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The role of nanotechnologies in personalized medicine is rising remarkably in the last decade because of the ability of these new sensing systems to diagnose diseases from early stages and the availability of continuous screenings to characterize the efficiency of drugs and therapies for each single patient. Recent technological advancements are allowing the development of biosensors in low-cost and user-friendly platforms, thereby overcoming the last obstacle for these systems, represented by limiting costs and low yield, until now. In this context, photonic biosensors represent one of the main emerging sensing modalities because of their ability to combine high sensitivity and selectivity together with real-time operation, integrability, and compatibility with microfluidics and electric circuitry for the readout, which is fundamental for the realization of lab-on-chip systems. This book, “Photonic Biosensors: Detection, Analysis and Medical Diagnostics”, has been published thanks to the contributions of the authors and collects research articles, the content of which is expected to assume an important role in the outbreak of biosensors in the biomedical field, considering the variety of the topics that it covers, from the improvement of sensors’ performance to new, emerging applications and strategies for on-chip integrability, aiming at providing a general overview for readers on the current advancements in the biosensing field.

Research & information: general --- integrated photonics --- microfluidics --- packaging --- photonic biosensors --- optical resonators --- multiplexed sensing --- 3D printing --- wearable laser Doppler flowmetry --- blood perfusion --- wavelet analysis --- smokers --- biosensors --- optical cavity-based biosensor --- biomarker detection --- noninvasive glucose sensing --- near-infrared spectroscopy --- skin tissue reflection spectroscopy --- calibration modeling --- science-based calibration (SBC) --- blood pressure --- photoplethysmography --- derivatives of PPG --- convolutional neural network --- ensemble empirical mode decomposition --- bacteria biofilm --- optoelectronic device --- antimicrobial resistance --- biosensing --- integrated photonics --- microfluidics --- packaging --- photonic biosensors --- optical resonators --- multiplexed sensing --- 3D printing --- wearable laser Doppler flowmetry --- blood perfusion --- wavelet analysis --- smokers --- biosensors --- optical cavity-based biosensor --- biomarker detection --- noninvasive glucose sensing --- near-infrared spectroscopy --- skin tissue reflection spectroscopy --- calibration modeling --- science-based calibration (SBC) --- blood pressure --- photoplethysmography --- derivatives of PPG --- convolutional neural network --- ensemble empirical mode decomposition --- bacteria biofilm --- optoelectronic device --- antimicrobial resistance --- biosensing

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Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization.

Technology: general issues --- inertial sensor --- gait --- validity --- functional calibration --- accuracy --- wearable electronic devices --- kinematics --- head rotation --- ecological research --- gait analysis --- characterization --- smart insole --- vertical ground reaction forces --- force sensitive resistors --- piezoelectric sensors --- sensor calibration --- heart rate --- photoplethysmography --- PPG --- time-domain --- wearable device --- concurrent validity --- outcome assessment --- feasibility --- rehabilitation --- data fusion --- MARG --- IMU --- eye tracker --- self-contained --- head motion measurement --- motor variability --- actigraphy --- triaxial accelerometers --- jumping --- human-computer interaction --- affective technologies --- interaction design --- biosensing --- actuation --- somaesthetics --- design toolkits --- serious videogames --- motion capture --- upper limbs --- physical rehabilitation --- telerehabilitation --- inertial sensors --- inertial measurement unit (IMU) --- state of the art --- inertial sensor measurement systems --- motion accuracy --- Baduanjin --- physical education --- physiotherapy --- e-health --- motion sensing --- wireless charging --- wireless connectivity --- low power --- trunk --- upper extremity --- compensation --- reaching --- Kinect --- video motion capture --- reliability --- inertial sensor --- gait --- validity --- functional calibration --- accuracy --- wearable electronic devices --- kinematics --- head rotation --- ecological research --- gait analysis --- characterization --- smart insole --- vertical ground reaction forces --- force sensitive resistors --- piezoelectric sensors --- sensor calibration --- heart rate --- photoplethysmography --- PPG --- time-domain --- wearable device --- concurrent validity --- outcome assessment --- feasibility --- rehabilitation --- data fusion --- MARG --- IMU --- eye tracker --- self-contained --- head motion measurement --- motor variability --- actigraphy --- triaxial accelerometers --- jumping --- human-computer interaction --- affective technologies --- interaction design --- biosensing --- actuation --- somaesthetics --- design toolkits --- serious videogames --- motion capture --- upper limbs --- physical rehabilitation --- telerehabilitation --- inertial sensors --- inertial measurement unit (IMU) --- state of the art --- inertial sensor measurement systems --- motion accuracy --- Baduanjin --- physical education --- physiotherapy --- e-health --- motion sensing --- wireless charging --- wireless connectivity --- low power --- trunk --- upper extremity --- compensation --- reaching --- Kinect --- video motion capture --- reliability

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With recent technological advances in multiple research fields such as materials science, micro-/nano-technology, cellular and molecular biology, bioengineering and the environment, much attention is shifting toward the development of new detection tools that not only address needs for high sensitivity and specificity but fulfil economic, environmental, and rapid point-of-care needs for groups and individuals with constrained resources and, possibly, limited training. Miniaturized fluidics-based platforms that precisely manipulate tiny body fluid volumes can be used for medical, healthcare or even environmental (e.g., heavy metal detection) diagnosis in a rapid and accurate manner. These new detection technologies are potentially applicable to different healthcare or environmental issues, since they are disposable, inexpensive, portable, and easy to use for the detection of human diseases or environmental issues—especially when they are manufactured based on low-cost materials, such as paper. The topics in this book (original and review articles) would cover point-of-care detection devices, microfluidic or paper-based detection devices, new materials for making detection devices, and others.

History of engineering & technology --- sepsis --- PCT --- procalcitonin --- immunoassay --- antibiotic --- chemiluminescence --- immunofluorescence --- n/a --- origami-based paper analytic device --- origami ELISA --- IgG --- paraquat --- diabetes mellitus --- ketone bodies --- human breath --- acetone --- beta-hydroxybutyrate --- acetoacetate --- gas chromatography-mass spectrometry (GC-MS) --- type 2 diabetes --- diabetic peripheral neuropathy (DPN) --- electrocardiogram (ECG) --- photoplethysmography (PPG) --- percussion entropy index (PEI) --- decision making, computer-assisted --- decision support systems, clinical --- precision medicine --- computational biology --- molecular tumor board --- cBioPortal --- requirements analysis --- neoplasms --- pH value --- diagnosis --- skin --- wound --- blood --- coagulation --- hemostasis --- point of care --- ROTEM --- TEG --- thromboelastography --- VHA --- viscoelastic testing --- partial-thickness burn injury --- burn blister fluid --- P-ELISA --- angiogenin --- burn wound healing --- Alzheimer’s disease --- β-amyloid peptide --- paper-based ELISA --- P-ELISA, point of care testing --- microfluidics --- point-of-care diagnostics --- antimicrobial resistance --- lab-on-a-chip --- capillary-driven flow --- capillary action --- detections --- smartphone imaging --- lateral flow assay --- immuno-chromatographic --- gold nanoparticles sensor --- UV/Vis spectrophotometer --- malaria pan rapid diagnostic strip --- point-of-care --- Alzheimer's disease

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Smart, wearables devices on a miniature scale are becoming increasingly widely available, typically in the form of smart watches and other connected devices. Consequently, devices to assist in measurements such as electroencephalography (EEG), electrocardiogram (ECG), electromyography (EMG), blood pressure (BP), photoplethysmography (PPG), heart rhythm, respiration rate, apnoea, and motion detection are becoming more available, and play a significant role in healthcare monitoring. The industry is placing great emphasis on making these devices and technologies available on smart devices such as phones and watches. Such measurements are clinically and scientifically useful for real-time monitoring, long-term care, and diagnosis and therapeutic techniques. However, a pertaining issue is that recorded data are usually noisy, contain many artefacts, and are affected by external factors such as movements and physical conditions. In order to obtain accurate and meaningful indicators, the signal has to be processed and conditioned such that the measurements are accurate and free from noise and disturbances. In this context, many researchers have utilized recent technological advances in wearable sensors and signal processing to develop smart and accurate wearable devices for clinical applications. The processing and analysis of physiological signals is a key issue for these smart wearable devices. Consequently, ongoing work in this field of study includes research on filtration, quality checking, signal transformation and decomposition, feature extraction and, most recently, machine learning-based methods.

Technology: general issues --- History of engineering & technology --- automated dietary monitoring --- eating detection --- eating timing error analysis --- biomedical signal processing --- smart eyeglasses --- wearable health monitoring --- artificial neural network --- joint moment prediction --- extreme learning machine --- Hill muscle model --- online input variables --- Review --- ECG --- Signal Processing --- Machine Learning --- Cardiovascular Disease --- Anomaly Detection --- photoplethysmography --- motion artifact --- independent component analysis --- multi-wavelength --- continuous arterial blood pressure --- systolic blood pressure --- diastolic blood pressure --- deep convolutional autoencoder --- genetic algorithm --- electrocardiography --- vectorcardiography --- myocardial infarction --- long short-term memory --- spline --- multilayer perceptron --- pain detection --- stress detection --- wearable sensor --- physiological signals --- behavioral signals --- non-invasive system --- hemodynamics --- arterial blood pressure --- central venous pressure --- pulmonary arterial pressure --- intracranial pressure --- heart rate measurement --- remote HR --- remote PPG --- remote BCG --- blind source separation --- drowsiness detection --- EEG --- frequency-domain features --- multicriteria optimization --- machine learning --- n/a

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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.

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 --- Cramér-Rao lower bound (CRLB) --- human-computer interaction