近年來，一個國家復健治療的好壞，決定了一個國家是否為先進國家。復健的目的是讓病患可以恢復，或是維持身體某一部份的功能。以往復健需要在醫院進行，由專業的物理治療師在一旁看護，確保病患的復健安全並有效。然而小型電子裝置的發展，使得病患現在可以借由穿著可穿戴式的感測器，在家中進行復健。由於大部份的穿戴式感測器需要借由radio把資料傳送回接收端，所以我們需要克服訊號的遮蔽的問題。以網路的角度來看，由穿戴式感測器所組成的無線人體區域網路(WBAN)，因為訊號遮蔽而變得斷斷續續，進而造成資料丟失。我們可以將這種WBAN當作一種延遲容忍網路(DTN)，之後便有很多中方法可以解決這個問題。
當我們考慮復健運動監控的特定一種應用時，我們可以找出更多DTN的解法。我們觀察到復健的其中一個特性，即做復健運動時，病患會不斷重複地做同樣一個動作。而這個重複的動作隱含了許多有用的資訊，包括兩個感測器相遇的時間，以及其中一個感測器如何能幫助另外一個感測器傳送訊息給接收端。在這篇論文中，我們利用這個特性，為感測器找到了一個有效的傳輸排程。我們分成兩個部分來解決這個問題。在第一個部分，我們收集感測器在病患做動作時的動態鄰居資料，並從這些資料當中找出重複的動作，再利用這個動作來安排感測器之間的溝通與代傳。在第二個部分，可穿戴感測器便依循第一部分做出的行程來執行傳輸。實驗結果顯示我們的系統依照預期的執行，在實際的復健運動中展現良好的性能。

Nowadays, physical therapy has become an indicator of the advancement of a country. Physical therapy helps patients to regain and maintain proper functioning of their bodies. Traditionally, physical therapy has to be performed in the hospitals, assisted and monitored by professional therapists to ensure the safety and effectiveness. With the development of microelectronics, home rehabilitation is now possible with wearable sensors worn on patients to monitor their rehabilitative exercises at home. As most these wearable devices communicate their data with the gateway (or sink) through radio, the blockage of radio signals by the human body is a difficult challenge. From the network perspective, the blockage results in intermittent connections of the wireless body area network (WBAN) formed by the wearable sensors, causing data losses during transmissions. Such a WBAN can be modeled as a delay-tolerant network (DTN), and its data loss problem may be solved using many existing solutions proposed in the literature.
On the other hand, when considering the specific application of rehabilitation exercise monitoring, more efficient DTN solutions may be developed. One key observation is that almost all rehabilitation exercises require repetitive movements. The repetitive body moving patterns provide valuable hints on when two sensor nodes will meet, and how one may help the other to relay data to the sink. In this thesis, we exploit this behavior for very efficient transmission scheduling of the wearable sensors. We solve the problem in two parts. First, we collect dynamic neighboring information of the wearable sensors during the exercise. From the collected information, repetitive neighboring patterns are identified, which are then used to schedule when two sensors should communicate to relay data. In the second part of our scheme, the wearable sensors just follow the transmission schedule to send and relay data. Experimental results show that our system operates correctly using the transmission schedule and it performs well in real rehabilitation exercises.

1 Introduction 1
2 System Design 4
2.1 System Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Information Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.3 Pattern Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.4 Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3 Experiments 11
3.1 Experiment Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.2 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4 Conclusions and Future Works 19

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