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| 准确提取脉搏血氧信号特征值是计算血氧饱和度的关键。本文提出一种基于一元线性回归模型的动态实时提取算法。利用搭建的脉搏血氧信号实验平台采集了含有闭气过程的光电容积脉搏波信号，分析发现IR和RD两束透射光强之间具有很强的相关性（r> 0.9），基于线性回归模型提取了特征值，较移动平均算法提取的结果具有相同的变化趋势，两者均能反映闭气过程中的血氧饱和度变化。结果表明，本方法切实有效，可以实现血氧饱和度的实时监测。 |
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fjtony163
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【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ...
Mally89(金币+1): 感谢应助！~欢迎常来！~吼吼！~\(^o^)/~ 2012-03-05 15:40:05
GlintRock(金币+160, 翻译EPI+1): ★★★很有帮助 2012-03-05 19:38:30
Mally89(金币+1): 感谢应助！~欢迎常来！~吼吼！~\(^o^)/~ 2012-03-05 15:40:05
GlintRock(金币+160, 翻译EPI+1): ★★★很有帮助 2012-03-05 19:38:30
| It is essential to precisely select characteristic value of pulse blood oxygen signal for calculate the blood oxygen saturation. The article sets up an active real-time selection algorithm based on one variable linear regression model. It used settled pulse blood oxygen signal experimental platform to collect pulse wave signal of photoelectric volume including breath suspending process. After analyzed, a strong correlation (r>0.9) was found between strength of IR and RD. It selected characteristic value based on linear regression model and the result has same changing trend compared to mobile average algorithm. Both of them can illustrate the blood oxygen saturation change during breath suspending process. The result showed that this method was efficient and could realize the real-time monitor on blood oxygen saturation. |
2楼2012-03-05 15:27:11
| It is essential to extract the R value of pulse oximetry signals for calculate the pulse oxygen saturation(SpO2). This paper presents a dynamically real-time algorithm based on linear regression model. It used an acquisition system to collect photoplethysmography(PPG) signals including breath suspending process. After analyzed, a significant correlation (r>0.9) is found between IR and RD. R value is calculated by linear regression, and the result has the same changing trends compared to moving average algorithm. Both of them can illustrate the SpO2 changes during breath suspending process. Comparison analysis indicated that, linear regression is more effective and can be used for real-time monitoring purpose. |
3楼2012-03-05 19:37:41
4楼2012-03-05 19:38:15
fjtony163
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5楼2012-03-06 02:03:59
6楼2012-03-06 07:41:56