隨著老年人口增加以及人們對健康的重視不斷上升，行動照護裝置的需求越來越重要。在本論文中設計出一款多功能的穿戴式生理感測裝置，此裝置可量測心電圖 (electrocardiography, ECG) 訊號、呼吸時的胸腔阻抗變化、穿戴者的運動軌跡、穿戴者體表的溫溼度以及環境中的溫溼度。透過微控制器整合訊號後再使用藍芽低功耗 (Bluetooth Low Energy, BLE) 將資料傳送至行動裝置的應用程式中監控。本系統中使用的行動裝置為iOS系統的裝置，如iPhone和iPad。
本系統中的穿戴式裝置提供了3種運作模式和心率版本，使用者可以根據不同的應用來選擇適合的模式來達到省電的效果並延長裝置的使用時間。而在心率版本中，此裝置關閉了所有不需要的執行緒並降低運作頻率來達到最低的功耗。電流消耗將會降至2.52 mA，總共節省了約79.55%的電流消耗，且裝置的使用時間將會延長到119.2小時。
除了心率版本外，我們也為系統設計了其他的低功號設計，像是資料量簡化和線程控制。在透過資料量簡化後，ECG訊號的解析度為12位元，取樣頻率為500赫茲，呼吸阻抗的解析度為12位元，取樣頻率為20赫茲，九軸訊號的解析度為16位元，取樣頻率為25赫茲，三軸訊號的解析度為12位元，取樣頻率為30赫茲，溫度和濕度的解析度為8位元，取樣頻率為0.2赫茲。在ECG-9axis模式下節省了75.6%的封包傳輸量，且節省了約22%的電流消耗。
我們使用多線程的方式來整合處理器、藍芽模組和所有裝置上的感測器。當此裝置在不同模式下運作時，我們可透過線程控制來阻止或激活特定的線程，透過此方法，我們降低了MSP432的工作量以及電流消耗量。此外，此裝置會使用
QRS波群偵測演算法來計算心率並且估測ECG訊號品質，當訊號品質不佳時，裝置會關閉ECG感測器以節省功耗，且iOS裝置上的監測App也會傳送訊息來 之使用者。
在未使用低功耗設計的情況下，平均消耗電流約為12.31毫安培，在一個300毫安時容量的電池作為電源供應之下，已經可以使用約24.37小時。使用低功耗設計後，在ECG-9axis模式下可使用約35.44小時，ECG-3axis模式下可使用約58.47小時。

With the older population grows dramatically and people pay more and more attention to their health, the requirement of mobile health care system increases gradually. In this thesis, we design a wearable sensing system. The wearable sensor in this system can measure the electrocardiography (ECG) signal, respiration signal, motion of users, body surface temperature, body surface humidity, environment temperature, and environment humidity. These signals are integrated by the microcontroller (MCU) and sent to mobile devices by Bluetooth Low Energy (BLE). Besides, mobile devices are iOS devices, such as iPhone and iPad.

The sensor in this system provides three operating modes and the heart rate version. According to different applications, we can select the most appropriate mode to save power consumption and extend the usage time of this sensor. In addition, when the sensor works in the heart rate version, it will terminate threads which are unnecessary and decrease the operating frequency to reach the lowest power consumption. The current consumption is reduced to 2.52 mA in heart rate version, which saves about 79.55\% of current consumption. In addition, the battery lifetime of the sensor in this version can extend to 119.2 hours.

Except for the heart rate version, we implement other low-power designs to the system, such as reducing data and thread control. After reducing data, the resolution of ECG signal is 12 bits, and the sampling rate is 500 Hz. The resolution of respiration signal is 12 bits, and the sampling rate is 20 Hz. The resolution of 9-axis signal is 16 bits, and the sampling rate is 25 Hz. The resolution of 3-axis signal is 12 bits, and the sampling rate is 30 Hz. The resolution of temperature signal and humidity signal is 8 bits, and the sampling rate is 0.2 Hz. Finally, it saves about 75.6\% packets rate when the device works in the ECG-9axis mode. Besides, after implementing the data reduction, the sensing device can save about 22\% of current consumption.

We integrates main processor, BLE module, and peripheral sensors by multithread. When the device works in different modes, we block or active specific thread by the thread control. By thread control, we decrease the workload of main processor and reduce the current consumption. Moreover, the sensor calculates the heart rate and estimates the quality of ECG signals by QRS complex detection algorithm. When the sensor detects bad quality ECG signals, the ECG sensor will be disabled to save the power consumption, and the monitoring App in the iOS device will send an alarm to notify users.

In terms of the current consumption of the sensor, the original average current consumption is 12.31 mA, and the battery lifetime is 24.37 hours with a 300 mAh battery. After the low power design, the battery lifetime of the sensor is 35.44 hours in the ECG-9axis mode. Besides, in the ECG-3axis mode, the battery lifetime of the sensor is 58.47 hours.

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