Hodono Shota, Jin Jin, Zimmermann Jan, Maillet Donald, Reutens David, Cloos Martijn A
Annu Int Conf IEEE Eng Med Biol Soc. 2023 Jul;2023:1-4. doi: 10.1109/EMBC40787.2023.10341187.
We present a custom-built MR-compatible data glove to capture hand motion during concurrent fMRI experiments at 7 Tesla. Thermal and phantom tests showed our data glove can be used safely and without degradation of image quality. Subject-specific Blood Oxygen Level Dependent (BOLD) signal models, for use in fMRI analysis, were constructed based on recorded kinematic measurements. Experiments revealed the relative fMRI BOLD signal contribution of flexing, extending, and sustained isotonic extension. The ability to evaluate subject performance in real-time and create subject-specific BOLD signal models enables a wide range of experimental paradigms with improved data quality.Clinical Relevance- Using an MR compatible dataglove, subject specific Blood Oxygen Signal Level Dependent (BOLD) signal models can be constructed to study how the brain implements fine motor control.
我们展示了一种定制的与磁共振成像(MR)兼容的数据手套,用于在7特斯拉的同步功能磁共振成像(fMRI)实验中捕捉手部运动。热测试和体模测试表明,我们的数据手套可以安全使用,且不会降低图像质量。基于记录的运动学测量数据,构建了用于fMRI分析的特定受试者血氧水平依赖(BOLD)信号模型。实验揭示了弯曲、伸展和持续等张伸展时fMRI BOLD信号的相对贡献。实时评估受试者表现并创建特定受试者BOLD信号模型的能力,使得能够采用各种实验范式,并提高数据质量。临床意义——使用与MR兼容的数据手套,可以构建特定受试者的血氧信号水平依赖(BOLD)信号模型,以研究大脑如何实现精细运动控制。