腦中風是現在常見的疾病，而中風後的症狀經常會造成日常生活上的功能障礙，中風患者需積極的配合治療，才能有效的改善運動功能。目前病人所接受的復健治療，皆是以治療師徒手或配合輔具，來對患者進行一對一的治療訓練，需要相當多的人力及時間，且沒有客觀的評估及數據可以讓患者直接看見成效。因此，本研究目的研發居家式的復健輔助系統，提供患者能夠在家中自主進行復健訓練，減少醫療成本與往返醫院的不便。
本研究在硬體方面利用兩顆AI馬達帶動踏板，完成可提供踝關節進行拉伸及旋轉運動的機構。軟體方面，則利用Visual Studio 2010，編寫人機介面，系統提供兩種訓練模式：主動模式及被動模式。主動模式是由患者自行帶動踏板進行復健運動；被動模式則是在患者無法自行施力時，由馬達驅動帶領患者做復健，並配合肌電訊號感測器，量測作用中肌肉的肌電訊號，進行分析後做疲勞的判定，決定是否能繼續進行復健，預防二次傷害。

Nowadays, the cerebral vascular accident (CVA) is a common disease. People who suffer from this disease would be inconvenient in their daily life. Patients should receive treatments actively to improve movement ability effectively. However, it takes lots of time and manpower as the rehabilitation therapies are needed to be conducted one-on-one. Moreover, whether to treat with assistive devices or not is lacking objective evaluations and also lacking data to measure the effect of training. To solve the above-mentioned inadequate situations, the idea is to develop a housebound rehab system which can provide patients with autonomous training. Also, it reduces medical costs and inconvenience of traffic.
In the hardware design of the proposed rehab system, the integration of AI servos and footboards enables patients to stretch and rotate their ankle joints. Single-chip microcomputer is installed and implemented to convert analog signals to digital signals to show on the human-machine interface, which is programmed by Visual Studio. Both active and passive modes are set in the interface. In the active mode, the user steps up the footboards voluntarily, while the servos force the user to move accordingly. Moreover, electromyogram sensors measure the electromyogram of worked muscles which is analyzed to judge whether the muscles are fatigued or not. This could avoid the patient from relapsing of the disease.

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