Nitro Powered Motorcycles

    pedometer

    0.0.5 • Public • Published

    node-pedometer

    Pedometer implementation for node.js

    Build status

    Build Status Coverage Status

    Notes

    Uses a windowed average peak counting algorithm to perform low-cost step detection.
    
    Assumes all input data to be 2D arrays
    
    [[x1, y1, z1], [x2, y2, z2],...]
    [[pitch1, roll1, yaw1]. [pitch2, roll2, yaw2],... ] (in Radians)
    

    Installation

    npm install pedometer --save
    

    Usage

    var pedometer = require('pedometer').pedometer;
    var steps=pedometer(accelerometerData,attitudeData,samplingrate,options);
    

    accelerometerdata is a time series of 3D acceleration vectors in m/s^2 [[x1, y1, z1], [x2, y2, z2],...]

    attitudeData is a time series of 3D attitude vectors in radians [[pitch1, roll1, yaw1]. [pitch2, roll2, yaw2],... ]

    samplingrate is the number of samples per second. All tests were done with 100Hz

    options provides optional parameters. Default values are:

    options={
        windowSize:1, //Length of window in seconds
        minPeak:2, //minimum magnitude of a steps largest positive peak
        maxPeak:8, //maximum magnitude of a steps largest positive peak
        minStepTime: 0.3, //minimum time in seconds between two steps
        peakThreshold: 0.5, //minimum ratio of the current window's maximum to be considered a step
        minConsecutiveSteps: 3, //minimum number of consecutive steps to be counted
        maxStepTime: 0.8, //maximum time between two steps to be considered consecutive
        meanFilterSize: 1, //Amount of smoothing (Values <=1 disable the smoothing)
        debug:false //Enable output of debugging data in matlab/octave format
        }
    

    Returns an array of the indices in the input signal where steps occured

    See src/debug.js and test/test.js for more examples
    

    Example

    Before you run this, make sure to have installed the modules fs and csv-parse.

    var pedometer = require('pedometer').pedometer,
        fs = require('fs'),
        parse = require('csv-parse/lib/sync');
    
    //Function to load Data from csv file
    function loadData(filename){
        
        //Load file
        var data=fs.readFileSync(filename,'utf8');
        
        //parse CSV
        data=parse(data, {trim: true, auto_parse: true});
        
        //Store data in arrays
        var acc=[],att=[];
        for (var i=0;i<data.length;i++){
            acc[i]=data[i].slice(0,3);
            att[i]=[data[i][4], -data[i][5],data[i][3]];   //Attitude is adjusted to correctly match [ pitch, roll, yaw ]
        }
        
        //Return arrays
        return {acc:acc,att:att};
    }
       
    //Load first test case
    var data=loadData('node_modules/pedometer/test/DataWalking1.csv');      //You might need to adjust the path here
    
    //Define algorithm options (optional). All recommended default values here.
    var options={
                    windowSize:1, //Length of window in seconds
                    minPeak:2, //minimum magnitude of a steps largest positive peak
                    maxPeak:8, //maximum magnitude of a steps largest positive peak
                    minStepTime: 0.3, //minimum time in seconds between two steps
                    peakThreshold: 0.5, //minimum ratio of the current window's maximum to be considered a step
                    minConsecutiveSteps: 3, //minimum number of consecutive steps to be counted
                    maxStepTime: 0.8, //maximum time between two steps to be considered consecutive
                    meanFilterSize: 1, //Amount of smoothing (Values <=1 disable the smoothing)
                    debug:false //Enable output of debugging data in matlab/octave format
    };
            
    //Perform step detection. Leaving away ,options here (recommended), will use the default settings as specified above.
    var steps=pedometer(data.acc,data.att,100,options);
    
    //Print number of detected steps
    console.log("The algorithm detected "+steps.length+" steps.");
    

    Output:

    The algorithm detected 116 steps.
    

    Test

    npm test
    

    Returns:

        Detect steps in acceleration signal
      The algorithm detected 116 steps.
          ✓ Test 1 - Signal of walk 1 (186ms)
      The algorithm detected 292 steps.
          ✓ Test 2 - Signal of walk 2 (442ms)
      The algorithm detected 25 steps.
          ✓ Test 3 - Signal of walk 3 (54ms)
      The algorithm detected 27 steps.
          ✓ Test 4 - Signal of walk 4 (47ms)
      The algorithm detected 483 steps.
          ✓ Test 5 - Signal of walk 5 (732ms)
      The algorithm detected 16 steps.
          ✓ Test 6 - Signal of not walking 1 (558ms)
      The algorithm detected 10 steps.
          ✓ Test 7 - Signal of not walking 2 (130ms)
      The algorithm detected 28 steps.
          ✓ Test 8 - Signal of not walking 3 (787ms)
      The algorithm detected 0 steps.
          ✓ Test 9 - Signal of not walking 4 (891ms)
      The algorithm detected 23 steps.
          ✓ Test 10 - Signal of not walking 5 (235ms)
      The algorithm detected 68 steps.
          ✓ Test 11 - Signal of mixed action 1 (751ms)
      The algorithm detected 46 steps.
          ✓ Test 12 - Signal of mixed action 2 (792ms)
      
      
        12 passing (6s)
    

    License

    MIT License

    Copyright (c) 2016 Maximilian Bügler

    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 THE AUTHORS OR COPYRIGHT HOLDERS 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.

    Install

    npm i pedometer

    DownloadsWeekly Downloads

    4

    Version

    0.0.5

    License

    MIT

    Last publish

    Collaborators

    • maximilianbuegler