用 python 编写代码，从绿色通道帧的视频中提取心率

问：

这是我的代码，但心率值不准确。 请帮助我如何改进它。 正常 BPM 应为 60-100。 我试图通过获取绿色通道来提取 hr，然后计算它的 fft 频率， 然后找到峰值并过滤它们，然后计算峰值，然后将其转换为 BPM。 当然，这种方式基于一些文章，现在我想实现它。

import numpy as np
from scipy.signal import find_peaks

class ExtractHeartRate:
   def __init__(self, green_channel, timer):
    self.green_channel = green_channel  # Green channel of the frame
    self.timer = timer
    self.heart_rate = 0

   def calc_hr_process(self):
    # Perform FFT on the Green Channel
    fft_result = np.fft.fft(self.green_channel)
    fft_result = np.abs(fft_result).flatten()
    fft_freq = np.fft.fftfreq(len(fft_result))

    # Locate peaks in the necessary frequency range
    peaks, _ = find_peaks(fft_result, height=0, threshold=0)

    # Filter peaks within the necessary frequency range
    valid_peaks = peaks[(fft_freq[peaks] >= 0.48) & (fft_freq[peaks] <= 4)]

    # Count the peaks within a set time range
    elapsed_time = self.timer.elapsed() / 1000  # Elapsed time in seconds
    if elapsed_time > 0:
        # Calculate the peak count within the set time range
        peak_count = len(valid_peaks)

        # Calculate the heart rate
        heart_rate = peak_count * 60 / elapsed_time  # Convert to BPM using elapsed time
        self.heart_rate = round(heart_rate)
    else:
        self.heart_rate = 0
    return self.heart_rate