在臨床中風復健領域，分析患者的運動情形對於復健成效的評估十分重要。為了準確捕捉受測者運動時的身體姿態變化，並進一步分析動作部位與關節旋轉情況，本研究開發出一套由九顆感測器組成的姿態量測系統，我們將其配戴與四肢及腰部上，來獲取受測者全身的運動狀態。每顆姿態感測器主要是由一顆九軸慣性感測元件（IMU）構成，用來量測空間中三維方向的角速度、加速度以及地磁強度等訊，且具備Wi-Fi供無線傳輸之用。本研究選擇四元數法來表現感測器的旋轉狀態，並利用二階擴展卡爾曼濾波器作為輸出角度校正補償的演算法。經計算後的身體姿態會以簡單三維圖形的形式在圖形化界面上顯示，其餘運動姿態資訊則會被儲存於電腦中供後續分析及應用。此外，我們希望透過經顱直流電刺激技術（tDCS）與復健動作的結合，來加強復健治療的效果。因此本研究亦開發出一套電刺激裝置，操作者可自由調節電流強度與即時監測電流變化，並且具備過流保護功能，避免電流過大對人體造成損傷。經實驗驗證，本系統確實能用於擷取受測者全身的姿態動作變化，將能夠幫助復健師評估中風患者的恢復情況。;Monitoring body kinematics and analyzing posture are important for rehabilitation evaluation in disabled patients. In this research, we want to analysis the motions and figure out which part did a stroke patient use to complete the action during rehabilitation. To achieve our goal, we place 9 inertial measurement units (IMU) on body to detect entire motions from shoulder to foot. Each IMU contains a 9-Axis Gyro-Accel-Magnet meter and a Wi-Fi module. We collect all three values from IMUs, calculates them using Quaternion algorithm and corrects by a two-step extended Kalman filter. Then we analyze those data on computer and can also reappear the motions in realtime. Also, we wants using the transcranial direct current stimulation (tDCS) technique to increase the effect of rehabilitation. In conclusion, we can detect, record and analyze the whole rehabilitation process using this IMUs system. It will help physiotherapists to evaluate the recovery situation of stroke patients.
