Classification of normal and pathological tremors using a multidimensional electromagnetic system.

A new multidimensional movement analysis system was used to record limb tremor over six degrees-of-freedom, and signal processing techniques were explored to develop a suitable classification method to distinguish between different types of tremor. The specific aims were to investigate the ability of the system to screen for differences between normal subjects and a group of neurological patients, and then to differentiate between three diagnostic groups of patients. Postural tremor at the hand was recorded in normal subjects (n=24) and patients with essential tremor (n=21), multiple sclerosis (n=17) and parkinsonism (n=19). Data were collected using a 3Space Fastrak((R)) (Polhemus, Inc.) over six degrees-of-freedom (three translational directions and three rotations). Spectral estimates produced measures of tremor frequency and amplitude. Mathematical models of the data, using autoregressive modelling and K-nearest neighbour classification, produced parameters used to classify, (1) the normal subjects and 24 patients (using the three rotational movements), and (2) the three patient groups (using all six movement directions). Results were given in terms of the probability of each subject belonging to the groups being classified. 70%). The diagnostic classification produced clear differences between the patient groups (60% for essential tremor, 80% for multiple sclerosis and 60% for parkinsonism). The ability of this assessment technique to distinguish between postural tremor in normal subjects and neurological patients suggests that it could be developed as a screening tool. Classification of tremors between the patients groups, with a high degree of sensitivity, indicates the potential for further development of the system as a diagnostic aid.