sensors mounted on the participant’s head (head-IMU) and the fNIRS probe (probe-IMU). To this end, we analyzed the hemodynamic responses of single-channel oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) signals from 17 participants who performed a hand tapping task with different levels of concurrent head movement. Additionally, the tapping task was performed without head movements to estimate the ground-truth brain activation. We compared the performance of our novel approach with the probe-IMU and head-IMU to eight established methods (PCA, tPCA, spline, spline Savitzky–Golay, wavelet, CBSI, RLOESS, and WCBSI) on four quality metrics: SNR, △AUC, RMSE, and R. Our proposed nonlinear Hammerstein–Wiener method achieved the best SNR increase (p < 0.001) among all methods. Visual inspection revealed that our approach mitigated MA contaminations that other techniques could not remove effectively. MA correction quality was comparable with head- and probe-IMUs.

Background: Flatfoot deformity is a common condition in children and teenagers that may increase the risk of knee, hip, and back pain. Most of the insoles suggested to treat flatfoot symptoms are not designed to adapt to foot temperature during walking, and they are either too soft to provide support or hard enough to be uncomfortable. Purpose: This study aims to develop an advanced solution to diagnose and treat flexible flatfoot (FFT) using infrared thermography measurements and a hybrid insole reinforced by nitinol (NiTiCu) smart-memory-alloy wires (SMAWs), this super-elastic alloy can return back to its pre-deformed shape when heated, which helps to reduce the local high-temperature points caused by the uneven pressure of FFT. This approach achieves a more uniform thermal distribution across the foot, which makes the hybrid insole more comfortable. Methods: The study involved 16 subjects, divided into two groups of eight flat-footed and eight normal. The procedure includes two parts, namely, designing a prototype insole with SMAW properties based on thermography measurement by using SolidWorks, and evaluating this design using Ansys. Second, a hybrid insole reinforced with SMAWs is customized for flatfoot subjects. The thermography measurement differences between the medial and lateral sides of the metatarsophalangeal line are compared for the normal and flatfoot groups before and after wearing the suggested design. Results: The results show that our approach safely diagnosed FFT and significantly improved the thermal distribution in FFT subjects by more than 80% after wearing the suggested design. A paired t-test reported significant (p-value > 0.001) thermal decreases in the high-temperature points after using the SMAW insole, which was closely approximated to the normal subjects. Conclusions: the SMAW-reinforced insole is comfortable and suitable for treating FFT deformity, and infrared thermography is an effective tool to evaluate FFT deformity.