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In this Special Issue on “Human Health Engineering Volume II”, we invited submissions exploring recent contributions to the field of human health engineering, i.e., technology for monitoring the physical or mental health status of individuals in a variety of applications. Contributions could focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing physiological variables, papers highlighting health-monitoring applications, and examples of control and process management applications for human health. In comparison to biomedical engineering, we envision that the field of human health engineering will also cover applications for healthy humans (e.g., sports, sleep, and stress), and thus not only contribute to the development of technology for curing patients or supporting chronically ill people, but also to more general disease prevention and optimization of human well-being.

Technology: general issues --- vibratory stimulation device --- local muscle vibration --- proprioceptors --- low back pain --- response frequency --- postural control --- Vater-Pacini corpuscles --- electroencephalography --- deep learning --- driving fatigue --- feature extraction --- convolutional neural network --- rehabilitation --- robotics --- technological devices --- upper limb impairment --- organizational model --- inkjet printing --- respiratory rate --- strain gauge --- stretchable and wearable sensors --- silver nanoparticles --- clinical evaluation --- body posture --- upper limb rehabilitation --- serious games --- haptic feedback --- electromyography sensors --- virtual reality --- smoothness --- wearable sensors --- gait analysis --- stumbling --- plantar visualization --- remote fetal monitor --- measurement uncertainty --- standard deviation --- Monte-Carlo method (MMC) --- efficient estimator --- automated assessment --- UE-FMA --- pinch force --- pulling force --- slip onset --- stroke --- anorexia nervosa --- electrodermal activity --- time-domain analysis --- frequency-domain analysis --- nonlinear analysis --- virtual reality exposure therapy --- driving phobia --- post-traumatic stress disorder --- physiological signal --- piezo-fluid-structural coupled simulation --- APS --- valveless micropump --- closed-loop insulin pump --- Individual verification --- Electrocardiogram (ECG) --- Interval based LDA --- biometrics --- n/a

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People living in both developed and developing countries face serious health challenges related to sedentary lifestyles. It is therefore essential to find new ways to improve health so that people can live longer and can age well. With an ever-growing number of smart sensing systems developed and deployed across the globe, experts are primed to help coach people toward healthier behaviors. The increasing accountability associated with app- and device-based behavior tracking not only provides timely and personalized information and support but also gives us an incentive to set goals and to do more. This book presents some of the recent efforts made towards automatic and autonomous identification and coaching of troublesome behaviors to procure lasting, beneficial behavioral changes.

Technology: general issues --- activity recognition --- wearable devices --- inertial sensors --- Bluetooth beacons --- machine learning --- e-coaching --- m-health intervention --- personalization --- healthy lifestyle --- physical activity --- tangible user interface --- affordance --- multimodal cueing --- animate objects --- activities of daily living --- human activity recognition --- context-awareness --- Bayesian network --- mobile application --- wearable computing --- wrist-worn heart rate devices --- cardiac rehabilitation --- real-time wearable monitoring --- fuzzy logic --- fuzzy linguistic approach --- m-health --- remote coaching --- telemonitoring --- telehealth --- cadence --- marathon --- elevation change analysis --- personalized assistance level --- coaching --- electric bicycles --- ubiquitous computing --- health --- human-centered computing --- digital coaching --- diabetes education --- serious gaming --- self-management --- user evaluations --- sedentary lifestyle --- context recognition --- unhealthy sitting habits --- wearable sensors --- smartphones --- smart objects --- behavior change

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Biomedical imaging is the key technique and process to create informative images of the human body or other organic structures for clinical purposes or medical science. Micro-electro-mechanical systems (MEMS) technology has demonstrated enormous potential in biomedical imaging applications due to its outstanding advantages of, for instance, miniaturization, high speed, higher resolution, and convenience of batch fabrication. There are many advancements and breakthroughs developing in the academic community, and there are a few challenges raised accordingly upon the designs, structures, fabrication, integration, and applications of MEMS for all kinds of biomedical imaging. This Special Issue aims to collate and showcase research papers, short commutations, perspectives, and insightful review articles from esteemed colleagues that demonstrate: (1) original works on the topic of MEMS components or devices based on various kinds of mechanisms for biomedical imaging; and (2) new developments and potentials of applying MEMS technology of any kind in biomedical imaging. The objective of this special session is to provide insightful information regarding the technological advancements for the researchers in the community.

micromachining --- n/a --- capacitive micromachined ultrasonic transducer (CMUT) --- transducer --- gold nanoparticles --- cantilever waveguide --- push-pull actuator --- MEMS mirror --- chemo-FET --- ultrahigh frequency ultrasonic transducer --- fluorescence --- lead-free piezoelectric materials --- acoustics --- bioimaging --- scanner --- micro-optics --- MEMS --- microendoscopy --- ego-motion estimation --- rib waveguide --- electromagnetically-driven --- two-photon --- Lissajous scanning --- fabrication --- microwave resonator --- finite element simulation --- noise figure --- imaging --- modelling --- Si lens --- microwave remote sensing --- piezoelectric array --- smart hydrogels --- bio-FET --- surface micromachining --- tilted microcoil --- near-field microwave --- electrochemical sensors --- potentiometric sensor --- photoacoustic imaging --- micromachined US transducer --- electrostatic actuator --- polyimide capillary --- high frequency ultrasonic transducer --- microring resonator --- ultrasonic transducer --- ultrasonic imaging --- indoor navigation --- optical scanner --- scale ambiguity --- bio-sensors --- non-resonating scanner --- wide-filed imaging --- confocal --- acoustic delay line --- tight focus --- miniaturized microscope --- monocular camera --- low noise amplifier (LNA) --- in vivo --- capacitive --- high spatial resolution --- sensing --- microelectromechanical systems (MEMS) --- needle-type --- display --- pseudo-resonant --- MEMS actuators --- microtechnology --- metal oxide field-effect transistor --- transduction techniques --- MEMS scanning mirror --- 3D Printing --- photoacoustic --- chemo-sensor --- in vitro --- wearable sensors

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The advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as wearables, inertial measurement units, ambient sensors, and cameras or depth sensors, have been adopted on a wide scale. Furthermore, computational intelligence (CI) methods, such as artificial neural networks, have recently emerged as promising tools for the development and application of intelligent systems in motion analysis. Thus, the synergy of classic instrumentation and novel smart devices and techniques has created unique capabilities in the continuous monitoring of motor behaviors in different fields, such as clinics, sports, and ergonomics. However, real-time sensing, signal processing, human activity recognition, and characterization and interpretation of motion metrics and behaviors from sensor data still representing a challenging problem not only in laboratories but also at home and in the community. This book addresses open research issues related to the improvement of classic approaches and the development of novel technologies and techniques in the domain of motion analysis in all the various fields of application.

Technology: general issues --- falls --- slips --- trips --- postural perturbations --- wearables --- stretch-sensors --- ankle kinematics --- rowing --- technology --- inertial sensor --- accelerometer --- performance --- signal processing --- sEMG --- knee --- random forest --- principal component analysis --- back propagation --- estimation model --- knee angle --- deep learning --- neural networks --- gait-phase classification --- electrogoniometer --- EMG sensors --- walking --- gait-event detection --- automotive radar --- machine learning --- walking analysis --- seated posture --- cognitive engagement --- stress level --- load cells --- embedded systems --- sensorized seat --- flexion-relaxation phenomenon --- surface electromyography --- wearable device --- WBSN --- automatic detection of the FRP --- Internet of Things (IoT) --- human activity recognition (HAR) --- motion analysis --- wearable sensors --- cerebral palsy --- hemiplegia --- motor disorders --- gait variability --- coefficient of variation --- surface EMG --- statistical gait analysis --- activation patterns --- co-activation --- Parkinson’s disease --- activity recognition --- rate invariance --- Lie group

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Quantitative movement analysis is widely used in clinical practice and research to investigate movement disorders objectively and in a complete way. Conventionally, body segment kinematic and kinetic parameters are measured in gait laboratories using marker-based optoelectronic systems, force plates, and electromyographic systems. Although movement analyses are considered accurate, the availability of specific laboratories, high costs, and dependency on trained users sometimes limit its use in clinical practice. A variety of compact wearable sensors are available today and have allowed researchers and clinicians to pursue applications in which individuals are monitored in their homes and in community settings within different fields of study, such movement analysis. Wearable sensors may thus contribute to the implementation of quantitative movement analyses even during out-patient use to reduce evaluation times and to provide objective, quantifiable data on the patients’ capabilities, unobtrusively and continuously, for clinical purposes.

Research & information: general --- Biology, life sciences --- Biochemistry --- gait --- smoothness --- older adults --- accelerometer --- inertial measurement unit (IMU) --- upper extremity --- stroke --- biomechanical phenomena --- kinematics --- inertial measurement systems --- motion analysis --- wearable devices --- e-textile --- gait analysis --- m-health --- plantar pressure --- validation --- Internet of Things --- body sensor network --- inertial sensors --- ground reaction force --- spatio-temporal parameters --- wearable sensors --- decision trees --- foot drop stimulation --- symmetry --- inertial measurement sensor --- wearable inertial sensors --- marker-based optoelectronic system --- ACL --- rehabilitation --- motion capture validation --- upper limb --- Parkinson’s disease --- Box and Block test --- inertial sensors network --- biomechanics analysis --- kinematic data --- hand trajectories --- kinematic --- inertial measurement units --- angle-angle diagrams --- cyclograms --- obesity --- bradykinesia --- real-life --- naturalistic monitoring --- motor fluctuation --- wearable movement sensor --- IMU --- motion capture --- reliability --- clinical --- orthopedic --- sensory–motor gait disorders --- limb prosthesis --- spatial–temporal analysis --- symmetry index --- walking --- 6-min walking test --- wearable system --- inertial sensor --- RGB-D sensors --- optoelectronic system --- movement analysis --- hemiparesis --- n/a --- Parkinson's disease --- sensory-motor gait disorders --- spatial-temporal analysis