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| Max A. Little; Patrick E. McSharry; Eric J. Hunter; Jennifer Spielman; Lorraine O. Ramig. |
| We present an assessment of the practical value of existing traditional and non-standard measures for discriminating healthy people from people with Parkinson?s disease (PD) by detecting dysphonia. We introduce a new measure of dysphonia, Pitch Period Entropy (PPE), which is robust to many uncontrollable confounding effects including noisy acoustic environments and normal, healthy variations in voice frequency. We collected sustained phonations from 31 people, 23 with PD. We then selected 10 highly uncorrelated measures, and an exhaustive search of all possible combinations of these measures finds four that in combination lead to overall correct classification performance of 91.4%, using a kernel support vector machine. In conclusion, we find that... |
| Tipo: Manuscript |
Palavras-chave: Neuroscience; Bioinformatics. |
| Ano: 2008 |
URL: http://precedings.nature.com/documents/2298/version/1 |
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| John C. Rodda; Max A. Little; Harvey J. E. Rodda; Patrick E. McSharry. |
| During the 1960s, a study was made of the magnitude, frequency and distribution of intense rainfall over the UK, employing data from more than 120 daily-read rain gauges covering the period 1911 to 1960. Using the same methodology, that study was recently updated utilizing data for the period 1961 to 2006 for the same gauges, or from those nearby. This paper describes the techniques applied to ensure consistency of data and statistical modelling. It presents a comparison of patterns of extreme rainfalls for the two periods and discusses the changes that have taken place. Most noticeably, increases up to 20% have occurred in the north west of the country and in parts of East Anglia. There have also been changes in other areas, including decreases of the... |
| Tipo: Manuscript |
Palavras-chave: Earth & Environment. |
| Ano: 2009 |
URL: http://precedings.nature.com/documents/3847/version/1 |
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| Athanasios Tsanas; Max A. Little; Patrick E. McSharry; Lorraine O. Ramig. |
| Tracking Parkinson's disease (PD) symptom progression often uses the Unified Parkinson’s Disease Rating Scale (UPDRS), which requires the patient's presence in clinic, and time-consuming physical examinations by trained medical staff. Thus, symptom monitoring is costly and logistically inconvenient for patient and clinical staff alike, also hindering recruitment for future large-scale clinical trials. Here, for the first time, we demonstrate rapid, remote replication of UPDRS assessment with clinically useful accuracy (about 7.5 UPDRS points difference from the clinicians’ estimates), using only simple, self-administered, and non-invasive speech tests. We characterize speech with signal processing algorithms,... |
| Tipo: Manuscript |
Palavras-chave: Neuroscience; Bioinformatics. |
| Ano: 2009 |
URL: http://precedings.nature.com/documents/3920/version/1 |
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| Max A. Little; Patrick E. McSharry; Stephen A. Roberts; Declan A. E. Costello; Irene M. Moroz. |
| Background: Voice disorders affect patients profoundly, and acoustic tools can potentially measure voice function objectively. Disordered sustained vowels exhibit wide-ranging phenomena, from nearly periodic to highly complex, aperiodic vibrations, and increased "breathiness". Modelling and surrogate data studies have shown significant nonlinear and non-Gaussian random properties in these sounds. Nonetheless, existing tools are limited to analysing voices displaying near periodicity, and do not account for this inherent biophysical nonlinearity and non-Gaussian randomness, often using linear signal processing methods insensitive to these properties. They do not directly measure the two main biophysical symptoms of disorder: complex... |
| Tipo: Manuscript |
Palavras-chave: Biotechnology. |
| Ano: 2007 |
URL: http://precedings.nature.com/documents/326/version/1 |
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