文章目錄

• 1 簡介
• 2 主要器件
• 3 實現效果
• 4 設計原理
• • 4.1 MAX30102 模塊
  • 4.2 心率檢測的基本原理
  • • 4.2.1 PPG光電容積法
    • 4.2.2 心電信號測量法
  • 5 部分實現代碼
• 6 最后

1 簡介

Hi，大家好，今天向大家介紹一個學長做的單片機項目

基于STM32的心率檢測器的設計與實現

大家可用于 課程設計 或 畢業設計

2 主要器件

• 主控：STM32F103C8T6
• MAX30102傳感器
• OLED屏幕：用于顯示實時心率波形

3 實現效果

未測試時的狀態：心率波形顯為平穩直線，即0

將手指放上進行心率測試：

還可以把圖像做成心形的

4 設計原理

4.1 MAX30102 模塊

MAX30102是一個集成的脈搏血氧儀和心率監測儀生物傳感器的模塊。它集成了一個紅光 LEO 和一個紅外光 LEO 、光電檢測器、光器件，以及帶環境光抑制的低噪聲電子電路。MAX30102采用一個 1.8V電源和一個獨立的 5.0V 用于內部 LEO 的電源，應用于可穿戴設備進行心率和血氧采集檢測，佩戴于手指、耳垂和手腕等處。標準的I2C兼容的通信接口可以將采集到的數值傳輸給Arduino、STM32 等單片機進行心率和血氧計算。此外，該芯片還可通過軟件關斷模塊，待機電流接近為零，實現電源始終維持供電狀態。

芯片內部電路圖：

4.2 心率檢測的基本原理

4.2.1 PPG光電容積法

由于人體的皮膚、骨骼、肌肉、脂肪等對于光的反射是固定值，而毛細血管和動脈、靜脈由于隨著脈搏容積不停變大變小，所以對光的反射值是波動值，而這個波動值正好與心率一致，所以光電容積法正是通過這個波動的頻率來確定使用者的心率數據。

目前市面上絕大多數的智能手環/手表都采用這種方式監測心率，而且這種方式的技術方案已經比較成熟，所以價格也相對較低。

4.2.2 心電信號測量法

還有一種就是心電信號測量法，它通過智能穿戴設備上搭載的傳感器捕捉人每次心跳時微小的電極變化，再經過算法還原出心率跳動的頻率，原理和心電圖類似原理。目前已經很少有智能穿戴設備采用這種方式了。

5 部分實現代碼

心率血樣算法：

/** \file algorithm.c ****************************************************** * * Project: MAXREFDES117# * Filename: algorithm.cpp * Description: This module calculates the heart rate/SpO2 level * * * -------------------------------------------------------------------- * * This code follows the following naming conventions: * * char ch_pmod_value * char (array) s_pmod_s_string[16] * float f_pmod_value * int32_t n_pmod_value * int32_t (array) an_pmod_value[16] * int16_t w_pmod_value * int16_t (array) aw_pmod_value[16] * uint16_t uw_pmod_value * uint16_t (array) auw_pmod_value[16] * uint8_t uch_pmod_value * uint8_t (array) auch_pmod_buffer[16] * uint32_t un_pmod_value * int32_t * pn_pmod_value * * ------------------------------------------------------------------------- */ /******************************************************************************* * Copyright (C) 2016 Maxim Integrated Products, Inc., All Rights Reserved. * * Permission is hereby granted, free of charge, to any person obtaining a * copy of this software and associated documentation files (the "Software"), * to deal in the Software without restriction, including without limitation * the rights to use, copy, modify, merge, publish, distribute, sublicense, * and/or sell copies of the Software, and to permit persons to whom the * Software is furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included * in all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. * IN NO EVENT SHALL MAXIM INTEGRATED BE LIABLE FOR ANY CLAIM, DAMAGES * OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, * ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR * OTHER DEALINGS IN THE SOFTWARE. * * Except as contained in this notice, the name of Maxim Integrated * Products, Inc. shall not be used except as stated in the Maxim Integrated * Products, Inc. Branding Policy. * * The mere transfer of this software does not imply any licenses * of trade secrets, proprietary technology, copyrights, patents, * trademarks, maskwork rights, or any other form of intellectual * property whatsoever. Maxim Integrated Products, Inc. retains all * ownership rights. ******************************************************************************* */ #include "algorithm.h"const uint16_t auw_hamm[31]={ 41, 276, 512, 276, 41 }; //Hamm= long16(512* hamming(5)'); //uch_spo2_table is computed as -45.060*ratioAverage* ratioAverage + 30.354 *ratioAverage + 94.845 ; const uint8_t uch_spo2_table[184]={ 95, 95, 95, 96, 96, 96, 97, 97, 97, 97, 97, 98, 98, 98, 98, 98, 99, 99, 99, 99, 99, 99, 99, 99, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 99, 99, 99, 99, 99, 99, 99, 99, 98, 98, 98, 98, 98, 98, 97, 97, 97, 97, 96, 96, 96, 96, 95, 95, 95, 94, 94, 94, 93, 93, 93, 92, 92, 92, 91, 91, 90, 90, 89, 89, 89, 88, 88, 87, 87, 86, 86, 85, 85, 84, 84, 83, 82, 82, 81, 81, 80, 80, 79, 78, 78, 77, 76, 76, 75, 74, 74, 73, 72, 72, 71, 70, 69, 69, 68, 67, 66, 66, 65, 64, 63, 62, 62, 61, 60, 59, 58, 57, 56, 56, 55, 54, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33, 31, 30, 29, 28, 27, 26, 25, 23, 22, 21, 20, 19, 17, 16, 15, 14, 12, 11, 10, 9, 7, 6, 5, 3, 2, 1 } ; static int32_t an_dx[ BUFFER_SIZE-MA4_SIZE]; // delta static int32_t an_x[ BUFFER_SIZE]; //ir static int32_t an_y[ BUFFER_SIZE]; //redvoid maxim_heart_rate_and_oxygen_saturation(uint32_t *pun_ir_buffer, int16_t n_ir_buffer_length, uint32_t *pun_red_buffer, int16_t *pn_spo2, int8_t *pch_spo2_valid, int16_t *pn_heart_rate, int8_t *pch_hr_valid) /** * \brief Calculate the heart rate and SpO2 level * \par Details * By detecting peaks of PPG cycle and corresponding AC/DC of red/infra-red signal, the ratio for the SPO2 is computed. * Since this algorithm is aiming for Arm M0/M3. formaula for SPO2 did not achieve the accuracy due to register overflow. * Thus, accurate SPO2 is precalculated and save longo uch_spo2_table[] per each ratio. * * \param[in] *pun_ir_buffer - IR sensor data buffer * \param[in] n_ir_buffer_length - IR sensor data buffer length * \param[in] *pun_red_buffer - Red sensor data buffer * \param[out] *pn_spo2 - Calculated SpO2 value * \param[out] *pch_spo2_valid - 1 if the calculated SpO2 value is valid * \param[out] *pn_heart_rate - Calculated heart rate value * \param[out] *pch_hr_valid - 1 if the calculated heart rate value is valid * * \retval None */ {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[15] ;int32_t an_exact_ir_valley_locs[15] ;int32_t an_dx_peak_locs[15] ;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[5],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[k] ;un_ir_mean =un_ir_mean/n_ir_buffer_length ;for (k=0 ; k<n_ir_buffer_length ; k++ ) an_x[k] = pun_ir_buffer[k] - un_ir_mean ; // 4 pt Moving Averagefor(k=0; k< BUFFER_SIZE-MA4_SIZE; k++){n_denom= ( an_x[k]+an_x[k+1]+ an_x[k+2]+ an_x[k+3]);an_x[k]= n_denom/(int32_t)4; }// get difference of smoothed IR signalfor( k=0; k<BUFFER_SIZE-MA4_SIZE-1; k++)an_dx[k]= (an_x[k+1]- an_x[k]);// 2-pt Moving Average to an_dxfor(k=0; k< BUFFER_SIZE-MA4_SIZE-2; k++){an_dx[k] = ( an_dx[k]+an_dx[k+1])/2 ;}// hamming window// flip wave form so that we can detect valley with peak detectorfor ( i=0 ; i<BUFFER_SIZE-HAMMING_SIZE-MA4_SIZE-2 ;i++){s= 0;for( k=i; k<i+ HAMMING_SIZE ;k++){s -= an_dx[k] *auw_hamm[k-i] ; }an_dx[i]= s/ (int32_t)1146; // divide by sum of auw_hamm }n_th1=0; // threshold calculationfor ( k=0 ; k<BUFFER_SIZE-HAMMING_SIZE ;k++){n_th1 += ((an_dx[k]>0)? an_dx[k] : ((int32_t)0-an_dx[k])) ;}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[k]-an_dx_peak_locs[k -1]);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[k]=an_dx_peak_locs[k]+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[k] = pun_ir_buffer[k] ; an_y[k] = pun_red_buffer[k] ; }// find precise min near an_ir_valley_locsn_exact_ir_valley_locs_count =0; for(k=0 ; k<n_npks ;k++){un_only_once =1;m=an_ir_valley_locs[k];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[i]<n_c_min){if (un_only_once >0){un_only_once =0;} n_c_min= an_x[i] ;an_exact_ir_valley_locs[k]=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 MAfor(k=0; k< BUFFER_SIZE-MA4_SIZE; k++){an_x[k]=( an_x[k]+an_x[k+1]+ an_x[k+2]+ an_x[k+3])/(int32_t)4;an_y[k]=( an_y[k]+an_y[k+1]+ an_y[k+2]+ an_y[k+3])/(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 locationsn_ratio_average =0; n_i_ratio_count =0; for(k=0; k< 5; k++) an_ratio[k]=0;for (k=0; k< n_exact_ir_valley_locs_count; k++){if (an_exact_ir_valley_locs[k] > 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[k+1]-an_exact_ir_valley_locs[k] >10){for (i=an_exact_ir_valley_locs[k]; i< an_exact_ir_valley_locs[k+1]; i++){if (an_x[i]> n_x_dc_max) {n_x_dc_max =an_x[i];n_x_dc_max_idx =i; }if (an_y[i]> n_y_dc_max) {n_y_dc_max =an_y[i];n_y_dc_max_idx=i;}}n_y_ac= (an_y[an_exact_ir_valley_locs[k+1]] - an_y[an_exact_ir_valley_locs[k] ] )*(n_y_dc_max_idx -an_exact_ir_valley_locs[k]); //redn_y_ac= an_y[an_exact_ir_valley_locs[k]] + n_y_ac/ (an_exact_ir_valley_locs[k+1] - an_exact_ir_valley_locs[k]) ; n_y_ac= an_y[n_y_dc_max_idx] - n_y_ac; // subracting linear DC compoenents from raw n_x_ac= (an_x[an_exact_ir_valley_locs[k+1]] - an_x[an_exact_ir_valley_locs[k] ] )*(n_x_dc_max_idx -an_exact_ir_valley_locs[k]); // irn_x_ac= an_x[an_exact_ir_valley_locs[k]] + n_x_ac/ (an_exact_ir_valley_locs[k+1] - an_exact_ir_valley_locs[k]); n_x_ac= an_x[n_y_dc_max_idx] - n_x_ac; // subracting linear DC compoenents from raw n_nume=( n_y_ac *n_x_dc_max)>>7 ; //prepare X100 to preserve floating valuen_denom= ( n_x_ac *n_y_dc_max)>>7;if (n_denom>0 && n_i_ratio_count <5 && n_nume != 0){ an_ratio[n_i_ratio_count]= (n_nume*100)/n_denom ; //formular is ( n_y_ac *n_x_dc_max) / ( n_x_ac *n_y_dc_max) ;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[n_middle_idx-1] +an_ratio[n_middle_idx])/2; // use medianelsen_ratio_average = an_ratio[n_middle_idx ];if( n_ratio_average>2 && n_ratio_average <184){n_spo2_calc= uch_spo2_table[n_ratio_average] ;*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; } }void maxim_find_peaks(int32_t *pn_locs, int32_t *pn_npks, int32_t *pn_x, int32_t n_size, int32_t n_min_height, int32_t n_min_distance, int32_t n_max_num) /** * \brief Find peaks * \par Details * Find at most MAX_NUM peaks above MIN_HEIGHT separated by at least MIN_DISTANCE * * \retval None */ {maxim_peaks_above_min_height( pn_locs, pn_npks, pn_x, n_size, n_min_height );maxim_remove_close_peaks( pn_locs, pn_npks, pn_x, n_min_distance );*pn_npks = min( *pn_npks, n_max_num ); }void maxim_peaks_above_min_height(int32_t *pn_locs, int32_t *pn_npks, int32_t *pn_x, int32_t n_size, int32_t n_min_height) /** * \brief Find peaks above n_min_height * \par Details * Find all peaks above MIN_HEIGHT * * \retval None */ {int32_t i = 1, n_width;*pn_npks = 0;while (i < n_size-1){if (pn_x[i] > n_min_height && pn_x[i] > pn_x[i-1]){ // find left edge of potential peaksn_width = 1;while (i+n_width < n_size && pn_x[i] == pn_x[i+n_width]) // find flat peaksn_width++;if (pn_x[i] > pn_x[i+n_width] && (*pn_npks) < 15 ){ // find right edge of peakspn_locs[(*pn_npks)++] = i; // for flat peaks, peak location is left edgei += n_width+1;}elsei += n_width;}elsei++;} }void maxim_remove_close_peaks(int32_t *pn_locs, int32_t *pn_npks, int32_t *pn_x, int32_t n_min_distance) /** * \brief Remove peaks * \par Details * Remove peaks separated by less than MIN_DISTANCE * * \retval None */ {int32_t i, j, n_old_npks, n_dist;/* Order peaks from large to small */maxim_sort_indices_descend( pn_x, pn_locs, *pn_npks );for ( i = -1; i < *pn_npks; i++ ){n_old_npks = *pn_npks;*pn_npks = i+1;for ( j = i+1; j < n_old_npks; j++ ){n_dist = pn_locs[j] - ( i == -1 ? -1 : pn_locs[i] ); // lag-zero peak of autocorr is at index -1if ( n_dist > n_min_distance || n_dist < -n_min_distance )pn_locs[(*pn_npks)++] = pn_locs[j];}}// Resort indices longo ascending ordermaxim_sort_ascend( pn_locs, *pn_npks ); }void maxim_sort_ascend(int32_t *pn_x,int32_t n_size) /** * \brief Sort array * \par Details * Sort array in ascending order (insertion sort algorithm) * * \retval None */ {int32_t i, j, n_temp;for (i = 1; i < n_size; i++) {n_temp = pn_x[i];for (j = i; j > 0 && n_temp < pn_x[j-1]; j--)pn_x[j] = pn_x[j-1];pn_x[j] = n_temp;} }void maxim_sort_indices_descend(int32_t *pn_x, int32_t *pn_indx, int32_t n_size) /** * \brief Sort indices * \par Details * Sort indices according to descending order (insertion sort algorithm) * * \retval None */ {int32_t i, j, n_temp;for (i = 1; i < n_size; i++) {n_temp = pn_indx[i];for (j = i; j > 0 && pn_x[n_temp] > pn_x[pn_indx[j-1]]; j--)pn_indx[j] = pn_indx[j-1];pn_indx[j] = n_temp;} }

6 最后

總結

以上是生活随笔為你收集整理的毕业设计 单片机心率检测器设计与实现 - stm32的全部內容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯，歡迎將生活随笔推薦給好友。