Sensing and Signal Processing in Smart Healthcare

• Autore: Zhao Wenbing
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
• Descrizione fisica: 1 online resource (198 p.)
• Soggetto topico: English; For ELT / ESL learning, courses, examinations and certificates; Language and Linguistics; Language teaching and learning
• Soggetto non controllato: ambient assisted living; arrhythmia; auditory perception; autoencoder; Bayesian inference; behavioral analysis; biometrics; brain cancer detection; Cascaded-Integrator-Comb (CIC) filter; computer vision; computer-assisted screening; Cramér-Rao lower bound (CRLB); CUDA; data adaptive demodulator; deep learning; denoising autoencoder; Dynamic Time Warping; eHealth; endothelial dysfunction; fixed point math; FPGA; gesture recognition; Graphics Processing Units (GPUs); heartbeat classification; Hidden Markov Model; human monitoring; human motion; human-computer interaction; hyperspectral imaging; impaired sensor; indoor localisation; indoor monitoring; Inertial Measurement Unit (IMU); inertial sensors; intelligent luminaires; Internet of Things (IoT); K-means; Kalman filter; keypoints feature matching; machine learning; motion estimation; n/a; near-infrared images; OpenCL; OpenMP; photoplethysmography; scale invariant feature transform; simulation; sleep pose recognition; smart homes; software engineering; spline function; Structural Health Monitoring; subharmonics; Time of Arrival (TOA); Time of Flight; unsupervised clustering; usability; wearable sensors; web control access; web security; Wi-Fi; wireless sensor network
• Persona (resp. second.): SampalliSrinivas; ZhaoWenbing
• Sommario/riassunto: 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.
• Titolo autorizzato: Sensing and Signal Processing in Smart Healthcare
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557483503321
• Lo trovi qui: Univ. Federico II