Feature Extraction from EMG Data
Budget: €30 – €250 EUR
I need a skilled Matlab expert to process and extract features, focusing on both frequency and time-domain information from raw EMG data. The objective is to perform signal analysis for a variety of purposes - including biomedical research.
Key Responsibilities:
- Data Processing Steps: Data preparation, Filtering, Rectification, Normalisation, Plotting (Create plots at each stage (raw, filtered, rectified, normalised) for visual verification).
- Feature Extraction: time domain (e.g., mean, variance, root mean square, etc.), frequency domain (e.g., power spectral density, median frequency, etc.).
- Implementing Fourier Transform, Wavelet Transform, and Envelope Extraction on the raw EMG data.
- Extracting and analyzing various features from the data to gather insights and support the intended uses.
Ideal Candidate:
- Proficient in Matlab with past experience in signal processing.
- Familiarity with EMG data and its analysis would be a strong advantage.
- Ability to implement and understand Fourier and Wavelet Transforms, as well as Envelope Extraction.
- Strong analytical skills to interpret and present findings from the processed data.
Deliverables:
-Matlab code for the entire processing and feature extraction pipeline.
-Documentation and a summary report of the methods used.
Key Responsibilities:
- Data Processing Steps: Data preparation, Filtering, Rectification, Normalisation, Plotting (Create plots at each stage (raw, filtered, rectified, normalised) for visual verification).
- Feature Extraction: time domain (e.g., mean, variance, root mean square, etc.), frequency domain (e.g., power spectral density, median frequency, etc.).
- Implementing Fourier Transform, Wavelet Transform, and Envelope Extraction on the raw EMG data.
- Extracting and analyzing various features from the data to gather insights and support the intended uses.
Ideal Candidate:
- Proficient in Matlab with past experience in signal processing.
- Familiarity with EMG data and its analysis would be a strong advantage.
- Ability to implement and understand Fourier and Wavelet Transforms, as well as Envelope Extraction.
- Strong analytical skills to interpret and present findings from the processed data.
Deliverables:
-Matlab code for the entire processing and feature extraction pipeline.
-Documentation and a summary report of the methods used.