Android PPG 数据处理: 标准差和 Savitzky-Golay 滤波

{ "title": "Android PPG 数据处理: 标准差和 Savitzky-Golay 滤波", "description": "本代码片段展示了如何在 Android 中使用 Java 对 PPG 数据进行标准差计算和 Savitzky-Golay 滤波，并说明了代码的步骤和函数功能。", "keywords": "Android, PPG, 数据处理, 标准差, Savitzky-Golay 滤波, Java", "content": "double std_total = calculateStandardDeviation(ppg_data);

if (std_total < 100) { return -3; }

double[] filtered_data = savgolFilter(ppg_data, 51, 2);

// Continue with the rest of the code

// Function to calculate standard deviation public double calculateStandardDeviation(double[] data) { double mean = calculateMean(data); double sum = 0; for (int i = 0; i < data.length; i++) { sum += Math.pow(data[i] - mean, 2); } double variance = sum / data.length; return Math.sqrt(variance); }

// Function to perform Savitzky-Golay filtering public double[] savgolFilter(double[] data, int windowSize, int polynomialOrder) { double[] filteredData = new double[data.length]; int halfWindowSize = windowSize / 2; for (int i = halfWindowSize; i < data.length - halfWindowSize; i++) { double sum = 0; for (int j = -halfWindowSize; j <= halfWindowSize; j++) { sum += data[i + j] * calculateSavitzkyGolayCoeff(j, windowSize, polynomialOrder); } filteredData[i] = sum; } return filteredData; }

// Function to calculate Savitzky-Golay coefficients public double calculateSavitzkyGolayCoeff(int index, int windowSize, int polynomialOrder) { int m = windowSize / 2; double sum = 0; for (int k = 0; k <= polynomialOrder; k++) { sum += ((2 * k + 1) / factorial(k)) * polynomialValue(index, k, m, windowSize); } return sum; }

// Function to calculate factorial public int factorial(int n) { if (n == 0 || n == 1) { return 1; } int result = 1; for (int i = 2; i <= n; i++) { result *= i; } return result; }

// Function to calculate polynomial value public double polynomialValue(int index, int k, int m, int windowSize) { double sum = 0; for (int i = 0; i <= k; i++) { sum += Math.pow(index, i); } for (int i = 0; i <= k; i++) { sum *= (windowSize - 1) / Math.pow(m, i); } return sum; }