Bradykinesia is the fundamental motor feature of Parkinson’s disease - obligatory for diagnosis and central to monitoring. It is a complex clinicalsign that describes movements with slow speed, small amplitude, irregular rhythm, brief pauses and progressive decrements. Clinical ascertainment of the presence and severity of bradykinesia relies on subjective interpretation of these components, with considerable variability amongst clinicians, and this may contribute to diagnostic error and inaccurate monitoring in Parkinson’s disease. The primary aim of this thesis was to assess whether a novel non-invasive device could objectively measure bradykinesia and predict diagnostic classification of movement data from Parkinson’s disease patients and healthy controls. The second aim was to evaluate how objective measures of bradykinesia correlate with clinical measures of bradykinesia severity. The third aim was to investigate the characteristic kinematic features of bradykinesia. Forty-nine patients with Parkinson’s disease and 41 healthy controls were recruited in Leeds. They performed a repetitive finger-tapping task for 30 seconds whilst wearing small electromagnetic tracking sensors on their finger and thumb. Movement data was analysed using two different methods - statistical measures of the separable components of bradykinesia and a computer science technique called evolutionary algorithms. Validation data collected independently from 13 patients and nine healthy controls in San Francisco was used to assess whether the results generalised. The evolutionary algorithm technique was slightly superior at classifying the movement data into the correct diagnostic groups, especially for the mildest clinical grades of bradykinesia, and they generalised to the independent group data. The objective measures of finger tapping correlated well with clinical grades of bradykinesia severity. Detailed analysis of the data suggests that a defining feature of Parkinson’s disease bradykinesia called the sequence effect may be a physiological rather than a pathological phenomenon. The results inform the development of a device that may support clinical diagnosis and monitoring of Parkinson’s disease and also be used to investigate bradykinesia
