使用手臂動作規則於冷凍肩復健記錄及重播系統之研究

Study of Using Arm-Movement Rules to Implement Frozen Shoulder Rehabilitation Record and Replay System

本研究結合加速度感測器的運作原理與冷凍肩復健動作的特性，發展出各種手臂動作之規則，進而實作具有判斷冷凍肩復健動作的記錄及重播系統；藉由對加速度感測器晶片進行X、Y、Z三軸的各個方向做實驗測試，同時觀察及捕捉冷凍肩復健運動中的前舉、側舉、鐘擺運動等主要動作的特徵，發展並編列出能判斷各個手臂動作的規則，包括復健起始動作規則、手臂彎曲規則、前舉規則、側舉規則、鐘擺運動規則等。本研究以Visual Basic程式建構能判斷冷凍肩復健動作並做記錄的系統，並以Virtools將判斷後所記錄的結果以虛擬人物的方式來重播呈現；換句話說，復健者於復健時，系統判斷手臂動作並儲存成復健紀錄，進而可以提供給相關醫護人員，讓醫護人員可以追蹤復健者的復健行為及姿勢，有利於醫護人員給予復健者更多關於復健上的建議。本研究所研製系統在前舉與側舉之辨識率為100％，而鐘擺運動之辨識率為75％。

This study develops a variety of arm-movement rules based on the features of acceleration sensor and the characters of the frozen shoulder rehabilitation actions. Those rules about arm-movement include rehabilitation Start-action Rule, Arm-flexion Rule, Before-lift Rule, Side-lift Rule and Pendulum-movement Rule. The study also implements a system that can recognize the actions of the arm movements for the firozen shoulder rehabilitation; and then those recognized actions can be recorded and replayed by the system. This system is implemented by using Visual Basic program to determine the arm's movement, and can also display the arm's movement with the virtual actor in the Virtools environment. The study can also help rehabilitant observing his behavior on the virtual environment. In the other words, the information collected by this system can help medical stuff to trace the user's rehabilitation behavior and it will benefit for medical stuff to offer more suggestions to the rehabilitant. The results show that the recognizing rates of the Before-lift and Side-lift are 100%; and the highest recognizing rate of the Pendulum-movement is 75%.