Sensing and Signal Processing in Smart Healthcare
Zhao, Wenbing
Sensing and Signal Processing in Smart Healthcare - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (198 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-0027-0 9783036500263 9783036500270
10.3390/books978-3-0365-0027-0 doi
Language
English language teaching (ELT)
smart homes Internet of Things (IoT) Wi-Fi human monitoring behavioral analysis ambient assisted living intelligent luminaires wireless sensor network indoor localisation indoor monitoring Graphics Processing Units (GPUs) CUDA OpenMP OpenCL K-means brain cancer detection hyperspectral imaging unsupervised clustering impaired sensor Structural Health Monitoring Time of Flight subharmonics Cascaded-Integrator-Comb (CIC) filter FPGA fixed point math data adaptive demodulator motion estimation inertial sensors simulation spline function Kalman filter eHealth software engineering gesture recognition Dynamic Time Warping Hidden Markov Model usability Cramér–Rao lower bound (CRLB) human motion Inertial Measurement Unit (IMU) Time of Arrival (TOA) wearable sensors endothelial dysfunction photoplethysmography machine learning computer-assisted screening sleep pose recognition keypoints feature matching Bayesian inference near-infrared images scale invariant feature transform heartbeat classification arrhythmia denoising autoencoder autoencoder deep learning auditory perception biometrics computer vision web control access web security human–computer interaction n/a
Sensing and Signal Processing in Smart Healthcare - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (198 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-0027-0 9783036500263 9783036500270
10.3390/books978-3-0365-0027-0 doi
Language
English language teaching (ELT)
smart homes Internet of Things (IoT) Wi-Fi human monitoring behavioral analysis ambient assisted living intelligent luminaires wireless sensor network indoor localisation indoor monitoring Graphics Processing Units (GPUs) CUDA OpenMP OpenCL K-means brain cancer detection hyperspectral imaging unsupervised clustering impaired sensor Structural Health Monitoring Time of Flight subharmonics Cascaded-Integrator-Comb (CIC) filter FPGA fixed point math data adaptive demodulator motion estimation inertial sensors simulation spline function Kalman filter eHealth software engineering gesture recognition Dynamic Time Warping Hidden Markov Model usability Cramér–Rao lower bound (CRLB) human motion Inertial Measurement Unit (IMU) Time of Arrival (TOA) wearable sensors endothelial dysfunction photoplethysmography machine learning computer-assisted screening sleep pose recognition keypoints feature matching Bayesian inference near-infrared images scale invariant feature transform heartbeat classification arrhythmia denoising autoencoder autoencoder deep learning auditory perception biometrics computer vision web control access web security human–computer interaction n/a