计步和方向传感器组合, 实现记录人行走的轨迹.zip

package life.step; import android.content.Context; import android.hardware.Sensor; import android.hardware.SensorEvent; import android.hardware.SensorManager; import android.util.Log; import java.util.Timer; import java.util.TimerTask; /** * 加速度传感器 */ public class StepSensorAcceleration extends StepSensorBase { private final String TAG = "StepSensorAcceleration"; //存放三轴数据 final int valueNum = 5; //用于存放计算阈值的波峰波谷差值 float[] tempValue = new float[valueNum]; int tempCount = 0; //是否上升的标志位 boolean isDirectionUp = false; //持续上升次数 int continueUpCount = 0; //上一点的持续上升的次数，为了记录波峰的上升次数 int continueUpFormerCount = 0; //上一点的状态，上升还是下降 boolean lastStatus = false; //波峰值 float peakOfWave = 0; //波谷值 float valleyOfWave = 0; //此次波峰的时间 long timeOfThisPeak = 0; //上次波峰的时间 long timeOfLastPeak = 0; //当前的时间 long timeOfNow = 0; //当前传感器的值 float gravityNew = 0; //上次传感器的值 float gravityOld = 0; //动态阈值需要动态的数据，这个值用于这些动态数据的阈值 final float initialValue = (float) 1.7; //初始阈值 float ThreadValue = (float) 2.0; //初始范围 float minValue = 11f; float maxValue = 19.6f; /** * 0-准备计时 1-计时中 2-正常计步中 */ private int CountTimeState = 0; public static int TEMP_STEP = 0; private int lastStep = -1; //用x、y、z轴三个维度算出的平均值 public static float average = 0; private Timer timer; // 倒计时3.5秒，3.5秒内不会显示计步，用于屏蔽细微波动 private long duration = 3500; private TimeCount time; public StepSensorAcceleration(Context context, StepCallBack stepCallBack) { super(context, stepCallBack); } @Override protected void registerStepListener() { // 注册加速度传感器 isAvailable = sensorManager.registerListener(this, sensorManager.getDefaultSensor(Sensor.TYPE_ACCELEROMETER), SensorManager.SENSOR_DELAY_GAME); if (isAvailable) { Log.i(TAG, "加速度传感器可用！"); } else { Log.i(TAG, "加速度传感器不可用！"); } } @Override public void unregisterStep() { sensorManager.unregisterListener(this); } public void onAccuracyChanged(Sensor arg0, int arg1) { } public void onSensorChanged(SensorEvent event) { Sensor sensor = event.sensor; synchronized (this) { if (sensor.getType() == Sensor.TYPE_ACCELEROMETER) { calc_step(event); } } } synchronized private void calc_step(SensorEvent event) { average = (float) Math.sqrt(Math.pow(event.values[0], 2) + Math.pow(event.values[1], 2) + Math.pow(event.values[2], 2)); detectorNewStep(average); } /* * 检测步子，并开始计步 * 1.传入sersor中的数据 * 2.如果检测到了波峰，并且符合时间差以及阈值的条件，则判定为1步 * 3.符合时间差条件，波峰波谷差值大于initialValue，则将该差值纳入阈值的计算中 * */ public void detectorNewStep(float values) { if (gravityOld == 0) { gravityOld = values; } else { if (DetectorPeak(values, gravityOld)) { timeOfLastPeak = timeOfThisPeak; timeOfNow = System.currentTimeMillis(); if (timeOfNow - timeOfLastPeak >= 200 && (peakOfWave - valleyOfWave >= ThreadValue) && (timeOfNow - timeOfLastPeak) <= 2000) { timeOfThisPeak = timeOfNow; //更新界面的处理，不涉及到算法 preStep(); } if (timeOfNow - timeOfLastPeak >= 200 && (peakOfWave - valleyOfWave >= initialValue)) { timeOfThisPeak = timeOfNow; ThreadValue = Peak_Valley_Thread(peakOfWave - valleyOfWave); } } } gravityOld = values; } private void preStep() { // if (CountTimeState == 0) { // // 开启计时器 // time = new TimeCount(duration, 700); // time.start(); // CountTimeState = 1; // Log.v(TAG, "开启计时器"); // } else if (CountTimeState == 1) { // TEMP_STEP++; // Log.v(TAG, "计步中 TEMP_STEP:" + TEMP_STEP); // } else if (CountTimeState == 2) { StepSensorBase.CURRENT_STEP++; // if (stepCallBack != null) { stepCallBack.Step(StepSensorBase.CURRENT_STEP); // } // } } /* * 检测波峰 * 以下四个条件判断为波峰： * 1.目前点为下降的趋势：isDirectionUp为false * 2.之前的点为上升的趋势：lastStatus为true * 3.到波峰为止，持续上升大于等于2次 * 4.波峰值大于1.2g,小于2g * 记录波谷值 * 1.观察波形图，可以发现在出现步子的地方，波谷的下一个就是波峰，有比较明显的特征以及差值 * 2.所以要记录每次的波谷值，为了和下次的波峰做对比 * */ public boolean DetectorPeak(float newValue, float oldValue) { lastStatus = isDirectionUp; if (newValue >= oldValue) { isDirectionUp = true; continueUpCount++; } else { continueUpFormerCount = continueUpCount; continueUpCount = 0; isDirectionUp = false; } // Log.v(TAG, "oldValue:" + oldValue); if (!isDirectionUp && lastStatus && (continueUpFormerCount >= 2 && (oldValue >= minValue && oldValue < maxValue))) { peakOfWave = oldValue; return true; } else if (!lastStatus && isDirectionUp) { valleyOfWave = oldValue; return false; } else { return false; } } /* * 阈值的计算 * 1.通过波峰波谷的差值计算阈值 * 2.记录4个值，存入tempValue[]数组中 * 3.在将数组传入函数averageValue中计算阈值 * */ public float Peak_Valley_Thread(float value) { float tempThread = ThreadValue; if (tempCount < valueNum) { tempValue[tempCount] = value; tempCount++; } else { tempThread = averageValue(tempValue, valueNum); System.arraycopy(tempValue, 1, tempValue, 0, valueNum - 1); tempValue[valueNum - 1] = value; } return tempThread; } /* * 梯度化阈值 * 1.计算数组的均值 * 2.通过均值将阈值梯度化在一个范围里 * */ public float averageValue(float[] value, int n) { float ave = 0; for (int i = 0; i < n; i++) { ave += value[i]; } ave = ave / valueNum; if (ave >= 8) { // Log.v(TAG, "超过8"); ave = (float) 4.3; } else if (ave >= 7) { // Log.v(TAG, "7-8"); ave = (float) 3.3; } else if (ave >= 4) { // Log.v(TAG, "4-7"); ave = (float) 2.3; } else if (ave >= 3) { // Log.v(TAG, "3-4"); ave = (float) 2.0; } else { // Log.v(TAG, "else"); ave = (float) 1.7; } return ave; } class TimeCount extends CountDownTimer { public TimeCount(long millisInFuture, long countDownInterval) { super(millisInFuture, countDownInterval); } @Override public void onFinish() { // 如果计时