前言：國民運動人口數逐年增加，而運動的目的是為了促進健康，因此精準地測得身體活動量就變得很重要。近年來電子產業興盛及穿戴式技術純熟，加速規在準確度、體積與便利性都有大突破，目前已成為大眾記錄身體活動量的必需品。雖然加速規普遍應用在身體活動量計，但加速規的運算方式多樣化，到目前為止尚未有一標準。行進速度為運動強度指標，但身體加速度與行進速度之間的關係到目前為止也尚未明確。故本研究目的在探討（一） 身體加速度與行進速度、心跳儲備率 (HRR%) 之間關係為何。(二) 不同速度走跑，比較身體加速度運算方式何者為佳。方法：招募19名非運動選手的健康男性作為實驗參與者，測試過程中穿戴心率帶及三軸加速規，分別在不同速度下進行走路和跑步的實驗，每個速度各進行3分鐘，中間休息至恢復站立休息心率，每個試驗分別收取穩定心率時的一分鐘資料進行數據分析，加速度經不同運算方式處理後，分別與行進速度、心跳儲備率 (HRR%) 做相關分析。統計使用皮爾森績差相關，比較走路、跑步及整個走跑過程，身體加速度與行進速度、心跳儲備率 (HRR%) 之相關性。結果：在走路、跑步及整個走跑過程中，合加速度峰值與前後軸加速度MAD值皆與行進速度 (r=.829**、.514**、.836**； r=.833**、.637**、.780**)、HRR% (r=.771**、.517**、.856**； r= .837**、.651**、.787**) 呈高度相關。結論：身體合加速度峰值及前後軸加速度MAD值推估走路、跑步及整個走跑過程的運動強度是可行的，此結果可作為未來身體活動量計應用之基礎。

Introduction：The population engaged in exercise increases annually. One of the main reasons for exercising is for promoting overall health; therefore, the accuracy of measuring physical activity is critical. In recent years, the electronic industry has been booming and wearable technology is getting increasingly mature. The accelerometer has made a big breakthrough in accuracy, volume and convenience and is now a necessity for recording physical activity. Although accelerometers are commonly used in measuring physical activity, the algorithms are quite diverse and not yet standardized. The moving speed is an index of exercise intensity but the correlations between the physical acceleration and moving speed are not yet clear. Purpose: The purpose of this study is to examine: 1) the correlations between the physical acceleration, moving speed and heart rate reserve (HRR%)； 2） a better algorithm for estimating physical acceleration at different walking and running speeds. Method: This study recruited 19 healthy males who were asked to wear a heart rate monitor and a tri-axis accelerometer to perform walking and running at different speeds. Each speed was tested for 3 minutes followed by a rest until the participants returned to their standing rest heart rate. A one-minute stable heart rate of each trial was gathered for data analysis. After being processed with different algorithms the acceleration values were analyzed with moving speeds and HRR% respectively. The Pearson product-moment correlation coefficient was used to examine the relationships between walking, running, the entire walking-running period, physical acceleration, moving speeds and HRR%. Result: In the walking, running, and the entire walking-running period, the peak values of resultant acceleration and the MAD values of anterior-posterior acceleration showed significant correlations with moving speeds (r=.829**、.514**、.836**； r=.833**、.637**、.780**) and HRR% (r=.771**、.517**、.856**； r= .837**、.651**、.787**). Conclusion: It is feasible to estimate the exercise intensity for walking, running and the entire walking-running period with the peak values of resultant acceleration and the MAD values of anterior-posterior acceleration. The results can be used as a foundation for the future application in measuring physical activity.

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