Quantification of tremor and bradykinesia in Parkinson's disease using a novel ambulatory monitoring system.
An ambulatory system for quantification of tremor and bradykinesia in patients with Parkinson's disease (PD) is presented. To record movements of the upper extremities, a sensing units which included miniature gyroscopes, has been fixed to each of the forearms. An algorithm to detect and quantify tremor and another algorithm to quantify bradykinesia have been proposed and validated. Two clinical studies have been performed. In the first study, 10 PD patients and 10 control subjects participated in a 45-min protocol of 17 typical daily activities. The algorithm for tremor detection showed an overall sensitivity of 99.5% and a specificity of 94.2% in comparison to a video reference. The estimated tremor amplitude showed a high correlation to the Unified Parkinson's Disease Rating Scale (UPDRS) tremor subscore (e.g., r = 0.87, p < 0.001 for the roll axis). There was a high and significant correlation between the estimated bradykinesia related parameters estimated for the whole period of measurement and respective UPDRS subscore (e.g., r = -0.83, p < 0.001 for the roll axis). In the second study, movements of upper extremities of 11 PD patients were recorded for periods of 3-5 hr. The patients were moving freely during the measurements. The effects of selection of window size used to calculate tremor and bradykinesia related parameters on the correlation between UPDRS and these parameters were studied. By selecting a window similar to the period of the first study, similar correlations were obtained. Moreover, one of the bradykinesia related parameters showed significant correlation (r = -0.74, p < 0.01) to UPDRS with window sizes as short as 5 min. Our study provides evidence that objective, accurate and simultaneous assessment of tremor and bradykinesia can be achieved in free moving PD patients during their daily activities.
Salarian
Arash
A
Laboratory of Movement Analysis and Measurement, Swiss Federal Institute of Technology, Lausanne (EPFL), 1015, Switzerland. arash.salarian@ieee.org
Russmann
Heike
H
Wider
Christian
C
Burkhard
Pierre R
PR
Vingerhoets
Françios J G
FJ
Aminian
Kamiar
K
D000368:Aged; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation* / Q000379:methods*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005260:Female; D006801:Humans; D018476:Hypokinesia / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D010300:Parkinson Disease / Q000150:complications / Q000175:diagnosis* / Q000503:physiopathology; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity