Max A Little
Max A Little
University of Birmingham/MIT
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
Suitability of dysphonia measurements for telemonitoring of Parkinson’s disease
MA Little, PE McSharry, EJ Hunter, J Spielman, LO Ramig
IEEE Transactions on Biomedical Engineering 56 (4), 1015-1022, 2009
Exploiting nonlinear recurrence and fractal scaling properties for voice disorder detection
MA Little, P McSharry, S Roberts, D Costello, I Moroz
BioMedical Engineering OnLine 6, 23, 2007
Accurate telemonitoring of Parkinson’s disease progression by non-invasive speech tests
A Tsanas, MA Little, PE McSharry, LO Ramig
IEEE Transactions on Biomedical Engineering 57 (4), 884-893, 2010
Novel speech signal processing algorithms for high-accuracy classification of Parkinson's disease
A Tsanas, MA Little, P McSharry, J Spielman, L Ramig
IEEE Transactions on Biomedical Engineering 59 (5), 1264-1271, 2012
Technology in Parkinson's disease: Challenges and opportunities
AJ Espay, P Bonato, FB Nahab, W Maetzler, JM Dean, J Klucken, ...
Movement Disorders 31 (9), 1272-1282, 2016
Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates
HS Dashti, SE Jones, AR Wood, JM Lane, VT van Hees, H Wang, ...
Nature Communications 10, 1100, 2019
Highly comparative time-series analysis: the empirical structure of time series and their methods
BD Fulcher, MA Little, NS Jones
Journal of the Royal Society Interface 10 (83), 20130048, 2013
Detecting and monitoring the symptoms of Parkinson's disease using smartphones: A pilot study
S Arora, V Venkataraman, A Zhan, S Donohue, KM Biglan, ER Dorsey, ...
Parkinsonism & related disorders 21 (6), 650-653, 2015
Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity
A Tsanas, MA Little, PE McSharry, LO Ramig
Journal of the Royal Society Interface 8 (59), 842-855, 2011
Using smartphones and machine learning to quantify Parkinson disease severity: The mobile Parkinson disease score
A Zhan, S Mohan, C Tarolli, RB Schneider, JL Adams, S Sharma, ...
JAMA Neurology 75 (7), 876-880, 2018
Genome-wide association analyses of sleep disturbance traits identify new loci and highlight shared genetics with neuropsychiatric and metabolic traits
JM Lane, J Liang, I Vlasac, SG Anderson, DA Bechtold, J Bowden, ...
Nature Genetics 49, 274–281, 2017
Genome-wide association analysis identifies novel loci for chronotype in 100,420 individuals from the UK Biobank
JM Lane, I Vlasac, SG Anderson, S Kyle, WG Dixon, DA Bechtold, S Gill, ...
Nature Communications 7, 10889, 2016
Biological and clinical insights from genetics of insomnia symptoms
JM Lane, S Jones, H Dashti, A Wood, K Aragam, VT van Hees, ...
Nature Genetics 51, 387–393, 2019
Objective Automatic Assessment of Rehabilitative Speech Treatment in Parkinson's Disease
A Tsanas, MA Little, C Fox, LO Ramig
IEEE Transactions on Neural Systems and Rehabilitation Engineering 22 (1 …, 2014
Machine learning for large-scale wearable sensor data in Parkinson disease: concepts, promises, pitfalls and futures
K Kubota, J Chen, MA Little
Movement Disorders 31 (9), 1314-1326, 2016
What to do when K-means clustering fails: a simple yet principled alternative algorithm
YP Raykov, A Boukouvalas, F Baig, MA Little
PLoS One 11 (9), e0162259, 2016
Freezing of gait and fall detection in Parkinson’s disease using wearable sensors: a systematic review
MJF Ana Ligia Silva de Lima, Luc J. W. Evers, Tim Hahn, Lauren Bataille ...
Journal of Neurology 264 (8), 1642–1654, 2017
Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes
H Wang, JM Lane, SE Jones, HS Dashti, H Ollila, AR Wood, VT van Hees, ...
Nature Communications, 2019
Feasibility of large-scale deployment of multiple wearable sensors in Parkinson's disease
MJF Ana Lígia Silva de Lima, Tim Hahn, Luc JW Evers, Nienke M de Vries, Eli ...
PLoS One 12 (12), e0189161, 2017
Generalized methods and solvers for noise removal from piecewise constant signals. I. Background theory
MA Little, NS Jones
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2011
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