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Book
Wearables for Movement Analysis in Healthcare
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Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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.

Keywords

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


Book
Wearables for Movement Analysis in Healthcare
Authors: ---
Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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.


Book
Wearables for Movement Analysis in Healthcare
Authors: ---
Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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.


Book
Sensors for Gait, Posture, and Health Monitoring Volume 2
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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

Keywords

Humanities --- Social interaction --- 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


Book
Sensors for Gait, Posture, and Health Monitoring Volume 3
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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

Keywords

Humanities --- Social interaction --- 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


Book
Sensors for Gait, Posture, and Health Monitoring Volume 1
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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

Keywords

History of engineering & technology --- 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


Book
Sensors for Gait, Posture, and Health Monitoring Volume 3
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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

Keywords

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


Book
Sensors for Gait, Posture, and Health Monitoring Volume 2
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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

Keywords

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


Book
Sensors for Gait, Posture, and Health Monitoring Volume 1
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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

Keywords

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


Book
Sensors for Gait, Posture, and Health Monitoring Volume 3
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

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Bookmark

Abstract

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

Keywords

Humanities --- Social interaction --- 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 --- 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

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