為了提昇計步器裝置估計步數及步長之準確度，本論文開發一套可隨行走狀態估計步數及步長的裝置與方法。本裝置以CC2540單晶片為核心，三軸加速度計ADXL345為感測元件，擷取加速度訊號並經由藍牙4.0無線傳輸介面傳送資料到電腦端。電腦端則開發一套演算法去計算行走步數及估計行走步長，使用者只要配戴本裝置及輸入腿長，便可得到行走步數、步長、速度及距離等資訊。本論文先利用9個健康受試者於操場上各走路及跑步100公尺3次，並利用這些資料得到相關的系統參數。然後，另外用8個健康受試者驗證本系統的準確度，在操場上進行走路及跑步100公尺各2次。其走路與跑步之計步估計準確度分別為99.7%及99.9%，標準差為1.08%及1.46%。和市售計步器比較，本論文無論在走路或跑步狀態，都具有相當高的準確度。另外，走路與跑步之步長估計準確度分別為97.4%及99.12%，標準差為3.9%及10.3%。

In order to increase the accuracy of commercial pedometers, this thesis developed a wearable device and an acceleration-based algorithm to evaluate the step counts and step length for both walking and running status. This device uses a CC2540 single-chip and a tri-axial accelerometer ADXL345 to design this wearable device. The signals of 3-axis accelerometer are transmitted to PC via a Bluetooth 4.0 interface. Subject wears this device and input their leg length, and then the algorithms will calculate their step counts, step length, speed and distance, etc.. In order to get related parameters of system, nine health subjects are asked to walk and run 100 meters for three times in playground, respectively. Then, another eight health subjects are participated in the same experiments, the accuracy of estimated mean step counts for walking and running are 99.7%  1% and 100.1%  1.1%, respectively. Comparing with commercial pedometers, our method has high accuracy in both of walking and running status. The accuracy of estimated mean step length for walking and running are 97.4%  3.9% and 99.1%  10.3%, respectively.

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