Automatic Spiral Analysis for Objective Assessment of Motor Symptoms in Parkinson’s Disease

Abstract

A challenge for the clinical management of advanced Parkinson’s disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Digitized upper limb movement data of 65 advanced PD patients and 10 healthy (HE) subjects were recorded as they performed spiral drawing tasks on a touch screen device in their home environment settings. Several spatiotemporal features were extracted from the time series and used as inputs to machine learning methods. The methods were validated against ratings on animated spirals scored by four movement disorder specialists who visually assessed a set of kinematic features and the motor symptom. The ability of the method to discriminate between PD patients and HE subjects and the test-retest reliability of the computed scores were also evaluated. Computed scores correlated well with mean visual ratings of individual kinematic features. The best performing classifier (Multilayer Perceptron) classified the motor symptom (bradykinesia or dyskinesia) with an accuracy of 84% and area under the receiver operating characteristics curve of 0.86 in relation to visual classifications of the raters. In addition, the method provided high discriminating power when distinguishing between PD patients and HE subjects as well as had good test-retest reliability. This study demonstrated the potential of using digital spiral analysis for objective quantification of PD-specific and/or treatment-induced motor symptoms.

Detecting Parkinson’s disease from sustained phonation and speech signals

“…Additional information is worth considering by tracking an accelerometer signal in a posture test [ 19 ] of standing still and/or holding device in a hand with an arm extended or in a gait test [ 19 ] of walking. Tapping and reaction time tests [ 19 ] or drawing of an Archimedean spiral [ 43 ] are an interesting type of tactile tasks which could be recorded using a hand-held device. Fusion of information from diverse non-invasive modalities could help to develop an efficient SP-based tool for PD screening.…”

Feasibility of spirography features for objective assessment of motor function in Parkinson's disease

“…A clinician (D.N.) used a web interface that animated the spiral drawings, allowing him to observe different kinematic features during the drawing process and to rate task performance of the patients [7,17]. The interface retrieved spiral data from the database tables and then animated the drawing in real-time; that is with the same speed as the patients initially drew the spirals.…”

“…We had at our disposal a set of instances assessed for ground truth by four independent clinicians for this experiment [17]. For the reasons above we selected a random selection of 16 instances of each class from this set with the additional stipulation that there had to be a majority of three evaluators to one or better for each instance regarding its class.…”

“…In the present study we applied the PARKINSONCHECK methodology to automatically differentiate between the states of bradykinesia and dyskinesia which is important for drug dosage adjustment, using spirography data collected in a Swedish study [5,6,17]. Note that this application is different from PARKINSONCHECK's objective.…”

Verification of a Method for Measuring Parkinson’s Disease Related Temporal Irregularity in Spiral Drawings

“…In the same way, the wrist movement signal in PD patients had higher regularity than healthy controls [ 12 ]. Research studies with alternate tapping and spiral performances [ 13 , 14 ] used ApEn as one of the calculated features to automate the process of visual interpretation of movement anomalies. In one study, the ApEn-based variability score was higher for the power of the speed signal in the dynamic PD group, compared to static PD group, while they performed a biking exercise [ 15 ].…”