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- Memedi, Mevludin, 1983-, et al.
(författare)
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Computerized identification of motor complications in Parkinson's disease
- 2014
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Ingår i: Movement Disorders Supplement. - : Wiley-Blackwell. - 0885-3185. ; , s. S187-S188
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Objective: To investigate whether spirography-based objective measures of motor dysfunctions are able to discriminate between Parkinson’s disease (PD) patients with different motor states (Off and Dyskinesia) and healthy elderly (HE) subjects.Background: Sixty-five advanced PD patients and 10 HE subjects performed repeated assessments of spirography, using a touch screen telemetry device. On each test occasion, they were asked to trace a pre-drawn Archimedes spiral using dominant hand and repeating the test three times. The clinical assessment was only performed in the patient group by animating the three spirals in a web interface, allowing a clinician (DN) to observe accelerations and spa-tial changes during the drawing process. A scale ranging from 0 (normal) to 4 (extremely severe) was used for the assessment of kinematic properties of speed, irregularity and hesitation. Finally, the momentary motor state of the patient was marked using two classes: - 1 (Off) and 1 (Dyskinesia). The HE samples were assigned a 0 (On) class and used in subsequent analysis.Methods: After time series analysis, 13 quantitative measures were calculated for representing the severity of symptoms in each individual kinematic property. Principal Component Analysis was then used to reduce their dimensions by retaining the first 4 principal components (PC). To investigate differences in mean PC scores across the three classes a one-way ANOVA test followed by Tukey multiple comparisons was used. An ordinal logistic regression model, using 10-fold cross-validation, was used to map the 4 PC to the corresponding motor state classes.Results: The agreements between computer and clinician ratings were very good with a weighted area under the receiver operating characteristic curve (AUC) coefficient of 0.91 (Table 1). The mean PC scores were different across the three classes, only at different levels (Fig 1). The Spearman’s rank correlations between the first two PC and visually assessed kinematic properties were: speed (PC1, 0.34; PC2, 0.83), irregularity (PC1, 0.17; PC2, 0.17) and hesitation (PC1, 0.27; PC2, 0.77).Conclusions: These findings suggest that spirography-based objective measures are valid measures of spatial- and time-dependent deficits in PD. The differences among the three classes imply that these measures can be used to assess changes in the motor states in response to therapeutic interventions.
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| 3. |
- Memedi, Mevludin, 1983-, et al.
(författare)
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Visualization of spirography-based objective measures in Parkinson's disease
- 2014
-
Ingår i: Movement Disorders Supplement. - : Wiley-Blackwell. - 0885-3185. ; , s. S187-S189
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Objective: To investigate whether advanced visualizations of spirography-based objective measures are useful in differentiating motor complications among Parkinson’s disease (PD) patients.Background: Sixty-five patients diagnosed with advanced PD have utilized a telemetry test battery, implemented on a touch screen handheld computer, in a telemedicine setting. On each test occasion, they were asked to perform repeated and time-stamped assessments of spiral drawing performance by tracing a pre-drawn Archimedes spiral. The test battery was also used by 10 healthy elderly (HE) subjects.Methods: A web-based framework was developed to visualize the performance during spirography of both patients and HE subjects to a clinician (DN). The performance was depicted by animating the spiral drawings (Fig 1). In addition, the framework displayed two time series views for representing drawing speed (blue line) and displacement from the ideal trajectory (orange line). The views are coordinated and linked i.e. user interactions in one of the views will be reflected in other views. For instance, when the user points in one of the pixels in spiral view, the circle size of the underlying pixel increases and a vertical line appears in the time series views to depict the corresponding position. Fig 1 shows single randomly selected spirals per each subject group: A) a PD patient in Dyskinesia state, B) a HE subject, and C) a PD patient in Off state.Results: The clinician recognized Dyskinesia symptoms as movements made with high speed, smooth/gradual spatial displacements, and a small amount of hesitation (Fig 1A). Similarly, Off symptoms were associated with low speed, sharp/abrupt spatial displacements, and a large amount of hesitation (Fig 1C). In contrast, the spiral drawn by a HE subject (Fig 1B) was associated with unchanging levels of kinematic features i.e. drawing speed, spatial displacements and hesitation over time.Conclusions: Visualizing spirography-based objective measures enables identification of trends and patterns of motor dysfunctions at the patient’s individual level. Dynamic access of visualized motor tests may be useful during the evaluation of therapy-related complications such as under- and over-medications. This will assist during individualized optimization of therapies, enabling patients to spend more time in the On state with a minimum of Off and dyskinetic states.
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