electrocardiogram; deep metric learning; k-nearest neighbors classifier; premature ventricular contraction; dimensionality reduction; classifications; Laplacian eigenmaps; locality preserving projections; compressed sensing; convolutional neural network; EEG; epileptic seizure detection; RISC-V; ultra-low-power; sepsis; atrial fibrillation; prediction; heart rate variability; feature extraction; random forest; annotations; myoelectric prosthesis; sEMG; grasp phases analysis; grasp classification; machine learning; ...
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electrocardiogram; deep metric learning; k-nearest neighbors classifier; premature ventricular contraction; dimensionality reduction; classifications; Laplacian eigenmaps; locality preserving projections; compressed sensing; convolutional neural network; EEG; epileptic seizure detection; RISC-V; ultra-low-power; sepsis; atrial fibrillation; prediction; heart rate variability; feature extraction; random forest; annotations; myoelectric prosthesis; sEMG; grasp phases analysis; grasp classification; machine learning; electronic nose; liver dysfunction; cirrhosis; semiconductor metal oxide gas sensor; vagus nerve; intraneural; decoding; intrafascicular; recording; carbon nanotube; artificial intelligence; lens-free shadow imaging technique; cell-line analysis; cell signal enhancement; deep learning; compressed sensing; ECG signal; reconstruction dictionaries; projection matrices; signal classifications; osteopenia; sarcopenia; XAI; SHAP; IMU; gait analysis; artificial intelligence; sensors; convolutional neural networks; Parkinson's disease; biomedical monitoring; accelerometer; pressure sensor; disease management; electromyography; correlation; high blood pressure; hypertension; photoplethysmography; electrocardiography; calibration; classification models; machine learning; deep learning; COVID-19; ECG trace image; transfer learning; Convolutional Neural Networks (CNN); feature selection; sympathetic activity (SNA); skin sympathetic nerve activity (SKNA); electrodes; electrocardiogram (ECG); cardiac time interval; dynamic time warping; fiducial point detection; heart failure; seismocardiography; wearable electroencephalography; motor imagery; motor execution; beta rebound; brain-machine interface; feature extraction; EEG classification; n/a
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Edition: 2022, Mdpi AG
Hardcover,
New
Available Copies: 10+
Details: ISBN:
3036546014
ISBN-13:
9783036546018
Pages:
318
Publisher:
Mdpi AG
Published:
7/8/2022 12: 00: 00 AM
Language:
English
Alibris ID:
17833512045
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Seller's Description: PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.
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Edition: 2022, Mdpi AG
Hardcover,
New
Available Copies: 10+
Details: ISBN:
3036546014
ISBN-13:
9783036546018
Pages:
318
Publisher:
Mdpi AG
Published:
7/8/2022 12: 00: 00 AM
Language:
English
Alibris ID:
17860985819
Shipping Options: Standard Shipping: $4.57
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description: PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.
Hide Details ▴
Edition: 2022, Mdpi AG
Hardcover,
New
Available Copies: 10+
Details: ISBN:
3036546014
ISBN-13:
9783036546018
Pages:
318
Publisher:
Mdpi AG
Published:
2022
Language:
English
Alibris ID:
17248901758
Shipping Options: Standard Shipping: $4.57
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description: New. Print on demand Sewn binding. Cloth over boards. 318 p.
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