Essays about: "multi-channel data"
Showing result 1 - 5 of 36 essays containing the words multi-channel data.
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1. Heart rate estimation from wrist-PPG signals in activity by deep learning methods
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In the context of health improving, the measurement of vital parameters such as heart rate (HR) can provide solutions for health monitoring, prevention and screening for certain chronic diseases. Among the different technologies for HR measuring, photoplethysmography (PPG) technique embedded in smart watches is the most commonly used in the field of consumer electronics since it is comfortable and does not require any user intervention. READ MORE
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2. Multi-Channel Sentiment Analysis in Swedish as Basis for Marketing Decisions
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : In today’s world, it is not enough for companies to consider any one social media channel in isolation. Instead, they must provide their customers with a unified experience across channels and consider interdependencies between channels. READ MORE
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3. Elastic Net Regression for Prosthesis Control in Short Residual Limb Amputees: Performance and Generalizability
University essay from Lunds universitet/Avdelningen för Biomedicinsk teknikAbstract : This Master's thesis in Biomedical Engineering investigates the performance and generalizability of linear regression models in context of prosthesis control for short residual limb amputees. This thesis uses intramuscular electromyography data, and a regression and emplys a regression technique called Elastic Net Regression - a technique that combines L1 and L2-regularization - to predict 1-DOF isometric forces outputs from fingers and the wrist. READ MORE
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4. Deep convolution neural network for attention decoding in multi-channel EEG with conditional variational autoencoder for data augmentation
University essay from Lunds universitet/Institutionen för reglerteknikAbstract : Objectives: This project aims to develop a deep learning-based attention decoding system that can distinguish between noise and speech in noise and also identify the direction of attended speech from the brain data recorded with electroencephalography (EEG) instruments. Two deep convolutional neural network (DCNN) models will be designed: (1) one DCNN model capable of classifying incoming segments of sound as speech or speech in background noise, and (2) one DCNN model identifying the direction (left vs. READ MORE
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5. Battery Capacity Prediction Using Deep Learning : Estimating battery capacity using cycling data and deep learning methods
University essay from Mälardalens universitet/Framtidens energiAbstract : The growing urgency of climate change has led to growth in the electrification technology field, where batteries have emerged as an essential role in the renewable energy transition, supporting the implementation of environmentally friendly technologies such as smart grids, energy storage systems, and electric vehicles. Battery cell degradation is a common occurrence indicating battery usage. READ MORE