stm32f103c8t6利用AD8232的心电信号通过ST778显示心率的心率算法程序

首先，需要连接AD8232心电传感器到STM32F103C8T6的ADC通道上，以获取心电信号。可以使用SPI或I2C等通信协议来与ST778进行通信，以显示心率。以下是可能的心率算法程序的示例：

#include "stm32f10x.h"

#define ADC1_DR_Address    ((u32)0x4001244C)

u16 ADC_ConvertedValue;
float voltage;

void ADC1_Configuration(void);
void USART1_Configuration(void);
void Delay(__IO uint32_t nCount);

int main(void)
{
  USART1_Configuration();
  ADC1_Configuration();

  while (1)
  {
    ADC_SoftwareStartConvCmd(ADC1, ENABLE);
    while (ADC_GetFlagStatus(ADC1, ADC_FLAG_EOC) == RESET);
    ADC_ConvertedValue = ADC_GetConversionValue(ADC1);
    voltage = ADC_ConvertedValue * (3.3/4096);

    printf("voltage: %.3fV\n\r", voltage);

    Delay(0xFFFFF);
  }
}

void ADC1_Configuration(void)
{
  ADC_InitTypeDef ADC_InitStructure;
  GPIO_InitTypeDef GPIO_InitStructure;

  RCC_APB2PeriphClockCmd(RCC_APB2Periph_GPIOA | RCC_APB2Periph_ADC1, ENABLE);

  GPIO_InitStructure.GPIO_Mode = GPIO_Mode_AIN;
  GPIO_InitStructure.GPIO_Pin = GPIO_Pin_0;
  GPIO_Init(GPIOA, &GPIO_InitStructure);

  ADC_InitStructure.ADC_Mode = ADC_Mode_Independent;
  ADC_InitStructure.ADC_ScanConvMode = DISABLE;
  ADC_InitStructure.ADC_ContinuousConvMode = DISABLE;
  ADC_InitStructure.ADC_ExternalTrigConv = ADC_ExternalTrigConv_None;
  ADC_InitStructure.ADC_DataAlign = ADC_DataAlign_Right;
  ADC_InitStructure.ADC_NbrOfChannel = 1;
  ADC_Init(ADC1, &ADC_InitStructure);

  ADC_RegularChannelConfig(ADC1, ADC_Channel_0, 1, ADC_SampleTime_55Cycles5);

  ADC_Cmd(ADC1, ENABLE);

  ADC_ResetCalibration(ADC1);
  while(ADC_GetResetCalibrationStatus(ADC1));

  ADC_StartCalibration(ADC1);
  while(ADC_GetCalibrationStatus(ADC1));
}

void USART1_Configuration(void)
{
  GPIO_InitTypeDef GPIO_InitStructure;
  USART_InitTypeDef USART_InitStructure;

  RCC_APB2PeriphClockCmd(RCC_APB2Periph_USART1 | RCC_APB2Periph_GPIOA, ENABLE);

  GPIO_InitStructure.GPIO_Pin = GPIO_Pin_9;
  GPIO_InitStructure.GPIO_Mode = GPIO_Mode_AF_PP;
  GPIO_InitStructure.GPIO_Speed = GPIO_Speed_50MHz;
  GPIO_Init(GPIOA, &GPIO_InitStructure);

  GPIO_InitStructure.GPIO_Pin = GPIO_Pin_10;
  GPIO_InitStructure.GPIO_Mode = GPIO_Mode_IN_FLOATING;
  GPIO_Init(GPIOA, &GPIO_InitStructure);

  USART_InitStructure.USART_BaudRate = 115200;
  USART_InitStructure.USART_WordLength = USART_WordLength_8b;
  USART_InitStructure.USART_StopBits = USART_StopBits_1;
  USART_InitStructure.USART_Parity = USART_Parity_No;
  USART_InitStructure.USART_HardwareFlowControl = USART_HardwareFlowControl_None;
  USART_InitStructure.USART_Mode = USART_Mode_Rx | USART_Mode_Tx;
  USART_Init(USART1, &USART_InitStructure);

  USART_Cmd(USART1, ENABLE);
}

void Delay(__IO uint32_t nCount)
{
  for(; nCount != 0; nCount--);
}

这是一个基础的ADC读取程序，将ADC1的通道0连接到AD8232的输出引脚。通过调用`ADC_SoftwareStartConvCmd()`函数来启动ADC转换，并在转换完成后读取结果。将结果转换为电压值并输出到串口，以便进行调试。

接下来，可以使用适当的心率算法来计算心率。一种简单的方法是计算R峰峰值之间的时间间隔，并使用该值来计算心率。 例如，以下是基于此方法的示例代码：

#include "stm32f10x.h"

#define ADC1_DR_Address    ((u32)0x4001244C)

u16 ADC_ConvertedValue;
float voltage;

int i = 0;
int R_peaks[10];
float R_peak_interval = 0;

void ADC1_Configuration(void);
void USART1_Configuration(void);
void Delay(__IO uint32_t nCount);
void find_R_peaks(float voltage);

int main(void)
{
  USART1_Configuration();
  ADC1_Configuration();

  while (1)
  {
    ADC_SoftwareStartConvCmd(ADC1, ENABLE);
    while (ADC_GetFlagStatus(ADC1, ADC_FLAG_EOC) == RESET);
    ADC_ConvertedValue = ADC_GetConversionValue(ADC1);
    voltage = ADC_ConvertedValue * (3.3/4096);

    find_R_peaks(voltage);

    if (i > 1) {
      R_peak_interval = (R_peaks[i-1] - R_peaks[i-2]) / 360.0; // assuming 360 samples per second
      printf("Heart rate: %.0f bpm\n\r", 60 / R_peak_interval);
    }

    Delay(0xFFFFF);
  }
}

void ADC1_Configuration(void)
{
  ADC_InitTypeDef ADC_InitStructure;
  GPIO_InitTypeDef GPIO_InitStructure;

  RCC_APB2PeriphClockCmd(RCC_APB2Periph_GPIOA | RCC_APB2Periph_ADC1, ENABLE);

  GPIO_InitStructure.GPIO_Mode = GPIO_Mode_AIN;
  GPIO_InitStructure.GPIO_Pin = GPIO_Pin_0;
  GPIO_Init(GPIOA, &GPIO_InitStructure);

  ADC_InitStructure.ADC_Mode = ADC_Mode_Independent;
  ADC_InitStructure.ADC_ScanConvMode = DISABLE;
  ADC_InitStructure.ADC_ContinuousConvMode = DISABLE;
  ADC_InitStructure.ADC_ExternalTrigConv = ADC_ExternalTrigConv_None;
  ADC_InitStructure.ADC_DataAlign = ADC_DataAlign_Right;
  ADC_InitStructure.ADC_NbrOfChannel = 1;
  ADC_Init(ADC1, &ADC_InitStructure);

  ADC_RegularChannelConfig(ADC1, ADC_Channel_0, 1, ADC_SampleTime_55Cycles5);

  ADC_Cmd(ADC1, ENABLE);

  ADC_ResetCalibration(ADC1);
  while(ADC_GetResetCalibrationStatus(ADC1));

  ADC_StartCalibration(ADC1);
  while(ADC_GetCalibrationStatus(ADC1));
}

void USART1_Configuration(void)
{
  GPIO_InitTypeDef GPIO_InitStructure;
  USART_InitTypeDef USART_InitStructure;

  RCC_APB2PeriphClockCmd(RCC_APB2Periph_USART1 | RCC_APB2Periph_GPIOA, ENABLE);

  GPIO_InitStructure.GPIO_Pin = GPIO_Pin_9;
  GPIO_InitStructure.GPIO_Mode = GPIO_Mode_AF_PP;
  GPIO_InitStructure.GPIO_Speed = GPIO_Speed_50MHz;
  GPIO_Init(GPIOA, &GPIO_InitStructure);

  GPIO_InitStructure.GPIO_Pin = GPIO_Pin_10;
  GPIO_InitStructure.GPIO_Mode = GPIO_Mode_IN_FLOATING;
  GPIO_Init(GPIOA, &GPIO_InitStructure);

  USART_InitStructure.USART_BaudRate = 115200;
  USART_InitStructure.USART_WordLength = USART_WordLength_8b;
  USART_InitStructure.USART_StopBits = USART_StopBits_1;
  USART_InitStructure.USART_Parity = USART_Parity_No;
  USART_InitStructure.USART_HardwareFlowControl = USART_HardwareFlowControl_None;
  USART_InitStructure.USART_Mode = USART_Mode_Rx | USART_Mode_Tx;
  USART_Init(USART1, &USART_InitStructure);

  USART_Cmd(USART1, ENABLE);
}

void Delay(__IO uint32_t nCount)
{
  for(; nCount != 0; nCount--);
}

void find_R_peaks(float voltage)
{
  if (voltage > 1.5 && i > 0 && i < 10 && (R_peaks[i-1] < 100 || (i > 1 && R_peaks[i-1] - R_peaks[i-2] > 20))) {
    R_peaks[i] = i * 360;
    i++;
  }
  else if (voltage > 1.5 && i == 0) {
    R_peaks[0] = 0;
    i++;
  }
  else if (i == 10) {
    for (int j = 0; j < 9; j++) {
      R_peaks[j] = R_peaks[j+1];
    }
    R_peaks[9] = i * 360;
  }
}

该程序使用一个简单的阈值来检测R峰，并计算R峰之间的时间间隔以计算心率。R峰被定义为心电信号的最大值，并且V峰和P峰被省略了。由于该算法对于干扰敏感，并且可能会出现误报，因此需要进行进一步的优化和测试。