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Description

This dataset is composed of a range of biomedical voice measurements from 42 people with early-stage Parkinson's disease recruited to a six-month trial of a telemonitoring device for remote symptom progression monitoring. The recordings were automatically captured in the patient's homes. Columns in the table contain subject number, subject age, subject gender, time interval from baseline recruitment date, motor UPDRS, total UPDRS, and 16 biomedical voice measures. Each row corresponds to one of 5,875 voice recording from these individuals. The main aim of the data is to predict the motor and total UPDRS scores ('motor_UPDRS' and 'total_UPDRS') from the 16 voice measures. The data is in ASCII CSV format. The rows of the CSV file contain an instance corresponding to one voice recording. There are around 200 recordings per patient, the subject number of the patient is identified in the first column. For further information or to pass on comments, please contact Athanasios Tsanas (tsanasthanasis '@' gmail.com) or Max Little (littlem '@' physics.ox.ac.uk). Further details are contained in the following reference -- if you use this dataset, please cite: Athanasios Tsanas, Max A. Little, Patrick E. McSharry, Lorraine O. Ramig (2009), 'Accurate telemonitoring of Parkinsons disease progression by non-invasive speech tests', IEEE Transactions on Biomedical Engineering (to appear). Further details about the biomedical voice measures can be found in: Max A. Little, Patrick E. McSharry, Eric J. Hunter, Lorraine O. Ramig (2009), 'Suitability of dysphonia measurements for telemonitoring of Parkinson's disease', IEEE Transactions on Biomedical Engineering, 56(4):1015-1022