最近爆火的电子血氧仪是什么原理？测的准吗？
最近爆火的电子血氧仪是什么原理？测的准吗？继口罩、抗原、药品之后，最近电子血氧仪的价格也开始水涨船高。从一个多月前的100多元，暴涨到了300多元。
那么，这类家用的电子血氧仪是如何工作的呢？测量数据到底准不准？今天就带大家来分析一下。
一、血氧仪工作原理血氧仪是一种监测脉搏、血氧饱和度等指标的医疗器械，常见的家用型血氧仪，主要有指夹式、腕表式等形式。一般大家最关注的是血氧饱和度（oxygen saturation简写为SpO2），它是指在全部血容量中被结合O2容量占全部可结合的O2容量的百分比，是人体携带氧气能力的重要参考值。人体正常的SpO2应该不小于95%，长期低于93%时需要就医。SpO2 一般由以下公式计算：
其中CHbO2是氧合血红蛋白浓度，CHb是还原血红蛋白浓度。一方面，这两种血红蛋白对不同波长的光有不同的吸收度；另一方面，当动脉跳动时，动脉中的血液量会发生变化，可以区分出皮肤、肌肉、静脉血等对光的吸收影响（这些组织对光的吸收可以认为固定不变）。因此，利用两种不同波长的光，经透射或反射后，采集数据综合处理，就能计算出血氧饱和度。现在市面上最常见的，都是光电式的血氧仪，如下图所示，有透射式和反射式两种实现方法。常见的指夹式血氧仪就是透射式，智能手环或手表就是反射式，原理是差不多的。
而LED光源的选择，与血红蛋白对不同光波长的吸收率有关，下图是两种血红蛋白对不同波长的光的消光系数图：
可以看到，两种血红蛋白对波长为660nm左右光的吸收差别最大，而对波长为800nm左右光的吸收基本相等。从理论上说，使用660nm和800nm波长的光作为光源是最合适的，但由于在800nm左右时，二者的消光系数斜率相差较大，光波长偏差一点就会引起较大的吸收率变化，这对LED的制造工艺要求太高。所以，工程实现时，一般不用800nm波长的LED，而选择波长为860nm~920nm的LED作为另一个光源，这个区间的消光系数斜率基本一样，而且变化平缓。至此，硬件部分的实现我们已经了解大概了，其实核心就是要使用两个LED作为光源，一个660nm波长的红外光，一个900nm左右波长的红光。两束光分别通过透射（或反射）皮肤后，到达光电接收管，再采集光电接收管的值。那么，采集到两个光源的值后，又该如何处理呢？这里由于有比较多的公式推导，我们直接略过，给出下面的公式：这里的实现需要三步：第一步，我们采集的两个LED光源的值，需要分离出直流分量和交流分量，也就是：红光的交流分量ACred、红光的直流分量DCred、红外光的交流分量ACired、红外光的直流分量DCired；第二步，用采集到的四个值，计算出R；第三步，用R计算SpO2，这个计算公式中a、b、c是三个需要校准的参数。需要大量的试验数据去拟合出来。二、血氧仪的制作有了以上的理论基础，我们可以自己动手DIY一个血氧仪。Maxim公司有一款集成芯片，可以实现大部分的硬件功能，就是MAX30100、MAX30102系列芯片。MAX30100已停产，新设计中不推荐使用，MAX30102是新一代产品。目前价格还没有太离谱：
MAX30102集成了一个660nm红光LED、880nm红外光LED、光电检测器，以及带环境光抑制的低噪声电子电路。芯片内部含18bit ADC采集电路。对外是I2C接口。基本上单芯片就能实现光源信号的采集。要注意，MAX30102的输出值，只是两个LED光源的采集值。后续还需要软件去实现交流、直流分离，R的求解、SpO2的求解。顺带也可以求解出脉搏数据。使用max30102很简单，用I2C接口访问，初始化代码如下：max30102_Bus_Write(REG_INTR_ENABLE_1,0xc0);// INTR settingmax30102_Bus_Write(REG_INTR_ENABLE_2,0x00);max30102_Bus_Write(REG_FIFO_WR_PTR,0x00); //FIFO_WR_PTRmax30102_Bus_Write(REG_OVF_COUNTER,0x00); //OVF_COUNTERmax30102_Bus_Write(REG_FIFO_RD_PTR,0x00); //FIFO_RD_PTRmax30102_Bus_Write(REG_FIFO_CONFIG,0x0f); //sample avg = 1, fifo rollover=false, fifo almost full = 17max30102_Bus_Write(REG_MODE_CONFIG,0x03); //0x02 for Red only, 0x03 for SpO2 mode 0x07 multimode LEDmax30102_Bus_Write(REG_SPO2_CONFIG,0x27); // SPO2_ADC range = 4096nA, SPO2 sample rate (100 Hz), LED pulseWidth (400uS)max30102_Bus_Write(REG_LED1_PA,0x24); //Choose value for ~ 7mA for LED1max30102_Bus_Write(REG_LED2_PA,0x24); // Choose value for ~ 7mA for LED2max30102_Bus_Write(REG_PILOT_PA,0x7f); // Choose value for ~ 25mA for Pilot LED
主函数中循环调用fifo读取函数，用于获取LED光源的采集值：void maxim_max30102_read_fifo(uint32_t *pun_red_led, uint32_t *pun_ir_led){uint32_t un_temp;unsigned char uch_temp;char ach_i2c_data;*pun_red_led=0;*pun_ir_led=0;
//read and clear status registermaxim_max30102_read_reg(REG_INTR_STATUS_1, &uch_temp);maxim_max30102_read_reg(REG_INTR_STATUS_2, &uch_temp);
IIC_ReadBytes(I2C_WRITE_ADDR,REG_FIFO_DATA,(u8 *)ach_i2c_data,6);
un_temp=(unsigned char) ach_i2c_data;un_temp<<=16;*pun_red_led+=un_temp;un_temp=(unsigned char) ach_i2c_data;un_temp<<=8;*pun_red_led+=un_temp;un_temp=(unsigned char) ach_i2c_data;*pun_red_led+=un_temp;
un_temp=(unsigned char) ach_i2c_data;un_temp<<=16;*pun_ir_led+=un_temp;un_temp=(unsigned char) ach_i2c_data;un_temp<<=8;*pun_ir_led+=un_temp;un_temp=(unsigned char) ach_i2c_data;*pun_ir_led+=un_temp;*pun_red_led&=0x03FFFF;//Mask MSB *pun_ir_led&=0x03FFFF;//Mask MSB }
采集值最好经过滤波，以减少噪声的干扰。之后，再分离出交流、直流分量，求出R和SpO2即可，核心是这个函数：void maxim_heart_rate_and_oxygen_saturation(uint32_t *pun_ir_buffer,int32_t n_ir_buffer_length, uint32_t *pun_red_buffer, int32_t *pn_spo2, int8_t *pch_spo2_valid, int32_t *pn_heart_rate, int8_t*pch_hr_valid){ uint32_t un_ir_mean ,un_only_once ; int32_t k ,n_i_ratio_count; int32_t i, s, m, n_exact_ir_valley_locs_count ,n_middle_idx; int32_t n_th1, n_npks,n_c_min; int32_t an_ir_valley_locs ; int32_t an_exact_ir_valley_locs ; int32_t an_dx_peak_locs ; int32_t n_peak_interval_sum;
int32_t n_y_ac, n_x_ac; int32_t n_spo2_calc; int32_t n_y_dc_max, n_x_dc_max; int32_t n_y_dc_max_idx, n_x_dc_max_idx; int32_t an_ratio,n_ratio_average; int32_t n_nume,n_denom ; // remove DC of ir signal un_ir_mean =0; for (k=0 ; k<n_ir_buffer_length ; k++ ) un_ir_mean += pun_ir_buffer ; un_ir_mean =un_ir_mean/n_ir_buffer_length ; for (k=0 ; k<n_ir_buffer_length ; k++ )an_x =pun_ir_buffer - un_ir_mean ;
// 4 pt Moving Average for(k=0; k< BUFFER_SIZE-MA4_SIZE; k++){ n_denom= ( an_x+an_x+ an_x+ an_x); an_x=n_denom/(int32_t)4; }
// get difference of smoothed IR signal for( k=0; k<BUFFER_SIZE-MA4_SIZE-1;k++) an_dx= (an_x- an_x);
// 2-pt Moving Average to an_dx for(k=0; k< BUFFER_SIZE-MA4_SIZE-2; k++){ an_dx =( an_dx+an_dx)/2 ; }
// hamming window // flip wave form so that we can detect valley with peak detector for ( i=0 ; i<BUFFER_SIZE-HAMMING_SIZE-MA4_SIZE-2 ;i++){ s= 0; for( k=i; k<i+ HAMMING_SIZE ;k++){ s -= an_dx *auw_hamm ; } an_dx= s/ (int32_t)1146; // divide by sum of auw_hamm }
n_th1=0; // threshold calculation for ( k=0 ; k<BUFFER_SIZE-HAMMING_SIZE ;k++){ n_th1 += ((an_dx>0)? an_dx : ((int32_t)0-an_dx)) ; } n_th1= n_th1/ ( BUFFER_SIZE-HAMMING_SIZE); // peak location is acutally index for sharpest location of raw signal since we flipped the signal maxim_find_peaks( an_dx_peak_locs, &n_npks, an_dx, BUFFER_SIZE-HAMMING_SIZE, n_th1, 8, 5 );//peak_height, peak_distance, max_num_peaks
n_peak_interval_sum =0; if (n_npks>=2){ for (k=1; k<n_npks; k++) n_peak_interval_sum += (an_dx_peak_locs-an_dx_peak_locs); n_peak_interval_sum=n_peak_interval_sum/(n_npks-1); *pn_heart_rate=(int32_t)(6000/n_peak_interval_sum);// beats per minutes *pch_hr_valid= 1; } else{ *pn_heart_rate = -999; *pch_hr_valid= 0; }
for ( k=0 ; k<n_npks ;k++) an_ir_valley_locs=an_dx_peak_locs+HAMMING_SIZE/2;
// raw value : RED(=y) and IR(=X) // we need to assess DC and AC value of ir and red PPG. for (k=0 ; k<n_ir_buffer_length ; k++ ){ an_x =pun_ir_buffer ; an_y =pun_red_buffer ; }
// find precise min near an_ir_valley_locs n_exact_ir_valley_locs_count =0; for(k=0 ; k<n_npks ;k++){ un_only_once =1; m=an_ir_valley_locs; n_c_min= 16777216;//2^24; if (m+5 <BUFFER_SIZE-HAMMING_SIZE&& m-5 >0){ for(i= m-5;i<m+5; i++) if (an_x<n_c_min){ if (un_only_once >0){ un_only_once =0; } n_c_min= an_x ; an_exact_ir_valley_locs=i; } if (un_only_once ==0) n_exact_ir_valley_locs_count ++ ; } } if (n_exact_ir_valley_locs_count <2 ){ *pn_spo2 =-999 ; // do not use SPO2 since signal ratio is out of range *pch_spo2_valid= 0; return; } // 4 pt MA for(k=0; k< BUFFER_SIZE-MA4_SIZE; k++){ an_x=( an_x+an_x+ an_x+ an_x)/(int32_t)4; an_y=( an_y+an_y+ an_y+ an_y)/(int32_t)4; }
//using an_exact_ir_valley_locs , find ir-red DC andir-red AC for SPO2 calibration ratio //finding AC/DC maximum of raw ir * red between two valley locations n_ratio_average =0; n_i_ratio_count =0;
for(k=0; k< 5; k++) an_ratio=0; for (k=0; k< n_exact_ir_valley_locs_count; k++){ if (an_exact_ir_valley_locs > BUFFER_SIZE ){ *pn_spo2 =-999 ; // do not use SPO2 since valley loc is out of range *pch_spo2_valid= 0; return; } } // find max between two valley locations // and use ratio betwen AC compoent of Ir & Red and DC compoent of Ir & Red for SPO2
for (k=0; k< n_exact_ir_valley_locs_count-1; k++){ n_y_dc_max= -16777216 ; n_x_dc_max= - 16777216; if (an_exact_ir_valley_locs-an_exact_ir_valley_locs >10){ for (i=an_exact_ir_valley_locs; i< an_exact_ir_valley_locs; i++){ if (an_x> n_x_dc_max) {n_x_dc_max =an_x;n_x_dc_max_idx =i; } if (an_y> n_y_dc_max) {n_y_dc_max =an_y;n_y_dc_max_idx=i;} } n_y_ac= (an_y] - an_y ] )*(n_y_dc_max_idx -an_exact_ir_valley_locs); //red n_y_ac=an_y] + n_y_ac/ (an_exact_ir_valley_locs - an_exact_ir_valley_locs);
n_y_ac=an_y - n_y_ac; // subracting linear DC compoenents from raw n_x_ac= (an_x] - an_x ] )*(n_x_dc_max_idx -an_exact_ir_valley_locs); // ir n_x_ac=an_x] + n_x_ac/ (an_exact_ir_valley_locs - an_exact_ir_valley_locs); n_x_ac=an_x - n_x_ac; // subracting linear DC compoenents from raw n_nume=( n_y_ac *n_x_dc_max)>>7 ; //prepare X100 to preserve floating value n_denom= ( n_x_ac *n_y_dc_max)>>7; if (n_denom>0&& n_i_ratio_count <5 &&n_nume != 0) { an_ratio= (n_nume*20)/n_denom ; //formular is ( n_y_ac *n_x_dc_max) / ( n_x_ac *n_y_dc_max) ;///*************************n_nume原来是*100************************// n_i_ratio_count++; } } }
maxim_sort_ascend(an_ratio, n_i_ratio_count); n_middle_idx= n_i_ratio_count/2;
if (n_middle_idx >1) n_ratio_average =( an_ratio +an_ratio)/2; // use median else n_ratio_average = an_ratio;
if( n_ratio_average>2 && n_ratio_average <184){ n_spo2_calc= uch_spo2_table ; *pn_spo2 = n_spo2_calc ; *pch_spo2_valid= 1;//float_SPO2 =-45.060*n_ratio_average* n_ratio_average/10000 + 30.354 *n_ratio_average/100 + 94.845 ;// for comparison with table } else{ *pn_spo2 =-999 ; // do not use SPO2 since signal ratio is out of range *pch_spo2_valid= 0; }}需要注意的是，这里使用的函数是SpO2 = -45.060*R*R+ 30.354*R+ 94.845，采用了查表法求解。
这个函数执行完后，变量n_heart_rate中存储的是心率，变量n_sp02存储的就是血氧饱和度。最后将血氧饱和度值显示出来就行了。
三、血氧仪测量准不准？
在实现过程中，SpO2与R的关系的系数是非常难确定的，需要大量的试验数据来拟合，见下图，是maxim公司应用文档中的拟合过程：（每种颜色是一组测试结果，黄色叉是去除掉的偏离比较大的野值）可以发现，有些测量数据的方差是相当大的，很多数据偏离了拟合后的曲线很远。maxim公司建议在校准时，需要不断剔除偏离较大的数据，均方根误差（RMES）需要在3.5%以内。最终给出一组值：可是，在另一篇maxim公司的应用文档中，又给出了SpO2 = 104-17*R这个公式，其中0.4<R<3.4。
为什么这两公式相差这么大？
通过查阅一些论文发现，对于R值与血氧饱和度的公式并不固定，SpO2可以表示为R的一个高次的多项式函数，由于正常人体测出的R值都较小，人们一般关注的是R值小于1的情况，大于1已经是明显的不健康情况。所以，在计算SpO2时常常会去掉高次项，采用一阶函数或者二阶函数来拟合。又由于SpO2的测量方法本身误差较大，所以测量数据不同时，拟合出来的参数就大相径庭了。这里还收集了几个论文中拟合出的R值与SpO2之间的函数关系：
[*]SpO2 = -45.060*R*R+ 30.354*R+ 94.845
[*]SpO2 = -7.6*R*- 20.7*R+ 112.2，（0.5<R<1.4）
[*]SpO2 = -86.47*R*R+ 77.21*R+ 81.68，（0.4<R<1）
[*]SpO2 = -20*x+107.2,（0.36<R<0.66），-54*x+129.64,（0.66≤R<1）
把这几个函数的图形绘制在同一张图中：
可以看到，在R为0.4~1.0这个区间里，这些函数的值大体上相差不大，变化趋势也基本一样。而且这些参数，一般都是以正常人的数据来拟合的。所以，在正常血氧的范围内，可以认为用这种方法来测量血氧饱和度基本靠谱。而当血氧饱和度偏离正常值时，误差会显著增大。当然，这需要建立在光源的采集数据准确的前提下，也就是R值准确的时候。而现实是，在采集光源的数据时，会有环境光干扰、工频干扰、各种噪声干扰；即使滤除了这些噪声，还会有如下图这种低频的漂移。此时，要准确提取出光源的直流分量、交流分量是非常困难的。
因此，如果信号处理的算法不好，就会把微弱的噪声、漂移等等干扰识别为脉搏引起的光强变化，网上出现的各种能测出香肠的血氧和脉搏的笑话也就不足为奇了。综合来看，此类血氧仪作为健康监测的参考手段之一是可以的，但数据准确性存疑。所以，以它来判断身体是否健康是万万不能的！好了，本节内容就分享到这里了，希望这篇文章能对大家有所帮助。
来源：小白白学电子
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