Essays about: "Signal Processing Feature Extraction"

Showing result 1 - 5 of 20 essays containing the words Signal Processing Feature Extraction.

1. 1. Exploring State-of-the-Art Machine Learning Methods for Quantifying Exercise-induced Muscle Fatigue

   University essay from Högskolan i Halmstad/Akademin för informationsteknologi

   Author : Abboud Afram; Danial Sarab Fard Sabet; [2023]
   Keywords : EMG; SEMG; STFT; CWT; SVM; CNN; GAN; DCGAN; BCE; SGD; deep learning; machine learning; muscle fatigue; DCGAN; spectrogram; CNN models; transfers learning; data augmentation; feature extraction;

   Abstract : Muscle fatigue is a severe problem for elite athletes, and this is due to the long resting times, which can vary. Various mechanisms can cause muscle fatigue which signifies that the specific muscle has reached its maximum force and cannot continue the task. READ MORE

3. 2. Deep Learning-Driven EEG Classification in Human-Robot Collaboration

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Yuan Wo; [2023]
   Keywords : Human-robot collaboration; Electroencephalogram signal; Signal Processing Feature Extraction; Deep Learning method; Dilated Convolutional Neural Network; Människa-robot-samarbete; Elektroencefalogram-signal; Signalförädlingsfunktionsutvinning; Djupinlärningsmetod; Dilaterat konvolutionellt neuronnätverk.;

   Abstract : Human-robot collaboration (HRC) occurs when people and robots work together in a shared environment. Current robots often use rigid programs unsuitable for HRC. Multimodal robot programming offers an easier way to control robots using inputs like voice and gestures. READ MORE

4. 3. Exercise Classification with Machine Learning

   University essay from Högskolan i Halmstad/Akademin för informationsteknologi

   Author : Joel Ekstrand; [2023]
   Keywords : Machine learning; signal processing; noise reduction; feature extraction; exercise classification; machine learning; signalprocessering; brusreducering; feature extraction; rörelseklassificering;

   Abstract : Innowearable AB has developed a product called Inno-XTM that calculates musclefatigue during three exercises: squat jumps, wall sit, and leg extension. Inno-X uses an accelerometer and a surface electromyography sensor. READ MORE

5. 4. Motor Imagery Signal Classification using Adversarial Learning - A Systematic Literature Review

   University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

   Author : Osama Mahmudi; Shubhra Mishra; [2023]
   Keywords : Adversarial Learning; Motor Imagery; BCI; EEG; Machine Learning;

   Abstract : Context: Motor Imagery (MI) signal classification is a crucial task for developing Brain-Computer Interfaces (BCIs) that allow people to control devices using their thoughts. However, traditional machine learning approaches often suffer from limited performance due to inter-subject variability and limited data availability. READ MORE

6. 5. E-noses equipped with Artificial Intelligence Technology for diagnosis of dairy cattle disease in veterinary

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Farbod Haselzadeh; [2021]
   Keywords : Artificial intelligence; Electronic nose; Gas sensor arrays; Principal component analysis; Autoencoder; Veterinary diagnose; Feature extraction; Dimentionality reduction; Normalization; Maskin intelligence; Artificial intelligence; Elektronisk näsa; Gas sensore array; Normalisering; dimensionalitetsminskning; Autoencoder; Klassificering AI; E-nose; Feature Extraction; Normalization; PCA; Autoencoder; Encoder; Decoder; MLP; Classifier; LDA; Support Vector Machine; Logistic Regression; Cross Validation; Signal segmentation;

   Abstract : The main goal of this project, running at Neurofy AB, was that developing an AI recognition algorithm also known as, gas sensing algorithm or simply recognition algorithm, based on Artificial Intelligence (AI) technology, which would have the ability to detect or predict diary cattle diseases using odor signal data gathered, measured and provided by Gas Sensor Array (GSA) also known as, Electronic Nose or simply E-nose developed by the company. Two major challenges in this project were to first overcome the noises and errors in the odor signal data, as the E-nose is supposed to be used in an environment with difference conditions than laboratory, for instance, in a bail (A stall for milking cows) with varying humidity and temperatures, and second to find a proper feature extraction method appropriate for GSA. READ MORE