High-accuracy wearable detection of freezing of gait in Parkinson's disease based on pseudo-multimodal features.

[1]  Amir H. Gandomi,et al.  Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts , 2021, Expert Syst. Appl..

[2]  Adriana Dapena,et al.  Proposals and Comparisons from One-Sensor EEG and EOG Human-Machine Interfaces , 2021, Sensors.

[3]  Hantao Li Multimodal Dataset of Freezing of Gait in Parkinson's Disease , 2021 .

[4]  A. Suppa,et al.  Prediction of Freezing of Gait in Parkinson’s Disease Using Wearables and Machine Learning , 2021, Sensors.

[5]  Masudur R. Siddiquee,et al.  Neural Correlates of Freezing of Gait in Parkinson's Disease: An Electrophysiology Mini-Review , 2020, Frontiers in Neurology.

[6]  Dong Ming,et al.  Characterization of EEG Data Revealing Relationships With Cognitive and Motor Symptoms in Parkinson's Disease: A Systematic Review , 2020, Frontiers in Aging Neuroscience.

[7]  Huiling Chen,et al.  Slime mould algorithm: A new method for stochastic optimization , 2020, Future Gener. Comput. Syst..

[8]  Ying Wang,et al.  Freezing of gait detection in Parkinson’s disease via multimodal analysis of EEG and accelerometer signals , 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

[9]  B. Bloem,et al.  Integrated and patient-centred management of Parkinson's disease: a network model for reshaping chronic neurological care , 2020, The Lancet Neurology.

[10]  Lynn Rochester,et al.  Selecting Clinically Relevant Gait Characteristics for Classification of Early Parkinson’s Disease: A Comprehensive Machine Learning Approach , 2019, Scientific Reports.

[11]  Scott Makeig,et al.  Trial-by-trial source-resolved EEG responses to gait task challenges predict subsequent step adaptation , 2019, NeuroImage.

[12]  Aaron Miller,et al.  Towards Real-Time Prediction of Freezing of Gait in Patients With Parkinson’s Disease: Addressing the Class Imbalance Problem , 2019, Sensors.

[13]  Y. Li,et al.  The Detection of Freezing of Gait in Parkinson’s Disease Using Asymmetric Basis Function TV-ARMA Time–Frequency Spectral Estimation Method , 2019, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[14]  Hossam Faris,et al.  Harris hawks optimization: Algorithm and applications , 2019, Future Gener. Comput. Syst..

[15]  J. Kurths,et al.  Coupling Between Leg Muscle Activation and EEG During Normal Walking, Intentional Stops, and Freezing of Gait in Parkinson's Disease , 2019, Front. Physiol..

[16]  J. Volkmann,et al.  Freezing of gait in Parkinson’s disease reflects a sudden derangement of locomotor network dynamics , 2019, Brain : a journal of neurology.

[17]  Fernanda Irrera,et al.  Wearable Sensors System for an Improved Analysis of Freezing of Gait in Parkinson’s Disease Using Electromyography and Inertial Signals , 2019, Sensors.

[18]  Andrew M. Dai,et al.  Wearable sensors for Parkinson’s disease: which data are worth collecting for training symptom detection models , 2018, npj Digital Medicine.

[19]  Arnaud Delval,et al.  Motor Preparation of Step Initiation: Error-related Cortical Oscillations , 2018, Neuroscience.

[20]  Manuel Recuero,et al.  Short-Term Effects of Binaural Beats on EEG Power, Functional Connectivity, Cognition, Gait and Anxiety in Parkinson's Disease , 2017, Int. J. Neural Syst..

[21]  Stephen A. Billings,et al.  A New Proxy Measurement Algorithm with Application to the Estimation of Vertical Ground Reaction Forces Using Wearable Sensors , 2017, Sensors.

[22]  Aysegul Gunduz,et al.  Freezing-of-Gait detection using temporal, spatial, and physiological features with a support-vector-machine classifier , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[23]  Ganesh R. Naik,et al.  Detection of gait initiation Failure in Parkinson's disease based on wavelet transform and Support Vector Machine , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[24]  Andreu Català,et al.  Determining the optimal features in freezing of gait detection through a single waist accelerometer in home environments , 2017, Pattern Recognit. Lett..

[25]  Fernanda Irrera,et al.  Reliable and Robust Detection of Freezing of Gait Episodes With Wearable Electronic Devices , 2017, IEEE Sensors Journal.

[26]  Max A. Little,et al.  Freezing of gait and fall detection in Parkinson’s disease using wearable sensors: a systematic review , 2017, Journal of Neurology.

[27]  M. Hallett,et al.  Physiology of freezing of gait , 2016, Annals of neurology.

[28]  Gaige Wang,et al.  Moth search algorithm: a bio-inspired metaheuristic algorithm for global optimization problems , 2016, Memetic Computing.

[29]  S. Deb,et al.  Elephant Herding Optimization , 2015, 2015 3rd International Symposium on Computational and Business Intelligence (ISCBI).

[30]  Kang K. L. Liu,et al.  Network Physiology: How Organ Systems Dynamically Interact , 2015, PloS one.

[31]  Zhihua Cui,et al.  Monarch butterfly optimization , 2015, Neural Computing and Applications.

[32]  Thomas Foltynie,et al.  Parkinson’s disease dementia: a neural networks perspective , 2015, Brain : a journal of neurology.

[33]  Thomas Seidl,et al.  Prediction of freezing of gait from Parkinson's Disease movement time series using conditional random fields , 2014, HealthGIS '14.

[34]  Bernard Espiau,et al.  Detection of Freezing of Gait in Parkinson Disease: Preliminary Results , 2014, Sensors.

[35]  J. M. Shine,et al.  Abnormal patterns of theta frequency oscillations during the temporal evolution of freezing of gait in Parkinson’s disease , 2014, Clinical Neurophysiology.

[36]  B. Bloem,et al.  Quantitative wearable sensors for objective assessment of Parkinson's disease , 2013, Movement disorders : official journal of the Movement Disorder Society.

[37]  Hung T. Nguyen,et al.  Using EEG spatial correlation, cross frequency energy, and wavelet coefficients for the prediction of Freezing of Gait in Parkinson's Disease patients , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[38]  Valentina Dilda,et al.  Autonomous identification of freezing of gait in Parkinson's disease from lower-body segmental accelerometry , 2013, Journal of NeuroEngineering and Rehabilitation.

[39]  Hung T. Nguyen,et al.  The detection of Freezing of Gait in Parkinson's disease patients using EEG signals based on Wavelet decomposition , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[40]  Thomas D Brown,et al.  Entropy analysis of tri‐axial leg acceleration signal waveforms for measurement of decrease of physiological variability in human gait , 2012, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[41]  J. Contreras-Vidal,et al.  Decoding Intra-Limb and Inter-Limb Kinematics During Treadmill Walking From Scalp Electroencephalographic (EEG) Signals , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[42]  Ronald N. Goodman,et al.  Neural decoding of treadmill walking from noninvasive electroencephalographic signals. , 2011, Journal of neurophysiology.

[43]  Jeffrey M. Hausdorff,et al.  Heart rate changes during freezing of gait in patients with Parkinson's disease , 2010, Movement disorders : official journal of the Movement Disorder Society.

[44]  J. Duysens,et al.  Objective detection of subtle freezing of gait episodes in Parkinson's disease , 2010, Movement disorders : official journal of the Movement Disorder Society.

[45]  Jeffrey M. Hausdorff,et al.  A Wearable System to Assist Walking of Parkinson´s Disease Patients , 2009, Methods of Information in Medicine.

[46]  Miguel A. L. Nicolelis,et al.  Extracting Kinematic Parameters for Monkey Bipedal Walking from Cortical Neuronal Ensemble Activity , 2009, Front. Integr. Neurosci..

[47]  W. Ondo,et al.  Ambulatory monitoring of freezing of gait in Parkinson's disease , 2008, Journal of Neuroscience Methods.

[48]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[49]  E. Marder,et al.  Central pattern generators and the control of rhythmic movements , 2001, Current Biology.

[50]  S. Hochreiter,et al.  Long Short-Term Memory , 1997, Neural Computation.

[51]  S. Folstein,et al.  “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician , 1975 .

[52]  Conor Fearon,et al.  Motor Preparation Rather Than Decision-Making Differentiates Parkinsonâ•Žs Disease Patients With And Without Freezing of Gait , 2020 .

[53]  Moran Gilat,et al.  Prediction of Freezing of Gait in Patients with Parkinson's Disease Using EEG Signals. , 2018, Studies in health technology and informatics.

[54]  Leandro dos Santos Coelho,et al.  Earthworm optimisation algorithm: a bio-inspired metaheuristic algorithm for global optimisation problems , 2018, Int. J. Bio Inspired Comput..

[55]  Fernanda Irrera,et al.  Smart Sensing Systems for the Detection of Human Motion Disorders , 2015 .

[56]  H. Freund,et al.  The cerebral oscillatory network of parkinsonian resting tremor. , 2003, Brain : a journal of neurology.

[57]  R L Kirby,et al.  Coupling of cardiac and locomotor rhythms. , 1989, Journal of applied physiology.