예제 #1
0
 public override void Start()
 {
     AccelerometerFeatures.Start();
     GryoFeatures.Start();
     EMGFeatures.Start();
 }
예제 #2
0
        static void MyoGymFusion()
        {
            var Classifier = new MulticlassSupportVectorMachineClassifier();

            Classifier.Load("C:\\Users\\riz\\Desktop\\MyoGYm\\MyoGym_SVM1");
            var Features = new DataInFeatureOut(new MQTTReader <double[]>("/i5/myo/full", new SlidingWindow <double[]>(200, 0)), new IFeature[] {
                new HjorthParameters(8, 9, 10),
                new StandardDeviation(8, 9, 10),
                new Mean(8, 9, 10),
                new Max(8, 9, 10),
                new Min(8, 9, 10),
                new Percentile(5, 8, 9, 10),
                new Percentile(10, 8, 9, 10),
                new Percentile(25, 8, 9, 10),
                new Percentile(50, 8, 9, 10),
                new Percentile(75, 8, 9, 10),
                new Percentile(90, 8, 9, 10),
                new Percentile(95, 8, 9, 10),
                new ZeroCrossing(8, 9, 10),
                new MeanCrossing(8, 9, 10),
                new Entropy(8, 9, 10),
                new Correlation(9, 10),
                new Correlation(9, 11),
                new Correlation(10, 11),

                new HjorthParameters(11, 12, 13),
                new StandardDeviation(11, 12, 13),
                new Mean(11, 12, 13),
                new Max(11, 12, 13),
                new Min(11, 12, 13),
                new Percentile(5, 11, 12, 13),
                new Percentile(10, 11, 12, 13),
                new Percentile(25, 11, 12, 13),
                new Percentile(50, 11, 12, 13),
                new Percentile(75, 11, 12, 13),
                new Percentile(90, 11, 12, 13),
                new Percentile(95, 11, 12, 13),
                new ZeroCrossing(11, 12, 13),
                new MeanCrossing(11, 12, 13),
                new Entropy(11, 12, 13),

                new StandardDeviation(0, 1, 2, 3, 4, 5, 6, 7),
                new Mean(0, 1, 2, 3, 4, 5, 6, 7),
                new Max(0, 1, 2, 3, 4, 5, 6, 7),
                new Min(0, 1, 2, 3, 4, 5, 6, 7),
                new Percentile(5, 0, 1, 2, 3, 4, 5, 6, 7),
                new Percentile(10, 0, 1, 2, 3, 4, 5, 6, 7),
                new Percentile(25, 0, 1, 2, 3, 4, 5, 6, 7),
                new Percentile(50, 0, 1, 2, 3, 4, 5, 6, 7),
                new Percentile(75, 0, 1, 2, 3, 4, 5, 6, 7),
                new Percentile(90, 0, 1, 2, 3, 4, 5, 6, 7),
                new Percentile(95, 0, 1, 2, 3, 4, 5, 6, 7),

                new SumLargerThan(25, 0, 1, 2, 3, 4, 5, 6, 7),
                new SumLargerThan(50, 0, 1, 2, 3, 4, 5, 6, 7),
                new SumLargerThan(100, 0, 1, 2, 3, 4, 5, 6, 7)
            });
            var Decision = new FeaturesInDecisionOut(new List <IFusionStrategy>()
            {
                Features
            }, Classifier);

            Decision.OnFusionFinished = (decision) =>
            {
                Console.WriteLine(decision);
            };

            Features.Start();
        }
예제 #3
0
 public override void Start()
 {
     Feature1.Start();
 }
예제 #4
0
 public override void Start()
 {
     AllFeatures.Start();
 }