VitalDSP

Getting Started:

  • Getting Started with VitalDSP
  • What is VitalDSP?
  • Installation
    • Prerequisites
    • Installation Methods
    • Verify Installation
  • Quick Start
    • Comprehensive Signal Analysis Example
    • Web Application
  • Core Modules Overview
    • Data Synthesis
    • Signal Filtering and Processing
    • Physiological Features
    • Respiratory Analysis
    • Advanced Computation
  • Working with Real Data
    • Loading Data
    • Preprocessing
    • Feature Extraction Pipeline
  • Web Application Features
    • Interactive Analysis
    • API Integration
  • Explore More with Jupyter Notebooks
    • Notebooks
      • Health Report Analysis
        • Display the health analysis report
        • Save the health report as HTML file
        • Display the HTML file in the notebook
      • Synthetic Signal
        • Synthetic ECG Signal
        • Synthetic PPG Signal
        • Synthetic Respiratory Signal
      • Signal Filtering
        • Savgol Filter
        • Moving Average
        • Gaussian Filtering
        • Butterworth
        • Median
      • Advanced Filtering
        • Kalman Filter
        • Optimization-based filter
        • Gradient Descent Filter
        • Convolution-based filter
        • Attention-based filter
        • LMS Adaptive Filtering
      • Artifact Removal
        • Mean Subtraction
        • Baseline Correction
        • Wavelet Denoising
        • Adaptive Filtering
        • Notch Filter
        • PCA Artifact Removal
        • ICA Artifact Removal
      • Signal Quality Indices
        • Amplitude Variability SQI
        • Baseline Wander SQI
        • Zero-Crossing SQI
        • Entropy SQI
        • Skewness
        • Kurtosis SQI
        • Peak-to-Peak Amplitude SQI
        • Signal-to-Noise Ratio (SNR) SQI
        • Energy SQI
        • Waveform Similarity SQI
      • Feature Engineering
        • Morphology Features
      • Signal Transformations
        • Discrete Cosine Transformations
        • Fourier Transform
        • Hilbert Transform
      • Vital Transform
  • Best Practices
    • Performance Optimization
    • Data Quality
    • Error Handling
  • Support and Community
    • Getting Help
    • Contributing
  • Next Steps

Tutorials:

  • Tutorials
  • Tutorial Overview
  • Tutorial 1: Basic Signal Processing
  • Tutorial 2: Heart Rate Variability Analysis
  • Tutorial 3: Respiratory Signal Analysis
  • Tutorial 4: Web Application Usage
  • Tutorial 5: Machine Learning Integration
  • Best Practices
  • Troubleshooting Common Issues
  • Next Steps
  • Tutorial 6: EMD and Advanced Signal Decomposition
  • Tutorial 7: Sleep Apnea Detection and Respiratory Pattern Analysis
  • Tutorial 8: ECG-PPG Synchronization and Pulse Transit Time Analysis

Examples:

  • Examples
  • Example Categories
  • Example 1: ECG Analysis for Clinical Research
  • Example 2: PPG Analysis for Hemodynamic Studies
  • Example 3: Real-Time Vital Signs Monitoring
  • Example 4: Wearable Device Integration
  • Best Practices for Examples
  • Example 5: Advanced Multi-Scale Entropy Analysis
  • Example 6: Comprehensive Health Monitoring System
  • Example 7: Cross-Signal Synchronization Analysis
  • Example 8: Comprehensive Physiological Feature Extraction
  • Example 9: Machine Learning for Physiological Signal Analysis

Core Library Modules:

  • Preprocessing
    • Noise Reduction
      • Examples:
    • Signal Preprocessing
      • Examples:
  • Filtering
    • Overview
      • Key Features
    • Signal Filtering
      • Key Capabilities
      • Filter Families
      • Clinical Applications
        • Examples:
    • Artifact Removal
      • Key Capabilities
      • Advanced Techniques
      • Clinical Applications
        • Examples:
    • Advanced Signal Filtering
      • Key Capabilities
      • Advanced Techniques
      • Clinical Applications
      • Performance Optimization
        • Examples:
  • Transforms
    • Chroma STFT
      • Examples:
    • DCT Wavelet Fusion
      • Examples:
    • Discrete Cosine Transform
      • Examples:
    • Event Related Potential
      • Examples:
    • Fourier Transform
      • Examples:
    • Hilbert Transform
      • Examples:
    • MFCC (Mel Frequency Cepstral Coefficients)
      • Examples:
    • PCA and ICA Signal Decomposition
      • Examples:
    • STFT (Short-Time Fourier Transform)
      • Examples:
    • Time-Frequency Representation
      • Examples:
    • Vital Transformation
      • Examples:
    • Wavelet FFT Fusion
      • Examples:
    • Wavelet Transform
      • Examples:
  • Physiological Features
  • Overview
    • Clinical Applications
    • Key Features
  • Clinical Interpretation Guidelines
    • ECG Signal Analysis
    • PPG Signal Analysis
  • Time Domain Features
    • Time Domain Features
      • Examples:
    • Beat-to-Beat Analysis
      • Examples:
  • Frequency Domain Features
    • Frequency Domain Features
      • Examples:
  • HRV Analysis
    • HRV Features
      • Examples:
  • Nonlinear Analysis
    • Nonlinear Features
      • Examples:
  • Advanced Nonlinear Features
    • Multi-Scale Entropy Analysis
      • Advanced Entropy Analysis Module
        • Clinical Applications:
        • Mathematical Background:
        • References:
    • Symbolic Dynamics Analysis
      • Symbolic Dynamics Analysis Module
        • Implemented Methods:
        • Clinical Applications:
        • Mathematical Background:
        • References:
        • Examples:
    • Transfer Entropy Analysis
      • Transfer Entropy Module for Coupling Analysis
        • Implemented Methods:
        • Clinical Applications:
        • Mathematical Background:
        • References:
    • Advanced Features Guide
  • Morphological Analysis
    • Waveform Morphology
      • Examples:
  • Cross-Signal Analysis
    • Cross Correlation Analysis
      • Examples:
    • Cross-Signal Analysis
      • Examples:
    • Coherence Analysis
      • Examples:
  • Signal Processing Features
    • Signal Segmentation
      • Examples:
    • Signal Power Analysis
      • Examples:
    • Energy Analysis
      • Examples:
    • Envelope Detection
      • Examples:
    • Trend Analysis
      • Examples:
    • Signal Change Detection
      • Examples:
      • Ensemble-Based Feature Extraction
        • Examples:
      • Energy Analysis
        • Examples:
      • Envelope Detection
        • Examples:
      • Frequency Domain
        • Examples:
      • Nonlinear Analysis
        • Examples:
      • Signal Change Detection
        • Examples:
      • Signal Power Analysis
        • Examples:
      • Signal Segmentation
        • Examples:
      • Time Domain Analysis
        • Examples:
      • Trend Analysis
        • Examples:
      • Waveform Analysis
        • Examples:
  • Respiratory Analysis
  • Overview
  • Main Respiratory Analysis
    • Respiratory Analysis
      • Examples:
      • Estimation of Respiratory Rate (RR)
        • Examples:
        • Examples:
        • Examples:
        • Examples:
      • Multimodal Fusion
        • Examples:
        • Examples:
        • Examples:
      • Sleep Apnea Detection
        • Examples:
        • Examples:
  • Signal Quality Assessment
    • Adaptive SNR Estimation
      • Examples:
    • Artifact Detection and Removal
      • Examples:
    • Blind Source Separation
      • Examples:
    • Multi-Modal Artifact Detection
      • Examples:
    • SNR Computation
      • Examples:
    • Signal Quality Index
      • Examples:
    • Signal Quality
      • Examples:
  • Advanced Computation
  • Overview
  • Machine Learning and AI
    • Neural Network Filtering
      • Examples:
    • Reinforcement Learning Filter
      • Examples:
  • Anomaly Detection
    • Anomaly Detection
      • Examples:
    • Real-Time Anomaly Detection
      • Examples:
  • Bayesian Analysis
    • Bayesian Analysis
      • Classes:
      • Examples:
      • Notes:
      • Empirical Mode Decomposition (EMD)
        • Examples:
      • Generative Signal Synthesis
        • Examples:
      • Harmonic/Percussive Separation
        • Examples:
      • Kalman Filter
        • Examples:
      • Multimodal Fusion
        • Examples:
      • Neural Network Filtering
        • Examples:
      • Non-Linear Analysis
        • Examples:
      • Pitch Shift
        • Examples:
      • Real-Time Anomaly Detection
        • Examples:
      • Reinforcement Learning Filter
        • Examples:
      • Sparse Signal Processing
        • Examples:
  • Feature Engineering
  • Overview
  • Clinical Feature Interpretation
    • ECG Morphological Features
    • PPG Morphological Features
    • Heart Rate Variability Features
  • Morphological Features
    • Morphology Features
      • Examples:
  • Autonomic Features
    • ECG Autonomic Features
      • Examples:
    • PPG Autonomic Features
      • Examples:
  • Synchronization Features
    • ECG-PPG Synchronization Features
  • Light Source Features
    • PPG Light Features
      • Examples:
  • Usage Examples
    • Basic Feature Extraction
    • Multi-Signal Analysis
    • PPG Light Analysis
  • Utils
  • Overview
  • Peak Detection
    • Peak Detection
      • Examples:
  • Data Synthesis
    • Synthesize Data
      • Examples:
  • Normalization and Scaling
    • Normalization
      • Examples:
    • Scaler
      • Examples:
  • Data Interpolation
    • Interpolations
      • Examples:
  • Wavelet Functions
    • Mother Wavelets
      • Examples:
  • Machine Learning Utilities
    • Attention Weights
      • Examples:
    • Loss Functions
      • Examples:
    • Convolutional Kernels
      • Examples:
  • Common Utilities
    • Common Utilities
      • Examples:
  • Usage Examples
    • Peak Detection
    • Data Synthesis
    • Normalization
    • Interpolation
      • Convolutional Kernels
        • Examples:
      • Peak Detection
        • Examples:
      • Loss Functions
        • Examples:
      • Mother Wavelets
        • Examples:
      • Normalization
        • Examples:
      • Scaler
        • Examples:
      • Synthesize Data
        • Examples:

Advanced Features:

  • Advanced Features Guide
    • Overview
      • Modules Covered
    • Quick Start
      • Installation
      • Basic Usage Examples
    • Multi-Scale Entropy Analysis
      • Theory and Mathematical Background
      • Class API
        • MultiScaleEntropy
      • Clinical Applications
      • Performance Optimization
    • Symbolic Dynamics Analysis
      • Theory and Mathematical Background
      • Class API
        • SymbolicDynamics
      • Clinical Applications
      • Parameter Selection Guide
    • Transfer Entropy Analysis
      • Theory and Mathematical Background
      • Class API
        • TransferEntropy
      • Clinical Applications
      • Parameter Selection Guide
      • Interpretation Guidelines
    • Complete Clinical Workflow
      • Comprehensive HRV Analysis
    • Performance and Optimization
      • Computational Complexity Summary
      • Memory Requirements
      • Optimization Tips
      • Benchmarking Results
    • References
      • Multi-Scale Entropy
      • Symbolic Dynamics
      • Transfer Entropy
      • Clinical Applications
    • Additional Resources
    • Support and Community
  • Large Data Processing Architecture & Optimization Guide
  • Overview
  • Phase 1: Core Infrastructure Optimization
    • Key Components
    • Phase 1 Performance Improvements
  • Phase 2: Pipeline Integration Optimization
    • Key Components
    • Phase 2 Performance Improvements
  • Advanced Features
  • Performance Benchmarks
  • Best Practices
  • Migration Guide
  • Troubleshooting
  • Support and Resources
  • Large Data Processing Architecture
  • Architecture Overview
  • Design Principles
  • Phase 1: Core Infrastructure
    • Key Components
    • Phase 1 Architecture Benefits
  • Phase 2: Pipeline Integration
    • Key Components
    • Phase 2 Architecture Benefits
  • Data Processing Pipeline
  • Memory Management Architecture
  • Error Recovery Architecture
  • Caching Architecture
  • Checkpointing Architecture
  • Performance Characteristics
  • Configuration Architecture
  • Integration Guide
  • Best Practices
  • Future Enhancements

Web Application:

  • VitalDSP Web Application
  • Overview
  • Installation and Setup
  • Main Features
    • Application Screens Overview
    • Signal Upload and Management
    • Signal Processing
    • Physiological Analysis
  • Interactive Visualization
  • Detailed Screen Descriptions
    • Filtering Screen
    • Physiological Analysis Screen
    • Frequency Domain Analysis Screen
    • Respiratory Analysis Screen
  • Updated Workflow
    • Signal Upload and Processing
    • Key Improvements
  • Export and Reporting
  • API Integration
  • Data Management
    • Global Data Storage
    • Signal Type Detection
  • Configuration
  • Advanced Features
    • Custom Analysis Pipelines
    • Batch Processing
  • Troubleshooting
    • Common Issues and Solutions
  • Support and Documentation

Jupyter Notebooks:

  • Notebooks
    • Health Report Analysis
      • Display the health analysis report
      • Save the health report as HTML file
      • Display the HTML file in the notebook
    • Synthetic Signal
      • Synthetic ECG Signal
      • Synthetic PPG Signal
      • Synthetic Respiratory Signal
    • Signal Filtering
      • Savgol Filter
      • Moving Average
      • Gaussian Filtering
      • Butterworth
      • Median
    • Advanced Filtering
      • Kalman Filter
      • Optimization-based filter
      • Gradient Descent Filter
      • Convolution-based filter
      • Attention-based filter
      • LMS Adaptive Filtering
    • Artifact Removal
      • Mean Subtraction
      • Baseline Correction
      • Wavelet Denoising
      • Adaptive Filtering
      • Notch Filter
      • PCA Artifact Removal
      • ICA Artifact Removal
    • Signal Quality Indices
      • Amplitude Variability SQI
      • Baseline Wander SQI
      • Zero-Crossing SQI
      • Entropy SQI
      • Skewness
      • Kurtosis SQI
      • Peak-to-Peak Amplitude SQI
      • Signal-to-Noise Ratio (SNR) SQI
      • Energy SQI
      • Waveform Similarity SQI
    • Feature Engineering
      • Morphology Features
    • Signal Transformations
      • Discrete Cosine Transformations
      • Fourier Transform
      • Hilbert Transform
    • Vital Transform

API Reference:

  • API Reference
  • Core Library
    • Filtering Module
      • Signal Filtering
        • Examples:
        • BandpassFilter
        • SignalFiltering
      • Artifact Removal
        • Examples:
        • ArtifactRemoval
      • Advanced Signal Filtering
        • Examples:
        • AdvancedSignalFiltering
  • Physiological Features Module
    • Examples:
    • TimeDomainFeatures
      • TimeDomainFeatures.nn_intervals
      • TimeDomainFeatures.compute_sdnn()
      • TimeDomainFeatures.compute_rmssd()
      • TimeDomainFeatures.compute_nn50()
      • TimeDomainFeatures.compute_pnn50()
      • TimeDomainFeatures.compute_median_nn()
      • TimeDomainFeatures.compute_iqr_nn()
      • TimeDomainFeatures.compute_mean_nn()
      • TimeDomainFeatures.compute_std_nn()
      • TimeDomainFeatures.compute_pnn20()
      • TimeDomainFeatures.compute_nn20()
      • TimeDomainFeatures.compute_cvnn()
      • TimeDomainFeatures.compute_hrv_triangular_index()
      • TimeDomainFeatures.compute_tinn()
      • TimeDomainFeatures.compute_sdsd()
      • TimeDomainFeatures.compute_cvnn()
      • TimeDomainFeatures.compute_hrv_triangular_index()
      • TimeDomainFeatures.compute_iqr_nn()
      • TimeDomainFeatures.compute_mean_nn()
      • TimeDomainFeatures.compute_median_nn()
      • TimeDomainFeatures.compute_nn50()
      • TimeDomainFeatures.compute_pnn20()
      • TimeDomainFeatures.compute_pnn50()
      • TimeDomainFeatures.compute_rmssd()
      • TimeDomainFeatures.compute_sdnn()
      • TimeDomainFeatures.compute_sdsd()
      • TimeDomainFeatures.compute_std_nn()
      • TimeDomainFeatures.compute_tinn()
    • Examples:
    • FrequencyDomainFeatures
      • FrequencyDomainFeatures.nn_intervals
      • FrequencyDomainFeatures.fs
      • FrequencyDomainFeatures.compute_psd()
      • FrequencyDomainFeatures.compute_lf()
      • FrequencyDomainFeatures.compute_hf()
      • FrequencyDomainFeatures.compute_lf_hf_ratio()
      • FrequencyDomainFeatures.compute_ulf()
      • FrequencyDomainFeatures.compute_vlf()
      • FrequencyDomainFeatures.compute_total_power()
      • FrequencyDomainFeatures.compute_lfnu()
      • FrequencyDomainFeatures.compute_hfnu()
      • FrequencyDomainFeatures.compute_hf()
      • FrequencyDomainFeatures.compute_hfnu()
      • FrequencyDomainFeatures.compute_lf()
      • FrequencyDomainFeatures.compute_lf_hf_ratio()
      • FrequencyDomainFeatures.compute_lfnu()
      • FrequencyDomainFeatures.compute_psd()
      • FrequencyDomainFeatures.compute_total_power()
      • FrequencyDomainFeatures.compute_ulf()
      • FrequencyDomainFeatures.compute_vlf()
    • Examples:
    • HRVFeatures
      • HRVFeatures.nn_intervals
      • HRVFeatures.signal
      • HRVFeatures.fs
      • HRVFeatures.compute_all_features()
      • HRVFeatures.compute_all_features()
    • Examples:
    • BeatToBeatAnalysis
      • BeatToBeatAnalysis.signal
      • BeatToBeatAnalysis.r_peaks
      • BeatToBeatAnalysis.fs
      • BeatToBeatAnalysis.signal_type
      • BeatToBeatAnalysis.compute_hr()
      • BeatToBeatAnalysis.compute_mean_rr()
      • BeatToBeatAnalysis.compute_pnn50()
      • BeatToBeatAnalysis.compute_rmssd()
      • BeatToBeatAnalysis.compute_rr_intervals()
      • BeatToBeatAnalysis.compute_sdnn()
      • BeatToBeatAnalysis.detect_arrhythmias()
    • Examples:
    • NonlinearFeatures
      • NonlinearFeatures.signal
      • NonlinearFeatures.fs
      • NonlinearFeatures.compute_sample_entropy()
      • NonlinearFeatures.compute_approximate_entropy()
      • NonlinearFeatures.compute_fractal_dimension()
      • NonlinearFeatures.compute_lyapunov_exponent()
      • NonlinearFeatures.compute_dfa()
      • NonlinearFeatures.compute_poincare_features()
      • NonlinearFeatures.compute_recurrence_features()
      • NonlinearFeatures.compute_approximate_entropy()
      • NonlinearFeatures.compute_dfa()
      • NonlinearFeatures.compute_fractal_dimension()
      • NonlinearFeatures.compute_lyapunov_exponent()
      • NonlinearFeatures.compute_poincare_features()
      • NonlinearFeatures.compute_recurrence_features()
      • NonlinearFeatures.compute_sample_entropy()
  • Waveform Morphology
    • Examples:
    • WaveformMorphology
      • WaveformMorphology.waveform
      • WaveformMorphology.fs
      • WaveformMorphology.signal_type
      • WaveformMorphology.simple_mode
      • WaveformMorphology.compute_amplitude()
      • WaveformMorphology.compute_curvature()
      • WaveformMorphology.compute_duration()
      • WaveformMorphology.compute_eeg_wavelet_features()
      • WaveformMorphology.compute_ppg_dicrotic_notch()
      • WaveformMorphology.compute_skewness()
      • WaveformMorphology.compute_slope()
      • WaveformMorphology.compute_volume()
      • WaveformMorphology.detect_diastolic_peak()
      • WaveformMorphology.detect_dicrotic_notches()
      • WaveformMorphology.detect_ecg_session()
      • WaveformMorphology.detect_p_peak()
      • WaveformMorphology.detect_ppg_session()
      • WaveformMorphology.detect_q_session()
      • WaveformMorphology.detect_q_valley()
      • WaveformMorphology.detect_qrs_session()
      • WaveformMorphology.detect_r_session()
      • WaveformMorphology.detect_s_session()
      • WaveformMorphology.detect_s_valley()
      • WaveformMorphology.detect_t_peak()
      • WaveformMorphology.detect_troughs()
      • WaveformMorphology.get_amplitude_variability()
      • WaveformMorphology.get_area()
      • WaveformMorphology.get_duration()
      • WaveformMorphology.get_heart_rate()
      • WaveformMorphology.get_peak_trend_slope()
      • WaveformMorphology.get_qrs_amplitude()
      • WaveformMorphology.get_signal_skewness()
      • WaveformMorphology.get_slope()
  • Respiratory Analysis Module
  • Respiratory Analysis
    • Examples:
    • RespiratoryAnalysis
      • RespiratoryAnalysis.signal
      • RespiratoryAnalysis.fs
      • RespiratoryAnalysis.compute_respiratory_rate()
      • RespiratoryAnalysis.compute_respiratory_rate_ensemble()
  • FFT-Based RR Estimation
    • Examples:
    • fft_based_rr()
  • Peak Detection RR Estimation
    • Examples:
    • peak_detection_rr()
  • Sleep Apnea Detection
    • Examples:
    • detect_apnea_amplitude()
  • Transforms Module
  • Fourier Transform
    • Examples:
    • FourierTransform
      • FourierTransform.compute_dft()
      • FourierTransform.compute_idft()
      • FourierTransform.filter_frequencies()
  • Wavelet Transform
    • Examples:
    • WaveletTransform
      • WaveletTransform.perform_inverse_wavelet_transform()
      • WaveletTransform.perform_wavelet_transform()
  • Discrete Cosine Transform
    • Examples:
    • DiscreteCosineTransform
      • DiscreteCosineTransform.compress_signal()
      • DiscreteCosineTransform.compute_dct()
      • DiscreteCosineTransform.compute_idct()
  • Hilbert Transform
    • Examples:
    • HilbertTransform
      • HilbertTransform.compute_hilbert()
      • HilbertTransform.envelope()
      • HilbertTransform.instantaneous_phase()
  • Advanced Computation Module
  • Anomaly Detection
    • Examples:
    • AnomalyDetection
      • AnomalyDetection.detect_anomalies()
  • Bayesian Analysis
    • Classes:
    • Examples:
    • Notes:
    • BayesianOptimization
      • BayesianOptimization.optimize()
      • BayesianOptimization.acquisition()
      • BayesianOptimization.propose_location()
      • BayesianOptimization.acquisition()
      • BayesianOptimization.optimize()
      • BayesianOptimization.propose_location()
    • GaussianProcess
      • GaussianProcess.predict()
      • GaussianProcess.update()
      • GaussianProcess.predict()
      • GaussianProcess.update()
  • Neural Network Filtering
    • Examples:
    • ConvolutionalNetwork
      • ConvolutionalNetwork.predict()
      • ConvolutionalNetwork.train()
    • FeedforwardNetwork
      • FeedforwardNetwork.predict()
      • FeedforwardNetwork.train()
    • NeuralNetworkFiltering
      • NeuralNetworkFiltering.nn_filter.train()
      • NeuralNetworkFiltering.print()
      • NeuralNetworkFiltering.print()
      • NeuralNetworkFiltering.apply_filter()
      • NeuralNetworkFiltering.evaluate()
      • NeuralNetworkFiltering.train()
    • RecurrentNetwork
      • RecurrentNetwork.predict()
      • RecurrentNetwork.train()
  • Reinforcement Learning Filter
    • Examples:
    • ReinforcementLearningFilter
      • ReinforcementLearningFilter.train_q_learning()
      • ReinforcementLearningFilter.train_dqn()
      • ReinforcementLearningFilter.train_ppo()
      • ReinforcementLearningFilter.apply_filter()
      • ReinforcementLearningFilter.rl_filter.train_q_learning()
      • ReinforcementLearningFilter.print()
      • ReinforcementLearningFilter.rl_filter.train_dqn()
      • ReinforcementLearningFilter.print()
      • ReinforcementLearningFilter.rl_filter.train_ppo()
      • ReinforcementLearningFilter.print()
      • ReinforcementLearningFilter.apply_filter()
      • ReinforcementLearningFilter.train_dqn()
      • ReinforcementLearningFilter.train_ppo()
      • ReinforcementLearningFilter.train_q_learning()
    • SimpleNeuralNetwork
      • SimpleNeuralNetwork.get_weights()
      • SimpleNeuralNetwork.predict()
      • SimpleNeuralNetwork.set_weights()
      • SimpleNeuralNetwork.train()
    • SimplePolicyNetwork
      • SimplePolicyNetwork.predict()
      • SimplePolicyNetwork.sample_action()
      • SimplePolicyNetwork.train()
      • SimplePolicyNetwork.update()
    • SimpleValueNetwork
      • SimpleValueNetwork.predict()
      • SimpleValueNetwork.train()
  • EMD (Empirical Mode Decomposition)
    • Examples:
    • EMD
      • EMD.emd()
  • Machine Learning Module
  • Deep Learning Models
    • Examples:
    • BaseDeepModel
      • BaseDeepModel.build_model()
      • BaseDeepModel.load()
      • BaseDeepModel.predict()
      • BaseDeepModel.save()
      • BaseDeepModel.train()
    • CNN1D
      • CNN1D.model
      • CNN1D.history
      • CNN1D.build_model()
      • CNN1D.predict()
      • CNN1D.train()
    • LSTMModel
      • LSTMModel.build_model()
      • LSTMModel.predict()
      • LSTMModel.train()
  • Autoencoder Models
    • Examples:
    • BaseAutoencoder
      • BaseAutoencoder.compute_reconstruction_error()
      • BaseAutoencoder.decode()
      • BaseAutoencoder.detect_anomalies()
      • BaseAutoencoder.encode()
      • BaseAutoencoder.load()
      • BaseAutoencoder.predict()
      • BaseAutoencoder.save()
    • ConvolutionalAutoencoder
      • ConvolutionalAutoencoder.fit()
    • DenoisingAutoencoder
      • DenoisingAutoencoder.denoise()
      • DenoisingAutoencoder.fit()
    • LSTMAutoencoder
      • LSTMAutoencoder.fit()
    • StandardAutoencoder
      • StandardAutoencoder.fit()
    • VariationalAutoencoder
      • VariationalAutoencoder.encode()
      • VariationalAutoencoder.fit()
      • VariationalAutoencoder.sample()
    • denoise_signal()
    • detect_anomalies()
  • Transformer Models
    • MultiHeadSelfAttention
      • MultiHeadSelfAttention.call()
      • MultiHeadSelfAttention.split_heads()
    • PositionalEncoding
      • PositionalEncoding.build()
      • PositionalEncoding.call()
    • TransformerEncoderLayer
      • TransformerEncoderLayer.call()
    • TransformerModel
      • TransformerModel.model
      • TransformerModel.history
      • TransformerModel.build_model()
      • TransformerModel.get_attention_weights()
      • TransformerModel.load()
      • TransformerModel.predict()
      • TransformerModel.save()
      • TransformerModel.train()
  • Feature Extractor
    • FeatureEngineering
      • FeatureEngineering.fit()
      • FeatureEngineering.fit_transform()
      • FeatureEngineering.transform()
    • FeatureExtractor
      • FeatureExtractor.feature_names_
      • FeatureExtractor.n_features_in_
      • FeatureExtractor.feature_importances_
      • FeatureExtractor.fit()
      • FeatureExtractor.get_feature_importances()
      • FeatureExtractor.get_feature_names()
      • FeatureExtractor.transform()
    • extract_features()
  • Transfer Learning
    • DomainAdapter
      • DomainAdapter.fit()
      • DomainAdapter.predict()
    • FineTuner
      • FineTuner.fit()
      • FineTuner.freeze_layers()
      • FineTuner.predict()
      • FineTuner.unfreeze_layers()
    • TransferFeatureExtractor
      • TransferFeatureExtractor.fit()
      • TransferFeatureExtractor.freeze_layers()
      • TransferFeatureExtractor.predict()
      • TransferFeatureExtractor.unfreeze_layers()
    • TransferLearningStrategy
      • TransferLearningStrategy.freeze_layers()
      • TransferLearningStrategy.unfreeze_layers()
    • quick_transfer()
  • Pre-trained Models
    • ModelHub
      • ModelHub.clear_cache()
      • ModelHub.compare_models()
      • ModelHub.get_cache_size()
      • ModelHub.get_model()
      • ModelHub.list_models()
    • PretrainedModel
      • PretrainedModel.evaluate()
      • PretrainedModel.fine_tune()
      • PretrainedModel.from_registry()
      • PretrainedModel.get_features()
      • PretrainedModel.get_layer_names()
      • PretrainedModel.info()
      • PretrainedModel.load()
      • PretrainedModel.predict()
      • PretrainedModel.save()
    • load_pretrained_model()
  • Model Explainability
    • AttentionVisualizer
      • AttentionVisualizer.plot_attention_map()
      • AttentionVisualizer.plot_attention_rollout()
      • AttentionVisualizer.plot_head_comparison()
    • BaseExplainer
      • BaseExplainer.explain()
      • BaseExplainer.plot()
    • GradCAM1D
      • GradCAM1D.compute_heatmap()
      • GradCAM1D.plot_overlay()
    • LIMEExplainer
      • LIMEExplainer.explain()
      • LIMEExplainer.plot()
    • SHAPExplainer
      • SHAPExplainer.explain()
      • SHAPExplainer.plot_dependence()
      • SHAPExplainer.plot_force()
      • SHAPExplainer.plot_summary()
      • SHAPExplainer.plot_waterfall()
    • explain_prediction()
  • Feature Engineering Module
  • ECG Autonomic Features
    • Examples:
    • ECGExtractor
      • ECGExtractor.compute_p_wave_duration()
      • ECGExtractor.compute_pr_interval()
      • ECGExtractor.compute_qrs_duration()
      • ECGExtractor.compute_qt_interval()
      • ECGExtractor.compute_s_wave()
      • ECGExtractor.compute_st_interval()
      • ECGExtractor.detect_arrhythmias()
      • ECGExtractor.detect_r_peaks()
  • PPG Autonomic Features
    • Examples:
    • PPGAutonomicFeatures
      • PPGAutonomicFeatures.compute_dfa()
      • PPGAutonomicFeatures.compute_fractal_dimension()
      • PPGAutonomicFeatures.compute_rrv()
      • PPGAutonomicFeatures.compute_rsa()
  • Morphology Features
    • Examples:
    • PhysiologicalFeatureExtractor
      • PhysiologicalFeatureExtractor.preprocess_signal()
      • PhysiologicalFeatureExtractor.extract_features()
      • PhysiologicalFeatureExtractor.compute_amplitude_variability()
      • PhysiologicalFeatureExtractor.compute_peak_trend()
      • PhysiologicalFeatureExtractor.detect_troughs()
      • PhysiologicalFeatureExtractor.extract_features()
      • PhysiologicalFeatureExtractor.get_preprocess_signal()
  • Signal Quality Assessment Module
  • Signal Quality
    • Examples:
    • SignalQuality
      • SignalQuality.mse()
      • SignalQuality.psnr()
      • SignalQuality.snr()
      • SignalQuality.snr_of_noise()
  • Signal Quality Index
    • Examples:
    • SignalQualityIndex
      • SignalQualityIndex.amplitude_variability_sqi()
      • SignalQualityIndex.baseline_wander_sqi()
      • SignalQualityIndex.eeg_band_power_sqi()
      • SignalQualityIndex.energy_sqi()
      • SignalQualityIndex.heart_rate_variability_sqi()
      • SignalQualityIndex.kurtosis_sqi()
      • SignalQualityIndex.peak_to_peak_amplitude_sqi()
      • SignalQualityIndex.ppg_signal_quality_sqi()
      • SignalQualityIndex.respiratory_signal_quality_sqi()
      • SignalQualityIndex.signal_entropy_sqi()
      • SignalQualityIndex.skewness_sqi()
      • SignalQualityIndex.snr_sqi()
      • SignalQualityIndex.waveform_similarity_sqi()
      • SignalQualityIndex.zero_crossing_sqi()
  • SNR Computation
    • Examples:
    • crest_factor()
    • harmonic_distortion()
    • signal_to_noise_and_distortion_ratio()
    • signal_to_noise_and_interference_ratio()
    • snr_mean_square()
    • snr_peak_to_peak()
    • snr_power_ratio()
  • Utils Module
  • Peak Detection
    • Examples:
    • PeakDetection
      • PeakDetection.detect_peaks()
  • Data Synthesis
    • Examples:
    • SynthesizeData
      • SynthesizeData.generate_ecg_signal()
      • SynthesizeData.generate_noisy_signal()
      • SynthesizeData.generate_ppg_data()
      • SynthesizeData.generate_resp_signal()
      • SynthesizeData.generate_sinusoidal()
      • SynthesizeData.generate_square_wave()
      • SynthesizeData.generate_synthetic_ppg()
      • SynthesizeData.generate_synthetic_ppg_reversed()
    • generate_ecg_signal()
    • generate_noisy_signal()
    • generate_resp_signal()
    • generate_sinusoidal()
    • generate_square_wave()
    • generate_synthetic_ppg()
    • generate_synthetic_ppg_reversed()
    • ordinary_differential_equation()
    • rrprocess()
  • Standard Scaler
    • Examples:
    • StandardScaler
      • StandardScaler.mean_
      • StandardScaler.std_
      • StandardScaler.fit()
      • StandardScaler.transform()
      • StandardScaler.fit_transform()
      • StandardScaler.fit()
      • StandardScaler.fit_transform()
      • StandardScaler.transform()
  • Normalization
    • Examples:
    • min_max_normalization()
    • z_score_normalization()
  • Interpolations
    • Examples:
    • backward_fill()
    • forward_fill()
    • linear_interpolation()
    • mean_imputation()
    • median_imputation()
    • rolling_mean_imputation()
    • spline_interpolation()
  • Health Analysis Module
  • Health Report Generator
    • Examples:
    • HealthReportGenerator
      • HealthReportGenerator.feature_data
      • HealthReportGenerator.segment_duration
      • HealthReportGenerator.interpreter
      • HealthReportGenerator.visualizer
      • HealthReportGenerator.max_workers
      • HealthReportGenerator.batch_visualization()
      • HealthReportGenerator.downsample()
      • HealthReportGenerator.generate()
      • HealthReportGenerator.get_performance_info()
      • HealthReportGenerator.set_concurrency()
    • process_single_feature_visualization()
  • Health Report Visualization
    • Examples:
    • HealthReportVisualizer
      • HealthReportVisualizer.auto_detect_roi()
      • HealthReportVisualizer.create_visualizations()
  • Interpretation Engine
    • Examples:
    • InterpretationEngine
      • InterpretationEngine.config
      • InterpretationEngine.get_range_status()
      • InterpretationEngine.interpret_feature()
      • InterpretationEngine.interpret_multiple_features()
      • InterpretationEngine.load_feature_config()
  • Web Application API
  • Data Service
    • DataService
      • DataService.clear_all_data()
      • DataService.clear_data()
      • DataService.clear_filtered_data()
      • DataService.get_all_data()
      • DataService.get_column_mapping()
      • DataService.get_config()
      • DataService.get_current_config()
      • DataService.get_current_data()
      • DataService.get_data()
      • DataService.get_data_info()
      • DataService.get_data_summary()
      • DataService.get_filter_info()
      • DataService.get_filtered_data()
      • DataService.has_filtered_data()
      • DataService.load_data()
      • DataService.process_data()
      • DataService.set_column_mapping()
      • DataService.store_data()
      • DataService.store_filtered_data()
      • DataService.update_column_mapping()
      • DataService.update_config()
    • get_data_service()
  • Settings Service
    • AnalysisSettings
      • AnalysisSettings.analysis_options
      • AnalysisSettings.default_fft_points
      • AnalysisSettings.default_sampling_freq
      • AnalysisSettings.default_window_type
      • AnalysisSettings.peak_threshold
      • AnalysisSettings.quality_threshold
    • ApplicationSettings
      • ApplicationSettings.analysis
      • ApplicationSettings.data
      • ApplicationSettings.general
      • ApplicationSettings.last_updated
      • ApplicationSettings.system
      • ApplicationSettings.version
    • DataSettings
      • DataSettings.auto_save_interval
      • DataSettings.data_retention_days
      • DataSettings.export_format
      • DataSettings.export_options
      • DataSettings.image_format
      • DataSettings.max_file_size
    • GeneralSettings
      • GeneralSettings.auto_refresh_interval
      • GeneralSettings.display_options
      • GeneralSettings.page_size
      • GeneralSettings.theme
      • GeneralSettings.timezone
    • SettingsService
      • SettingsService.export_settings()
      • SettingsService.get_all_settings()
      • SettingsService.get_analysis_settings()
      • SettingsService.get_data_settings()
      • SettingsService.get_general_settings()
      • SettingsService.get_settings_summary()
      • SettingsService.get_system_settings()
      • SettingsService.import_settings()
      • SettingsService.reset_to_defaults()
      • SettingsService.update_analysis_settings()
      • SettingsService.update_data_settings()
      • SettingsService.update_general_settings()
      • SettingsService.update_system_settings()
      • SettingsService.validate_settings()
    • SystemSettings
      • SystemSettings.max_cpu_usage
      • SystemSettings.memory_limit_gb
      • SystemSettings.parallel_threads
      • SystemSettings.security_options
      • SystemSettings.session_timeout_minutes
    • get_current_settings()
    • get_default_settings()
    • get_settings_service()
    • load_settings()
    • merge_settings()
    • save_settings()
    • update_settings()
    • validate_settings()
  • API Endpoints
    • FeatureExtractionRequest
      • FeatureExtractionRequest.data
      • FeatureExtractionRequest.feature_type
      • FeatureExtractionRequest.model_config
      • FeatureExtractionRequest.sampling_rate
    • FilterRequest
      • FilterRequest.data
      • FilterRequest.filter_type
      • FilterRequest.high_cutoff
      • FilterRequest.low_cutoff
      • FilterRequest.model_config
      • FilterRequest.order
      • FilterRequest.sampling_rate
    • QualityAssessmentRequest
      • QualityAssessmentRequest.model_config
      • QualityAssessmentRequest.original_data
      • QualityAssessmentRequest.processed_data
      • QualityAssessmentRequest.sampling_rate
    • RespiratoryRequest
      • RespiratoryRequest.data
      • RespiratoryRequest.method
      • RespiratoryRequest.model_config
      • RespiratoryRequest.sampling_rate
      • RespiratoryRequest.signal_type
    • SignalData
      • SignalData.data
      • SignalData.model_config
      • SignalData.sampling_rate
      • SignalData.signal_type
    • TransformRequest
      • TransformRequest.data
      • TransformRequest.model_config
      • TransformRequest.sampling_rate
      • TransformRequest.transform_type
    • apply_adaptive_filter()
    • apply_butterworth_filter()
    • apply_fft()
    • apply_wavelet()
    • assess_signal_quality()
    • batch_process_signals()
    • estimate_respiratory_rate()
    • extract_frequency_domain_features()
    • extract_hrv_features()
    • extract_time_domain_features()
    • generate_health_report()
    • get_version()
    • health_check()
  • Web Application Callbacks
  • Core Callbacks
    • register_sidebar_callbacks()
  • Upload Callbacks
    • create_data_preview()
    • create_error_status()
    • create_file_path_loading_indicator()
    • create_processing_progress_section()
    • create_success_status()
    • create_upload_progress_bar()
    • load_data_headers_only()
    • load_data_with_format()
    • register_upload_callbacks()
  • Page Routing Callbacks
    • display_page()
    • register_page_routing_callbacks()
  • Analysis Callbacks
    • apply_filter()
    • create_enhanced_psd_plot()
    • create_enhanced_spectrogram_plot()
    • create_fft_plot()
    • create_frequency_band_power_table()
    • create_frequency_harmonics_table()
    • create_frequency_peak_analysis_table()
    • create_frequency_stability_table()
    • create_stft_plot()
    • create_wavelet_plot()
    • generate_frequency_analysis_results()
    • register_vitaldsp_callbacks()
  • Signal Filtering Callbacks
    • apply_additional_traditional_filters()
    • apply_advanced_filter()
    • apply_enhanced_artifact_removal()
    • apply_enhanced_ensemble_filter()
    • apply_ensemble_filter()
    • apply_filter()
    • apply_multi_modal_filtering()
    • apply_neural_filter()
    • apply_traditional_filter()
    • calculate_advanced_quality_metrics()
    • calculate_correlation()
    • calculate_entropy()
    • calculate_frequency_metrics()
    • calculate_kurtosis()
    • calculate_morphological_features()
    • calculate_mse()
    • calculate_performance_metrics()
    • calculate_skewness()
    • calculate_smoothness()
    • calculate_snr_improvement()
    • calculate_statistical_metrics()
    • calculate_temporal_features()
    • configure_plot_with_pan_zoom()
    • create_empty_figure()
    • create_filter_comparison_plot()
    • create_filter_quality_plots()
    • create_filtered_signal_plot()
    • create_filtering_results_table()
    • create_original_signal_plot()
    • generate_filter_quality_metrics()
    • register_signal_filtering_callbacks()
    • safe_log_range()
  • Respiratory Analysis Callbacks
    • create_comprehensive_respiratory_plots()
    • create_empty_figure()
    • create_respiratory_signal_plot()
    • detect_respiratory_signal_type()
    • generate_comprehensive_respiratory_analysis()
    • register_respiratory_callbacks()
    • toggle_ensemble_options()
  • Features Callbacks
    • apply_preprocessing()
    • create_comprehensive_features_display()
    • create_empty_figure()
    • create_features_analysis_plots()
    • detect_signal_type()
    • extract_advanced_features()
    • extract_comprehensive_features()
    • extract_entropy_features()
    • extract_fractal_features()
    • extract_morphological_features()
    • extract_spectral_features()
    • extract_statistical_features()
    • extract_temporal_features()
    • register_features_callbacks()
  • Physiological Callbacks
    • analyze_advanced_computation()
    • analyze_advanced_features()
    • analyze_beat_to_beat()
    • analyze_energy()
    • analyze_envelope()
    • analyze_feature_engineering()
    • analyze_frequency()
    • analyze_hrv()
    • analyze_hrv_fallback()
    • analyze_morphology()
    • analyze_preprocessing()
    • analyze_segmentation()
    • analyze_signal_quality()
    • analyze_signal_quality_advanced()
    • analyze_statistical()
    • analyze_transforms()
    • analyze_trends()
    • analyze_waveform()
    • create_advanced_features_plots()
    • create_beat_to_beat_plots()
    • create_comprehensive_analysis_plot()
    • create_comprehensive_dashboard()
    • create_comprehensive_results_display()
    • create_empty_figure()
    • create_energy_analysis_plot()
    • create_energy_plots()
    • create_envelope_plots()
    • create_fourier_plots()
    • create_frequency_plots()
    • create_hilbert_plots()
    • create_hrv_plots()
    • create_hrv_poincare_plot()
    • create_hrv_time_series_plot()
    • create_morphology_analysis_plot()
    • create_morphology_plots()
    • create_physiological_analysis_plots()
    • create_physiological_signal_plot()
    • create_quality_assessment_plot()
    • create_segmentation_plots()
    • create_signal_quality_plots()
    • create_transform_plots()
    • create_waveform_plots()
    • create_wavelet_plots()
    • detect_physiological_signal_type()
    • format_large_number()
    • get_vitaldsp_advanced_computation()
    • get_vitaldsp_feature_engineering()
    • get_vitaldsp_hrv_analysis()
    • get_vitaldsp_morphology_analysis()
    • get_vitaldsp_signal_quality()
    • get_vitaldsp_transforms()
    • normalize_signal_type()
    • perform_physiological_analysis()
    • perform_physiological_analysis_enhanced()
    • physiological_analysis_callback()
    • register_additional_physiological_callbacks()
    • register_physiological_callbacks()
    • suggest_best_signal_column()
    • update_physio_time_inputs()
    • update_physio_time_slider_range()
    • update_time_input_max_values()
    • update_time_slider_marks()
  • Respiratory Callbacks
    • create_comprehensive_respiratory_plots()
    • create_empty_figure()
    • create_respiratory_signal_plot()
    • detect_respiratory_signal_type()
    • generate_comprehensive_respiratory_analysis()
    • register_respiratory_callbacks()
  • Utility Functions
  • Common Utilities
    • Examples:
    • argrelextrema()
    • coherence()
    • deprecated()
    • dtw_distance_windowed()
    • filtfilt()
    • find_peaks()
    • grangercausalitytests()
    • pearsonr()
  • Error Handling
    • AnalysisError
    • DataProcessingError
    • FileUploadError
    • ValidationError
    • WebappError
    • create_error_alert()
    • create_info_alert()
    • create_success_alert()
    • create_user_friendly_error_message()
    • create_warning_alert()
    • format_error_for_display()
    • format_error_message()
    • get_analysis_error_suggestions()
    • get_processing_error_suggestions()
    • get_upload_error_suggestions()
    • handle_analysis_error()
    • handle_error()
    • handle_processing_error()
    • handle_upload_error()
    • log_error_with_context()
    • safe_execute()
    • validate_data_types()
    • validate_required_fields()
  • Data Processor
    • DataProcessor
      • DataProcessor.generate_sample_ppg_data()
      • DataProcessor.process_uploaded_data()
      • DataProcessor.read_file()
      • DataProcessor.read_uploaded_content()
      • DataProcessor.validate_file_extension()
  • Settings Utils
    • SettingsExporter
      • SettingsExporter.export_settings_json()
      • SettingsExporter.import_settings_json()
    • SettingsValidator
      • SettingsValidator.validate_analysis_settings()
      • SettingsValidator.validate_data_settings()
      • SettingsValidator.validate_general_settings()
      • SettingsValidator.validate_system_settings()
    • SystemMonitor
      • SystemMonitor.get_cpu_info()
      • SystemMonitor.get_disk_info()
      • SystemMonitor.get_memory_info()
      • SystemMonitor.get_network_info()
      • SystemMonitor.get_system_health()
      • SystemMonitor.get_system_info()
    • ThemeManager
      • ThemeManager.THEMES
      • ThemeManager.get_css_variables()
      • ThemeManager.get_theme_colors()
      • ThemeManager.get_theme_preview()
    • apply_setting_constraints()
    • backup_settings()
    • export_settings()
    • get_default_settings()
    • get_setting_schema()
    • get_setting_value()
    • get_system_recommendations()
    • import_settings()
    • load_user_settings()
    • reset_to_defaults()
    • restore_settings()
    • save_user_settings()
    • set_setting_value()
    • validate_setting_value()
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