Patients with stroke, tendon injury and cardiovascular disease commonly have the sequelae of hand dysfunction which seriously affects the patients’ ability in daily life. Previous studies have found that the function...Patients with stroke, tendon injury and cardiovascular disease commonly have the sequelae of hand dysfunction which seriously affects the patients’ ability in daily life. Previous studies have found that the function of finger-tapping movement accounts for 80% of the hand function, and the recovery of the motor ability of the finger-tapping can greatly improve the patients’ self-care ability. Therefore, a rehabilitation training device to restore the finger-tapping movement is designed. In the study, anthropometry was applied to measure the dynamic and static dimensions of human hands in the finger-tapping movement. Subjects were selected according to the selected size range, and an experimental platform was built. Sampling points were set at key positions of index fingers and thumbs, and characteristic points of coronal planes and sagittal planes were recorded at a frequency of 10 frames per second. MATLAB was used to optimize the fitting of the scatter plot, and the fitted spatial curve parameters were input into the modeling software to establish the joint motion trajectory model and assist the design of rehabilitation training devices. It is proved that the device is ergonomic, and can effectively achieve the finger-tapping movement rehabilitation training of patients.展开更多
Currently, Granger-Geweke causality models have been widely applied to investigate the dynamic direction relationships among brain regions. In a previous study, we have found that the right hand finger-tapping task ca...Currently, Granger-Geweke causality models have been widely applied to investigate the dynamic direction relationships among brain regions. In a previous study, we have found that the right hand finger-tapping task can produce relatively reliable brain response. As an extension of our previous study, we developed an algorithm based on the classical Granger- Geweke causality model to further investigate the effective connectivity of three brain regions (left primary motor cortex (M1), supplementary motor area (SMA) and right cerebellum) that showed the most robust brain activations. Our computational results not only confirm the strong linear feedback among SMA, M1 and right cerebellum, but also demonstrate that M1 is the hub of these three regions indicated by the anatomy research. Moreover, the model predicts the high intermediate node density existing in the area between SMA and M1, which will stimulate the imaging experimentalists to carry out new experiments to validate this postulation.展开更多
基金Fundamental Research Funds for the Central Universities,China (No. 18D110317)。
文摘Patients with stroke, tendon injury and cardiovascular disease commonly have the sequelae of hand dysfunction which seriously affects the patients’ ability in daily life. Previous studies have found that the function of finger-tapping movement accounts for 80% of the hand function, and the recovery of the motor ability of the finger-tapping can greatly improve the patients’ self-care ability. Therefore, a rehabilitation training device to restore the finger-tapping movement is designed. In the study, anthropometry was applied to measure the dynamic and static dimensions of human hands in the finger-tapping movement. Subjects were selected according to the selected size range, and an experimental platform was built. Sampling points were set at key positions of index fingers and thumbs, and characteristic points of coronal planes and sagittal planes were recorded at a frequency of 10 frames per second. MATLAB was used to optimize the fitting of the scatter plot, and the fitted spatial curve parameters were input into the modeling software to establish the joint motion trajectory model and assist the design of rehabilitation training devices. It is proved that the device is ergonomic, and can effectively achieve the finger-tapping movement rehabilitation training of patients.
文摘Currently, Granger-Geweke causality models have been widely applied to investigate the dynamic direction relationships among brain regions. In a previous study, we have found that the right hand finger-tapping task can produce relatively reliable brain response. As an extension of our previous study, we developed an algorithm based on the classical Granger- Geweke causality model to further investigate the effective connectivity of three brain regions (left primary motor cortex (M1), supplementary motor area (SMA) and right cerebellum) that showed the most robust brain activations. Our computational results not only confirm the strong linear feedback among SMA, M1 and right cerebellum, but also demonstrate that M1 is the hub of these three regions indicated by the anatomy research. Moreover, the model predicts the high intermediate node density existing in the area between SMA and M1, which will stimulate the imaging experimentalists to carry out new experiments to validate this postulation.