Finger tapping analysis in patients with Parkinson’s disease and atypical parkinsonism

Djurić-Jovičić, Milica; Petrović, Igor; Ječmenica-Lukić, Milica; Radovanović, Saša; Dragašević-Mišković, Nataša; Belić, Minja; Miler-Jerkovic, Vera; Popović, Mirjana; Kostić, Vladimir

doi:10.1016/j.jocn.2015.10.053

Cited by 45 publications

(55 citation statements)

References 22 publications

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“…Finger tapping data have been successfully used to evaluate motor function in PD [19-21]. Individuals with PD often have motor fluctuations in response to commonly used medications for the condition.…”

Section: Introductionmentioning

confidence: 99%

Tablet-Based Application for Objective Measurement of Motor Fluctuations in Parkinson Disease

et al. 2018

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Background: The motor subscale of the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS-III) has limited applicability for the assessment of motor fluctuations in the home setting. Methods: To assess whether a self-administered, tablet-based application can reliably quantify differences in motor performance using two-target finger tapping and forearm pronation-supination tasks in the ON (maximal dopaminergic medication efficacy) and OFF (reemergence of parkinsonian deficits) medication states, we recruited 11 Parkinson disease (PD) patients (age, 60.6 ± 9.0 years; disease duration, 12.8 ± 4.1 years) and 11 healthy age-matched controls (age, 62.5 ± 10.5 years). The total number of taps, tap interval, tap duration, and tap accuracy were algorithmically calculated by the application, using the more affected side in patients and the dominant hand in healthy controls. Results: Compared to the OFF state, PD patients showed a higher number of taps (84.2 ± 20.3 vs. 54.9 ± 26.9 taps; p = 0.0036) and a shorter tap interval (375.3 ± 97.2 vs. 708.2 ± 412.8 ms; p = 0.0146) but poorer tap accuracy (2,008.4 ± 995.7 vs. 1,111.8 ± 901.3 pixels; p = 0.0055) for the two-target task in the ON state, unaffected by the magnitude of coexistent dyskinesia. Overall, test-retest reliability was high (r >0.75) and the discriminatory ability between OFF and ON states was good (0.60 ≤ AUC ≤ 0.82). The correlations between tapping data and MDS-UPDRS-III scores were only moderate (–0.55 to 0.55). Conclusions: A self-administered, tablet-based application can reliably distinguish between OFF and ON states in fluctuating PD patients and may be sensitive to additional motor phenomena, such as accuracy, not captured by the MDS-UPDRS-III.

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Section: Introductionmentioning

confidence: 99%

Tablet-Based Application for Objective Measurement of Motor Fluctuations in Parkinson Disease

et al. 2018

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“…Based on the proposed measurement system and the angle assessment methodology, the clinicians can be provided with numerical values describing the patient’s tapping performance: tapping duration, angular speed, maximal aperture (the difference between the maximal and the minimal angle within a tap), as well as their deviations and trends within the sequence [41]. This can provide an objective follow up of the patient’s state during routine examinations.…”

Section: Discussionmentioning

confidence: 99%

Quantification of Finger-Tapping Angle Based on Wearable Sensors

Djurić-Jovičić

Jovičić

Roby-Brami

et al. 2017

Sensors

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Abstract:We propose a novel simple method for quantitative and qualitative finger-tapping assessment based on miniature inertial sensors (3D gyroscopes) placed on the thumb and index-finger. We propose a simplified description of the finger tapping by using a single angle, describing rotation around a dominant axis. The method was verified on twelve subjects, who performed various tapping tasks, mimicking impaired patterns. The obtained tapping angles were compared with results of a motion capture camera system, demonstrating excellent accuracy. The root-mean-square (RMS) error between the two sets of data is, on average, below 4 • , and the intraclass correlation coefficient is, on average, greater than 0.972. Data obtained by the proposed method may be used together with scores from clinical tests to enable a better diagnostic. Along with hardware simplicity, this makes the proposed method a promising candidate for use in clinical practice. Furthermore, our definition of the tapping angle can be applied to all tapping assessment systems.

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“…During the performance, subjects were sitting comfortably in a chair, with their hand placed in front of them. As the part of the test, they repeatedly tapped index finger and thumb as rapidly and as widely as possible for 15 s, as described in [19]. Each recording began and ended with their fingers closed at the "zero-posture".…”

Section: Methodsmentioning

confidence: 99%

“…2. Firstly, tapping performance was described with parameters typically used for tapping description [19]:…”

Section: Signal Processingmentioning

confidence: 99%

“…In clinical practice, the finger tapping performance is often validated visually, which results in a low diagnostic resolution [18]. However, using the appropriate instrumentation, such as miniature inertial sensors, finger tapping performance can be quantified, allowing the objective assessment of specific characteristics or changes in the finger tapping pattern over time [19]- [20].…”

Section: Introductionmentioning

confidence: 99%

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Spectral parameters for finger tapping quantification

Bobic¹,

Djuric-Jovicic²,

Jarrassé

et al. 2017

FACTA U EE

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A miniature inertial sensor placed on fingertip of index finger while performing finger tapping test can be used for an objective quantification of finger tapping motion. Temporal and spatial parameters such as cadence, tapping duration, and tapping angle can be extracted for detailed analysis. However, the mentioned parameters, although intuitive and simple to interpret, do not always provide all the necessary information regarding the subject's motor performance. Analysis of frequency content of the finger tapping movement can provide crucial information about the patient's condition. In this paper, we present parameters extracted from spectral analysis that we found to be significant for finger tapping assessment. With these parameters, tapping's intra-variability, movement smoothness and anomalies that may occur within the tapping performance can be detected and described, providing significant information for further diagnostics and monitoring progress of the disease or response to therapy.

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Finger tapping analysis in patients with Parkinson’s disease and atypical parkinsonism

Cited by 45 publications

References 22 publications

Tablet-Based Application for Objective Measurement of Motor Fluctuations in Parkinson Disease

Tablet-Based Application for Objective Measurement of Motor Fluctuations in Parkinson Disease

Quantification of Finger-Tapping Angle Based on Wearable Sensors

Spectral parameters for finger tapping quantification

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