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The aging population and the increased prevalence of neurological diseases have raised the issue of gait and balance disorders as a major public concern worldwide. Indeed, gait and balance disorders are responsible for a high healthcare and economic burden on society, thus, requiring new solutions to prevent harmful consequences. Recently, wearable sensors have provided new challenges and opportunities to address this issue through innovative diagnostic and therapeutic strategies. Accordingly, the book “Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders” collects the most up-to-date information about the objective evaluation of gait and balance disorders, by means of wearable biosensors, in patients with various types of neurological diseases, including Parkinson’s disease, multiple sclerosis, stroke, traumatic brain injury, and cerebellar ataxia. By adopting wearable technologies, the sixteen original research articles and reviews included in this book offer an updated overview of the most recent approaches for the objective evaluation of gait and balance disorders.

History of engineering & technology --- inertial measurement units --- gait analysis --- biomedical signal processing --- pattern recognition --- step detection --- physiological signals --- Parkinson’s disease --- pathological gait --- turning analysis --- wearable sensors --- mobile gait analysis --- wearables --- inertial sensors --- traumatic brain injury --- dynamic balance --- gait disorders --- gait patterns --- head injury --- gait symmetry --- gait smoothness --- acceleration --- machine learning --- classification --- accelerometer --- GAITRite --- multi-regression normalization --- SVM --- random forest classifier --- balance --- gait --- transcranial direct current stimulation --- wearable electronics --- IMUs --- cueing --- posture --- rehabilitation --- cerebellar ataxia --- movement analysis --- personalized medicine --- stroke --- asymmetry --- trunk --- reliability --- validity --- aging --- reactive postural responses --- yaw perturbation --- kinematics --- postural stability --- dynamic posturography --- multiple sclerosis --- gait metrics --- test-retest reliability --- sampling frequency --- accelerometry --- autocorrelation --- harmonic ratio --- six-minute walk --- back school --- inertial sensor --- lower back pain --- stability --- timed up and go test --- gait assessment --- tri-axial accelerometer --- CV --- healthy subjects --- test-retest --- trajectory reconstruction --- stride segmentation --- dynamic time warping --- pedestrian dead-reckoning --- near falls --- loss of balance --- pre-impact fall detection --- activities of daily life --- bio-signals --- EEG --- EMG --- wireless sensors --- posturography --- Alzheimer’s disease --- vestibular syndrome --- diagnosis --- symptoms monitoring --- wearable --- home-monitoring --- inertial measurement units --- gait analysis --- biomedical signal processing --- pattern recognition --- step detection --- physiological signals --- Parkinson’s disease --- pathological gait --- turning analysis --- wearable sensors --- mobile gait analysis --- wearables --- inertial sensors --- traumatic brain injury --- dynamic balance --- gait disorders --- gait patterns --- head injury --- gait symmetry --- gait smoothness --- acceleration --- machine learning --- classification --- accelerometer --- GAITRite --- multi-regression normalization --- SVM --- random forest classifier --- balance --- gait --- transcranial direct current stimulation --- wearable electronics --- IMUs --- cueing --- posture --- rehabilitation --- cerebellar ataxia --- movement analysis --- personalized medicine --- stroke --- asymmetry --- trunk --- reliability --- validity --- aging --- reactive postural responses --- yaw perturbation --- kinematics --- postural stability --- dynamic posturography --- multiple sclerosis --- gait metrics --- test-retest reliability --- sampling frequency --- accelerometry --- autocorrelation --- harmonic ratio --- six-minute walk --- back school --- inertial sensor --- lower back pain --- stability --- timed up and go test --- gait assessment --- tri-axial accelerometer --- CV --- healthy subjects --- test-retest --- trajectory reconstruction --- stride segmentation --- dynamic time warping --- pedestrian dead-reckoning --- near falls --- loss of balance --- pre-impact fall detection --- activities of daily life --- bio-signals --- EEG --- EMG --- wireless sensors --- posturography --- Alzheimer’s disease --- vestibular syndrome --- diagnosis --- symptoms monitoring --- wearable --- home-monitoring

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Visible light communication (VLC) using light-emitting diodes (LEDs) or laser diodes (LDs) has been envisioned as one of the key enabling technologies for 6G and Internet of Things (IoT) systems, owing to its appealing advantages, including abundant and unregulated spectrum resources, no electromagnetic interference (EMI) radiation and high security. However, despite its many advantages, VLC faces several technical challenges, such as the limited bandwidth and severe nonlinearity of opto-electronic devices, link blockage and user mobility. Therefore, significant efforts are needed from the global VLC community to develop VLC technology further. This Special Issue, “Visible Light Communication (VLC)”, provides an opportunity for global researchers to share their new ideas and cutting-edge techniques to address the above-mentioned challenges. The 16 papers published in this Special Issue represent the fascinating progress of VLC in various contexts, including general indoor and underwater scenarios, and the emerging application of machine learning/artificial intelligence (ML/AI) techniques in VLC.

Technology: general issues --- History of engineering & technology --- visible light communication (VLC) --- dimming control --- constant transmission efficiency --- error performance --- light-emitting diode (LED) --- visible light communications --- deep learning --- bit error rate --- orthogonal frequency division multiplexing --- index modulation --- POF --- FSO --- LiFi --- LED --- orthogonal frequency division multiplexing (OFDM) --- power efficiency --- peak-to-average-power ratio (PAPR) --- pre-distorted enhanced --- underwater optical wireless communication (UOWC) --- ADO-OFDM --- gamma–gamma function --- full-duplex --- long-reach --- photon counting --- vehicular visible light communication (VVLC) --- intelligent reflecting surface (IRS) --- the number of mirrors --- energy efficiency (EE) --- carrierless amplitude and phase (CAP) modulation --- pairwise coding (PWC) --- dual-mode index modulation (DM) --- chaotic encryption --- visible light positioning (VLP) --- free-space communication --- RGB LED --- non-orthogonal multiple access (NOMA) --- superposition constellation adjustment --- successive interference cancellation --- bit error ratio --- NOMA triangle --- underwater wireless optical communication --- temporal dispersion --- bandwidth limitation --- Monte Carlo method --- maximum likelihood sequence estimation --- visible light communication --- nonlinear equalization --- reservoir computing --- neural network (NN) --- autoencoder (AE) --- transceiver design --- nonlinearity --- VLC --- predistortion --- coefficient approximation --- BLSTM --- orthogonal frequency-division multiplexing --- sampling frequency offset --- visible light communications (VLC) --- mmWave communications --- channel modeling --- channel propagation characteristics --- path loss --- delay spread (DS) --- Ricean K-factor --- cluster characteristics --- n/a --- gamma-gamma function

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The aging population and the increased prevalence of neurological diseases have raised the issue of gait and balance disorders as a major public concern worldwide. Indeed, gait and balance disorders are responsible for a high healthcare and economic burden on society, thus, requiring new solutions to prevent harmful consequences. Recently, wearable sensors have provided new challenges and opportunities to address this issue through innovative diagnostic and therapeutic strategies. Accordingly, the book “Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders” collects the most up-to-date information about the objective evaluation of gait and balance disorders, by means of wearable biosensors, in patients with various types of neurological diseases, including Parkinson’s disease, multiple sclerosis, stroke, traumatic brain injury, and cerebellar ataxia. By adopting wearable technologies, the sixteen original research articles and reviews included in this book offer an updated overview of the most recent approaches for the objective evaluation of gait and balance disorders.

inertial measurement units --- gait analysis --- biomedical signal processing --- pattern recognition --- step detection --- physiological signals --- Parkinson’s disease --- pathological gait --- turning analysis --- wearable sensors --- mobile gait analysis --- wearables --- inertial sensors --- traumatic brain injury --- dynamic balance --- gait disorders --- gait patterns --- head injury --- gait symmetry --- gait smoothness --- acceleration --- machine learning --- classification --- accelerometer --- GAITRite --- multi-regression normalization --- SVM --- random forest classifier --- balance --- gait --- transcranial direct current stimulation --- wearable electronics --- IMUs --- cueing --- posture --- rehabilitation --- cerebellar ataxia --- movement analysis --- personalized medicine --- stroke --- asymmetry --- trunk --- reliability --- validity --- aging --- reactive postural responses --- yaw perturbation --- kinematics --- postural stability --- dynamic posturography --- multiple sclerosis --- gait metrics --- test-retest reliability --- sampling frequency --- accelerometry --- autocorrelation --- harmonic ratio --- six-minute walk --- back school --- inertial sensor --- lower back pain --- stability --- timed up and go test --- gait assessment --- tri-axial accelerometer --- CV --- healthy subjects --- test-retest --- trajectory reconstruction --- stride segmentation --- dynamic time warping --- pedestrian dead-reckoning --- near falls --- loss of balance --- pre-impact fall detection --- activities of daily life --- bio-signals --- EEG --- EMG --- wireless sensors --- posturography --- Alzheimer’s disease --- vestibular syndrome --- diagnosis --- symptoms monitoring --- wearable --- home-monitoring