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The basal ganglia has received much attention over the last two decades, as it has been implicated in many neurological and psychiatric disorders. Most of this research—in both animals and humans—attempt to understand the neural and biochemical substrates of basic motor and learning processes, and how these are affected in human patients as well as animal models of brain disorders. The current volume contains research articles and reviews describing basic, pre-clinical and clinical neuroscience research of the basal ganglia written by attendees of the 11th Triennial Meeting of the International Basal Ganglia Society (IBAGS) that was held March 3-7th, 2013 at the Princess Hotel, Eilat, Israel and by researchers of the basal ganglia. Specifically, articles in this volume include research reports on the biochemistry, computational theory, anatomy and physiology of single neurons and functional circuitry of the basal ganglia networks as well as the latest data on animal models of basal ganglia dysfunction and clinical studies in human patients.
Basal ganglia --- Computational neuroscience --- Neurobiology --- Basal Ganglia --- Physiology. --- Research. --- Mathematical models. --- physiopathology. --- Subthalamic Nucleus --- dopaime --- Parkinson's disease (PD) --- human imagine studies --- animal studies --- computational modeling
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The contribution of genomic variants to the aetiopathogenesis of both paediatric and adult neurological disease is being increasingly recognized. The use of next-generation sequencing has led to the discovery of novel neurodevelopmental disorders, as exemplified by the deciphering developmental disorders (DDD) study, and provided insight into the aetiopathogenesis of common adult neurological diseases. Despite these advances, many challenges remain. Correctly classifying the pathogenicity of genomic variants from amongst the large number of variants identified by next-generation sequencing is recognized as perhaps the major challenge facing the field. Deep phenotyping (e.g., imaging, movement analysis) techniques can aid variant interpretation by correctly classifying individuals as affected or unaffected for segregation studies. The lack of information on the clinical phenotype of novel genetic subtypes of neurological disease creates limitations for genetic counselling. Both deep phenotyping and qualitative studies can capture the clinical and patient’s perspective on a disease and provide valuable information. This Special Issue aims to highlight how next-generation sequencing techniques have revolutionised our understanding of the aetiology of brain disease and describe the contribution of deep phenotyping studies to a variant interpretation and understanding of natural history.
polymicrogyria --- n/a --- neurodegenerative disease --- next generation sequencing (NGS) --- inborn error of metabolism --- genetic biomarker --- deep learning --- TUBA1A --- Alzheimer’s disease (AD) --- ataxia --- risk prediction --- p.(Arg2His) --- movement science --- tubulin --- R2H --- diagnosis --- machine learning --- metal storage disorders --- amyotrophic lateral sclerosis (ALS) --- glucocerebrosidase --- Parkinsonism --- cerebellar hypoplasia --- Gaucher disease --- disease phenotyping --- tubulinopathy --- Parkinson’s disease (PD) --- dementia --- Parkinson’s disease --- Neurogenetics. --- Nervous system --- Genetics --- Neurosciences --- Genetic aspects --- Alzheimer's disease (AD) --- Parkinson's disease (PD) --- Parkinson's disease
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Neurodegenerative diseases, including Alzheimer’s, Parkinson’s, Huntington’s, and amyotrophic lateral sclerosis, are the most common pathologies of the central nervous system currently without a cure. They share common molecular and cellular characteristics, including protein misfolding, mitochondrial dysfunction, glutamate toxicity, dysregulation of calcium homeostasis, oxidative stress, inflammation, and ageing, which contribute to neuronal death. Efforts to treat these diseases are often limited by their multifactorial etiology. Natural products, thanks to their multitarget activities, are considered promising alternatives for the treatment of neurodegeneration. This book deals with two different forms of natural products: extracts and isolated compounds. The study of the bioactivity of the extracts is extremely important as many studies have demonstrated the synergistic effect of the combination of different natural products. On the other hand, the investigation of the activity of specifically isolated natural products can be also important to understand their cellular and molecular mechanisms and to define the specific bioactive components in extracts or foods. This book can be considered an important contribution to knowledge of the neuroprotective effect of natural products and presents a great deal of information, related to both the benefits but also the limitations of their use in counteracting neurodegeneration.
Vitamin D --- Multiple Sclerosis --- symptom --- neurodegeneration --- oxidative injury --- Parkinson’s disease --- terpenes, rotenone --- thymol --- Alzheimer’s disease --- Centella asiatica --- hippocampus --- protein poshophatase 2 --- glycogen synthase kinase 3 --- B-cell lymphoma 2 --- neuroprotection --- nutraceuticals --- bioavailability --- stress response --- neurodegenerative disease --- bioactive compound --- natural extract --- β-amyloid peptide --- tau protein --- clinical trial --- human studies --- animal studies --- in vitro studies --- curcumin --- free radicals --- heme oxygenase --- safety profile --- type 2 diabetes --- inflammation --- vascular damage --- learning --- memory --- natural compound --- oxidative stress --- cognitive dysfunction --- cell death --- synapse loss --- protein aggregation --- neuroinflammation --- algae --- seaweeds --- neurodegenerative diseases --- auraptene --- dopamine neuron --- antioxidant --- mitochondria --- Chionanthus retusus --- flavonoid --- flower --- HO-1 --- NO --- Lippia citriodora --- VEE --- Vs --- relaxation --- depression --- cyclic AMP --- calcium --- blood–brain barrier --- catechin --- cognition --- epigallocatechin gallate --- green tea --- microbiota --- 5-(3,5-dihydroxyphenyl)-γ-valerolactone --- ascaroside pheromone --- C. elegans --- dauer --- neuronal signaling --- sexual behavior --- survival signals --- proteostasis --- chaperones --- autophagy --- ubiquitin-proteasome --- unfolded protein response --- natural compounds --- natural products --- ethics --- patients’ autonomy --- beneficence --- nonmaleficence --- medical liability --- Parkinson’s disease (PD) --- mitochondrial dysfunction --- dynamics --- hormesis --- ubiquitin‒proteasome system (UPS) --- mitophagy --- n/a --- Parkinson's disease --- Alzheimer's disease --- blood-brain barrier --- patients' autonomy --- Parkinson's disease (PD)
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Continuous research advances have been observed in the field of environmentally-friendly polymers and polymer composites due to the dependence of polymers on fossil fuels and the sustainability issues related to plastic wastes. This book compiles the most recent research works in biopolymers, their blends and composites, and the use of natural additives, such as vegetable oils and other renewable and waste-derived liquids, with their marked environmental efficiency devoted to developing novel sustainable materials. Therefore, Environmentally Friendly Polymers and Polymer Composites provides an overview to scientists of the potential of these environmentally friendly materials and helps engineers to apply these new materials for industrial purposes.
PLA --- PCL --- TPS --- biopolymer blends --- mechanical properties --- compostable plastics --- green composites --- natural fillers --- poly(butylene succinate) (PBS) --- almond shell flour (ASF) --- poly (lactic acid) (PLA) --- poly(butylene succinate-co-adipate) (PBSA) --- binary blends --- shape memory behaviour --- polymer‒matrix composites (PMCs) --- thermomechanical --- electron microscopy --- compatibilizers --- poly(lactic acid) (PLA) --- natural fibre (NF) --- nano-hydroxyapatite (nHA) --- flammability --- crab shell --- chitin --- spherical microgels --- reverse micelle --- gelation --- chitosan (CS) --- anti-oxidant --- anti-apoptotic activity --- rotenone --- Parkinson’s disease (PD) --- composite materials --- hybrid resin --- natural reinforcement --- non-uniformities --- mechanical behavior --- antifungal activity --- dendrimer --- Origanum majorana L. essential oil --- Phytophthora infestans --- maleinized linseed oil MLO --- poly(lactic acid) --- diatomaceous earth --- biocomposites --- active containers --- polymer mixtures --- blends --- cashew nut shell liquid (CNSL) --- polypropylene --- high impact polystyrene --- compatibilization --- PHB --- PHBV --- rice husk --- biosustainability --- waste valorization --- bacterial cellulose --- natural rubber --- reinforcing --- biodegradable polymers --- Arboform --- epoxidized oil --- maleinized linseed oil --- toughness --- thermal stability --- pectin --- food packaging --- active compounds --- agro-waste residues --- circular economy --- graphene oxide --- size selection --- sodium alginate --- bio-based polymers --- biodegradable polyesters --- wood plastic composites --- natural additives and fillers --- composites characterization --- bioplastics manufacturing
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In recent years, many technologies for gait and posture assessments have emerged. Wearable sensors, active and passive in-house monitors, and many combinations thereof all promise to provide accurate measures of physical activity, gait, and posture parameters. Motivated by market projections for wearable technologies and driven by recent technological innovations in wearable sensors (MEMs, electronic textiles, wireless communications, etc.), wearable health/performance research is growing rapidly and has the potential to transform future healthcare from disease treatment to disease prevention. The objective of this Special Issue is to address and disseminate the latest gait, posture, and activity monitoring systems as well as various mathematical models/methods that characterize mobility functions. This Special Issue focuses on wearable monitoring systems and physical sensors, and its mathematical models can be utilized in varied environments under varied conditions to monitor health and performance
step detection --- machine learning --- outlier detection --- transition matrices --- autoencoders --- ground reaction force (GRF) --- micro electro mechanical systems (MEMS) --- gait --- walk --- bipedal locomotion --- 3-axis force sensor --- shoe --- force distribution --- multi-sensor gait classification --- distributed compressed sensing --- joint sparse representation classification --- telemonitoring of gait --- operating range --- accelerometer --- stride length --- peak tibial acceleration --- running velocity --- wearable sensors --- feedback technology --- rehabilitation --- motor control --- cerebral palsy --- inertial sensors --- gait events --- spatiotemporal parameters --- postural control --- falls in the elderly --- fall risk assessment --- low-cost instrumented insoles --- foot plantar center of pressure --- flexible sensor --- gait recognition --- piezoelectric material --- wearable --- adaptability --- force sensitive resistors --- self-tuning triple threshold algorithm --- sweat sensor --- sweat rate --- dehydration --- IoT --- PDMS --- surface electromyography --- handgrip force --- force-varying muscle contraction --- nonlinear analysis --- wavelet scale selection --- inertial measurement unit --- gyroscope --- asymmetry --- feature extraction --- gait analysis --- lower limb prosthesis --- trans-femoral amputee --- MR damper --- knee damping control --- inertial measurement units --- motion analysis --- kinematics --- functional activity --- repeatability --- reliability --- biomechanics --- cognitive frailty --- cognitive–motor impairment --- Alzheimer’s disease --- motor planning error --- instrumented trail-making task --- ankle reaching task --- dual task walking --- nondestructive --- joint moment --- partial weight loading --- muscle contributions --- sit-to-stand training --- motion parameters --- step length --- self-adaptation --- Parkinson’s disease (PD) --- tremor dominant (TD) --- postural instability and gait difficulty (PIGD) --- center of pressure (COP) --- fast Fourier transform (FFT) --- wavelet transform (WT) --- fall detection system --- smartphones --- accelerometers --- machine learning algorithms --- supervised learning --- ANOVA analysis --- Step-detection --- ActiGraph --- Pedometer --- acceleration --- physical activity --- physical function --- physical performance test --- chair stand --- sit to stand transfer --- wearables --- gyroscopes --- e-Health application --- physical rehabilitation --- shear and plantar pressure sensor --- biaxial optical fiber sensor --- multiplexed fiber Bragg gratings --- frailty --- pre-frail --- wearable sensor --- sedentary behavior --- moderate-to-vigorous activity --- steps --- fall detection --- elderly people monitoring --- telerehabilitation --- virtual therapy --- Kinect --- eHealth --- telemedicine --- insole --- injury prevention --- biomechanical gait variable estimation --- inertial gait variable --- total knee arthroplasty --- falls in healthy elderly --- fall prevention --- biometrics --- human gait recognition --- ground reaction forces --- Microsoft Kinect --- high heels --- fusion data --- ensemble classifiers --- accidental falls --- older adults --- neural networks --- convolutional neural network --- long short-term memory --- accelerometry --- obesity --- nonlinear --- electrostatic field sensing --- gait measurement --- temporal parameters --- artificial neural network --- propulsion --- aging --- walking --- smart footwear --- frailty prediction --- fall risk --- smartphone based assessments --- adverse post-operative outcome --- intelligent surveillance systems --- human fall detection --- health and well-being --- safety and security --- n/a --- movement control --- anterior cruciate ligament --- kinetics --- real-time feedback --- biomechanical gait features --- impaired gait classification --- pattern recognition --- sensors --- clinical --- knee --- osteoarthritis --- shear stress --- callus --- woman --- TUG --- IMU --- geriatric assessment --- semi-unsupervised --- self-assessment --- domestic environment --- functional decline --- symmetry --- trunk movement --- autocorrelation --- gait rehabilitation --- wearable device --- IMU sensors --- gait classification --- stroke patients --- neurological disorders --- scanning laser rangefinders (SLR), GAITRite --- cadence --- velocity and stride-length --- power --- angular velocity --- human motion measurement --- sensor fusion --- complementary filter --- fuzzy logic --- inertial and magnetic sensors --- ESOQ-2 --- Parkinson’s disease --- UPDRS --- movement disorders --- human computer interface --- RGB-Depth --- hand tracking --- automated assessment --- at-home monitoring --- Parkinson’s Diseases --- motorized walker --- haptic cue --- gait pattern --- statistics study --- walk detection --- step counting --- signal processing --- plantar pressure --- flat foot --- insoles --- force sensors --- arch index --- sports analytics --- deep learning --- classification --- inertial sensor --- cross-country skiing --- classical style --- skating style --- batteryless strain sensor --- wireless strain sensor --- resonant frequency modulation --- Ecoflex --- human activity recognition --- smartphone --- human daily activity --- ensemble method --- running --- velocity --- smart shoe --- concussion --- inertial motion units (IMUs) --- vestibular exercises --- validation --- motion capture --- user intent recognition --- transfemoral prosthesis --- multi-objective optimization --- biogeography-based optimization --- smart cane --- weight-bearing --- health monitoring --- wearable/inertial sensors --- regularity --- variability --- human --- motion --- locomotion --- UPDRS tasks --- posture --- postural stability --- center of mass --- RGB-depth --- neurorehabilitation --- hallux abductus valgus --- high heel --- proximal phalanx of the hallux --- abduction --- valgus --- ultrasonography --- Achilles tendon --- diagnostic --- imaging --- tendinopathy --- foot insoles --- electromyography --- joint instability --- muscle contractions --- motorcycling --- wearable electronic devices --- validity --- relative movement --- lower limb prosthetics --- biomechanic measurement tasks --- quantifying socket fit --- rehabilitation exercise --- dynamic time warping --- automatic coaching --- exergame --- fine-wire intramuscular EMG electrode --- non-human primate model --- traumatic spinal cord injury --- wavelet transform --- relative power --- linear mixed model --- VO2 --- calibration --- MET --- VO2net --- speed --- equivalent speed --- free-living --- children --- adolescents --- adults --- gait event detection --- hemiplegic gait --- appropriate mother wavelet --- acceleration signal --- wavelet-selection criteria --- conductive textile --- stroke --- hemiparetic --- real-time monitoring --- lower limb locomotion activity --- triplet Markov model --- semi-Markov model --- on-line EM algorithm --- human kinematics --- phase difference angle --- cognitive-motor impairment --- Alzheimer's disease --- Parkinson's disease (PD) --- Parkinson's disease --- Parkinson's Diseases
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In recent years, many technologies for gait and posture assessments have emerged. Wearable sensors, active and passive in-house monitors, and many combinations thereof all promise to provide accurate measures of physical activity, gait, and posture parameters. Motivated by market projections for wearable technologies and driven by recent technological innovations in wearable sensors (MEMs, electronic textiles, wireless communications, etc.), wearable health/performance research is growing rapidly and has the potential to transform future healthcare from disease treatment to disease prevention. The objective of this Special Issue is to address and disseminate the latest gait, posture, and activity monitoring systems as well as various mathematical models/methods that characterize mobility functions. This Special Issue focuses on wearable monitoring systems and physical sensors, and its mathematical models can be utilized in varied environments under varied conditions to monitor health and performance
step detection --- machine learning --- outlier detection --- transition matrices --- autoencoders --- ground reaction force (GRF) --- micro electro mechanical systems (MEMS) --- gait --- walk --- bipedal locomotion --- 3-axis force sensor --- shoe --- force distribution --- multi-sensor gait classification --- distributed compressed sensing --- joint sparse representation classification --- telemonitoring of gait --- operating range --- accelerometer --- stride length --- peak tibial acceleration --- running velocity --- wearable sensors --- feedback technology --- rehabilitation --- motor control --- cerebral palsy --- inertial sensors --- gait events --- spatiotemporal parameters --- postural control --- falls in the elderly --- fall risk assessment --- low-cost instrumented insoles --- foot plantar center of pressure --- flexible sensor --- gait recognition --- piezoelectric material --- wearable --- adaptability --- force sensitive resistors --- self-tuning triple threshold algorithm --- sweat sensor --- sweat rate --- dehydration --- IoT --- PDMS --- surface electromyography --- handgrip force --- force-varying muscle contraction --- nonlinear analysis --- wavelet scale selection --- inertial measurement unit --- gyroscope --- asymmetry --- feature extraction --- gait analysis --- lower limb prosthesis --- trans-femoral amputee --- MR damper --- knee damping control --- inertial measurement units --- motion analysis --- kinematics --- functional activity --- repeatability --- reliability --- biomechanics --- cognitive frailty --- cognitive–motor impairment --- Alzheimer’s disease --- motor planning error --- instrumented trail-making task --- ankle reaching task --- dual task walking --- nondestructive --- joint moment --- partial weight loading --- muscle contributions --- sit-to-stand training --- motion parameters --- step length --- self-adaptation --- Parkinson’s disease (PD) --- tremor dominant (TD) --- postural instability and gait difficulty (PIGD) --- center of pressure (COP) --- fast Fourier transform (FFT) --- wavelet transform (WT) --- fall detection system --- smartphones --- accelerometers --- machine learning algorithms --- supervised learning --- ANOVA analysis --- Step-detection --- ActiGraph --- Pedometer --- acceleration --- physical activity --- physical function --- physical performance test --- chair stand --- sit to stand transfer --- wearables --- gyroscopes --- e-Health application --- physical rehabilitation --- shear and plantar pressure sensor --- biaxial optical fiber sensor --- multiplexed fiber Bragg gratings --- frailty --- pre-frail --- wearable sensor --- sedentary behavior --- moderate-to-vigorous activity --- steps --- fall detection --- elderly people monitoring --- telerehabilitation --- virtual therapy --- Kinect --- eHealth --- telemedicine --- insole --- injury prevention --- biomechanical gait variable estimation --- inertial gait variable --- total knee arthroplasty --- falls in healthy elderly --- fall prevention --- biometrics --- human gait recognition --- ground reaction forces --- Microsoft Kinect --- high heels --- fusion data --- ensemble classifiers --- accidental falls --- older adults --- neural networks --- convolutional neural network --- long short-term memory --- accelerometry --- obesity --- nonlinear --- electrostatic field sensing --- gait measurement --- temporal parameters --- artificial neural network --- propulsion --- aging --- walking --- smart footwear --- frailty prediction --- fall risk --- smartphone based assessments --- adverse post-operative outcome --- intelligent surveillance systems --- human fall detection --- health and well-being --- safety and security --- n/a --- movement control --- anterior cruciate ligament --- kinetics --- real-time feedback --- biomechanical gait features --- impaired gait classification --- pattern recognition --- sensors --- clinical --- knee --- osteoarthritis --- shear stress --- callus --- woman --- TUG --- IMU --- geriatric assessment --- semi-unsupervised --- self-assessment --- domestic environment --- functional decline --- symmetry --- trunk movement --- autocorrelation --- gait rehabilitation --- wearable device --- IMU sensors --- gait classification --- stroke patients --- neurological disorders --- scanning laser rangefinders (SLR), GAITRite --- cadence --- velocity and stride-length --- power --- angular velocity --- human motion measurement --- sensor fusion --- complementary filter --- fuzzy logic --- inertial and magnetic sensors --- ESOQ-2 --- Parkinson’s disease --- UPDRS --- movement disorders --- human computer interface --- RGB-Depth --- hand tracking --- automated assessment --- at-home monitoring --- Parkinson’s Diseases --- motorized walker --- haptic cue --- gait pattern --- statistics study --- walk detection --- step counting --- signal processing --- plantar pressure --- flat foot --- insoles --- force sensors --- arch index --- sports analytics --- deep learning --- classification --- inertial sensor --- cross-country skiing --- classical style --- skating style --- batteryless strain sensor --- wireless strain sensor --- resonant frequency modulation --- Ecoflex --- human activity recognition --- smartphone --- human daily activity --- ensemble method --- running --- velocity --- smart shoe --- concussion --- inertial motion units (IMUs) --- vestibular exercises --- validation --- motion capture --- user intent recognition --- transfemoral prosthesis --- multi-objective optimization --- biogeography-based optimization --- smart cane --- weight-bearing --- health monitoring --- wearable/inertial sensors --- regularity --- variability --- human --- motion --- locomotion --- UPDRS tasks --- posture --- postural stability --- center of mass --- RGB-depth --- neurorehabilitation --- hallux abductus valgus --- high heel --- proximal phalanx of the hallux --- abduction --- valgus --- ultrasonography --- Achilles tendon --- diagnostic --- imaging --- tendinopathy --- foot insoles --- electromyography --- joint instability --- muscle contractions --- motorcycling --- wearable electronic devices --- validity --- relative movement --- lower limb prosthetics --- biomechanic measurement tasks --- quantifying socket fit --- rehabilitation exercise --- dynamic time warping --- automatic coaching --- exergame --- fine-wire intramuscular EMG electrode --- non-human primate model --- traumatic spinal cord injury --- wavelet transform --- relative power --- linear mixed model --- VO2 --- calibration --- MET --- VO2net --- speed --- equivalent speed --- free-living --- children --- adolescents --- adults --- gait event detection --- hemiplegic gait --- appropriate mother wavelet --- acceleration signal --- wavelet-selection criteria --- conductive textile --- stroke --- hemiparetic --- real-time monitoring --- lower limb locomotion activity --- triplet Markov model --- semi-Markov model --- on-line EM algorithm --- human kinematics --- phase difference angle --- cognitive-motor impairment --- Alzheimer's disease --- Parkinson's disease (PD) --- Parkinson's disease --- Parkinson's Diseases
Choose an application
In recent years, many technologies for gait and posture assessments have emerged. Wearable sensors, active and passive in-house monitors, and many combinations thereof all promise to provide accurate measures of physical activity, gait, and posture parameters. Motivated by market projections for wearable technologies and driven by recent technological innovations in wearable sensors (MEMs, electronic textiles, wireless communications, etc.), wearable health/performance research is growing rapidly and has the potential to transform future healthcare from disease treatment to disease prevention. The objective of this Special Issue is to address and disseminate the latest gait, posture, and activity monitoring systems as well as various mathematical models/methods that characterize mobility functions. This Special Issue focuses on wearable monitoring systems and physical sensors, and its mathematical models can be utilized in varied environments under varied conditions to monitor health and performance
step detection --- machine learning --- outlier detection --- transition matrices --- autoencoders --- ground reaction force (GRF) --- micro electro mechanical systems (MEMS) --- gait --- walk --- bipedal locomotion --- 3-axis force sensor --- shoe --- force distribution --- multi-sensor gait classification --- distributed compressed sensing --- joint sparse representation classification --- telemonitoring of gait --- operating range --- accelerometer --- stride length --- peak tibial acceleration --- running velocity --- wearable sensors --- feedback technology --- rehabilitation --- motor control --- cerebral palsy --- inertial sensors --- gait events --- spatiotemporal parameters --- postural control --- falls in the elderly --- fall risk assessment --- low-cost instrumented insoles --- foot plantar center of pressure --- flexible sensor --- gait recognition --- piezoelectric material --- wearable --- adaptability --- force sensitive resistors --- self-tuning triple threshold algorithm --- sweat sensor --- sweat rate --- dehydration --- IoT --- PDMS --- surface electromyography --- handgrip force --- force-varying muscle contraction --- nonlinear analysis --- wavelet scale selection --- inertial measurement unit --- gyroscope --- asymmetry --- feature extraction --- gait analysis --- lower limb prosthesis --- trans-femoral amputee --- MR damper --- knee damping control --- inertial measurement units --- motion analysis --- kinematics --- functional activity --- repeatability --- reliability --- biomechanics --- cognitive frailty --- cognitive–motor impairment --- Alzheimer’s disease --- motor planning error --- instrumented trail-making task --- ankle reaching task --- dual task walking --- nondestructive --- joint moment --- partial weight loading --- muscle contributions --- sit-to-stand training --- motion parameters --- step length --- self-adaptation --- Parkinson’s disease (PD) --- tremor dominant (TD) --- postural instability and gait difficulty (PIGD) --- center of pressure (COP) --- fast Fourier transform (FFT) --- wavelet transform (WT) --- fall detection system --- smartphones --- accelerometers --- machine learning algorithms --- supervised learning --- ANOVA analysis --- Step-detection --- ActiGraph --- Pedometer --- acceleration --- physical activity --- physical function --- physical performance test --- chair stand --- sit to stand transfer --- wearables --- gyroscopes --- e-Health application --- physical rehabilitation --- shear and plantar pressure sensor --- biaxial optical fiber sensor --- multiplexed fiber Bragg gratings --- frailty --- pre-frail --- wearable sensor --- sedentary behavior --- moderate-to-vigorous activity --- steps --- fall detection --- elderly people monitoring --- telerehabilitation --- virtual therapy --- Kinect --- eHealth --- telemedicine --- insole --- injury prevention --- biomechanical gait variable estimation --- inertial gait variable --- total knee arthroplasty --- falls in healthy elderly --- fall prevention --- biometrics --- human gait recognition --- ground reaction forces --- Microsoft Kinect --- high heels --- fusion data --- ensemble classifiers --- accidental falls --- older adults --- neural networks --- convolutional neural network --- long short-term memory --- accelerometry --- obesity --- nonlinear --- electrostatic field sensing --- gait measurement --- temporal parameters --- artificial neural network --- propulsion --- aging --- walking --- smart footwear --- frailty prediction --- fall risk --- smartphone based assessments --- adverse post-operative outcome --- intelligent surveillance systems --- human fall detection --- health and well-being --- safety and security --- n/a --- movement control --- anterior cruciate ligament --- kinetics --- real-time feedback --- biomechanical gait features --- impaired gait classification --- pattern recognition --- sensors --- clinical --- knee --- osteoarthritis --- shear stress --- callus --- woman --- TUG --- IMU --- geriatric assessment --- semi-unsupervised --- self-assessment --- domestic environment --- functional decline --- symmetry --- trunk movement --- autocorrelation --- gait rehabilitation --- wearable device --- IMU sensors --- gait classification --- stroke patients --- neurological disorders --- scanning laser rangefinders (SLR), GAITRite --- cadence --- velocity and stride-length --- power --- angular velocity --- human motion measurement --- sensor fusion --- complementary filter --- fuzzy logic --- inertial and magnetic sensors --- ESOQ-2 --- Parkinson’s disease --- UPDRS --- movement disorders --- human computer interface --- RGB-Depth --- hand tracking --- automated assessment --- at-home monitoring --- Parkinson’s Diseases --- motorized walker --- haptic cue --- gait pattern --- statistics study --- walk detection --- step counting --- signal processing --- plantar pressure --- flat foot --- insoles --- force sensors --- arch index --- sports analytics --- deep learning --- classification --- inertial sensor --- cross-country skiing --- classical style --- skating style --- batteryless strain sensor --- wireless strain sensor --- resonant frequency modulation --- Ecoflex --- human activity recognition --- smartphone --- human daily activity --- ensemble method --- running --- velocity --- smart shoe --- concussion --- inertial motion units (IMUs) --- vestibular exercises --- validation --- motion capture --- user intent recognition --- transfemoral prosthesis --- multi-objective optimization --- biogeography-based optimization --- smart cane --- weight-bearing --- health monitoring --- wearable/inertial sensors --- regularity --- variability --- human --- motion --- locomotion --- UPDRS tasks --- posture --- postural stability --- center of mass --- RGB-depth --- neurorehabilitation --- hallux abductus valgus --- high heel --- proximal phalanx of the hallux --- abduction --- valgus --- ultrasonography --- Achilles tendon --- diagnostic --- imaging --- tendinopathy --- foot insoles --- electromyography --- joint instability --- muscle contractions --- motorcycling --- wearable electronic devices --- validity --- relative movement --- lower limb prosthetics --- biomechanic measurement tasks --- quantifying socket fit --- rehabilitation exercise --- dynamic time warping --- automatic coaching --- exergame --- fine-wire intramuscular EMG electrode --- non-human primate model --- traumatic spinal cord injury --- wavelet transform --- relative power --- linear mixed model --- VO2 --- calibration --- MET --- VO2net --- speed --- equivalent speed --- free-living --- children --- adolescents --- adults --- gait event detection --- hemiplegic gait --- appropriate mother wavelet --- acceleration signal --- wavelet-selection criteria --- conductive textile --- stroke --- hemiparetic --- real-time monitoring --- lower limb locomotion activity --- triplet Markov model --- semi-Markov model --- on-line EM algorithm --- human kinematics --- phase difference angle --- cognitive-motor impairment --- Alzheimer's disease --- Parkinson's disease (PD) --- Parkinson's disease --- Parkinson's Diseases
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