Sensing and Signal Processing in Smart Healthcare

In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication...

Full description

Saved in:
Bibliographic Details
Other Authors: Zhao, Wenbing (Editor), Sampalli, Srinivas (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:DOAB: download the publication
DOAB: description of the publication
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000naaaa2200000uu 4500
001 doab_20_500_12854_68355
005 20210501
003 oapen
006 m o d
007 cr|mn|---annan
008 20210501s2021 xx |||||o ||| 0|eng d
020 |a books978-3-0365-0027-0 
020 |a 9783036500263 
020 |a 9783036500270 
040 |a oapen  |c oapen 
024 7 |a 10.3390/books978-3-0365-0027-0  |c doi 
041 0 |a eng 
042 |a dc 
072 7 |a C  |2 bicssc 
072 7 |a E  |2 bicssc 
100 1 |a Zhao, Wenbing  |4 edt 
700 1 |a Sampalli, Srinivas  |4 edt 
700 1 |a Zhao, Wenbing  |4 oth 
700 1 |a Sampalli, Srinivas  |4 oth 
245 1 0 |a Sensing and Signal Processing in Smart Healthcare 
260 |a Basel, Switzerland  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2021 
300 |a 1 electronic resource (198 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication modules such as Bluetooth, radio frequency identification, and near-field communication. In smart healthcare applications, designing ergonomic and intuitive human-computer interfaces is crucial because a system that is not easy to use will create a huge obstacle to adoption and may significantly reduce the efficacy of the solution. Signal and data processing is another important consideration in smart healthcare applications because it must ensure high accuracy with a high level of confidence in order for the applications to be useful for clinicians in making diagnosis and treatment decisions. This Special Issue is a collection of 10 articles selected from a total of 26 contributions. These contributions span the areas of signal processing and smart healthcare systems mostly contributed by authors from Europe, including Italy, Spain, France, Portugal, Romania, Sweden, and Netherlands. Authors from China, Korea, Taiwan, Indonesia, and Ecuador are also included. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by/4.0/ 
546 |a English 
650 7 |a Language  |2 bicssc 
650 7 |a English language teaching (ELT)  |2 bicssc 
653 |a smart homes 
653 |a Internet of Things (IoT) 
653 |a Wi-Fi 
653 |a human monitoring 
653 |a behavioral analysis 
653 |a ambient assisted living 
653 |a intelligent luminaires 
653 |a wireless sensor network 
653 |a indoor localisation 
653 |a indoor monitoring 
653 |a Graphics Processing Units (GPUs) 
653 |a CUDA 
653 |a OpenMP 
653 |a OpenCL 
653 |a K-means 
653 |a brain cancer detection 
653 |a hyperspectral imaging 
653 |a unsupervised clustering 
653 |a impaired sensor 
653 |a Structural Health Monitoring 
653 |a Time of Flight 
653 |a subharmonics 
653 |a Cascaded-Integrator-Comb (CIC) filter 
653 |a FPGA 
653 |a fixed point math 
653 |a data adaptive demodulator 
653 |a motion estimation 
653 |a inertial sensors 
653 |a simulation 
653 |a spline function 
653 |a Kalman filter 
653 |a eHealth 
653 |a software engineering 
653 |a gesture recognition 
653 |a Dynamic Time Warping 
653 |a Hidden Markov Model 
653 |a usability 
653 |a Cramér-Rao lower bound (CRLB) 
653 |a human motion 
653 |a Inertial Measurement Unit (IMU) 
653 |a Time of Arrival (TOA) 
653 |a wearable sensors 
653 |a endothelial dysfunction 
653 |a photoplethysmography 
653 |a machine learning 
653 |a computer-assisted screening 
653 |a sleep pose recognition 
653 |a keypoints feature matching 
653 |a Bayesian inference 
653 |a near-infrared images 
653 |a scale invariant feature transform 
653 |a heartbeat classification 
653 |a arrhythmia 
653 |a denoising autoencoder 
653 |a autoencoder 
653 |a deep learning 
653 |a auditory perception 
653 |a biometrics 
653 |a computer vision 
653 |a web control access 
653 |a web security 
653 |a human-computer interaction 
653 |a n/a 
856 4 0 |a www.oapen.org  |u https://mdpi.com/books/pdfview/book/3364  |7 0  |z DOAB: download the publication 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/68355  |7 0  |z DOAB: description of the publication