Scoring atonia during normal and pathological rapid eye movement sleep: Visual and automatic quantification methods

Fulda, Stephany; Plazzi, Giuseppe; Ferri, Raffaele

doi:10.1111/j.1479-8425.2012.00552.x

Cited by 16 publications

(5 citation statements)

References 73 publications

(167 reference statements)

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“…The applied scoring method produced reliable results, as illustrated by identical mean scores for muscle atonia in our controls and in those reported by Gagnon et al Alternatively, consideration of phasic chin or limb muscle activity has been strongly advocated, although it remains controversial whether specificity can be increased by adding up different methods . In the future, computer‐assisted, automated quantification of loss of atonia, possibly in more than 1 muscle, may be the method of choice . Negative ageing effects on sleep added up in patients with IPD more markedly than in age‐matched controls, and a particularly significant interaction was observed between age and sleep efficiency.…”

Section: Discussionsupporting

confidence: 79%

“…15 In the future, computer-assisted, automated quantification of loss of atonia, possibly in more than 1 muscle, may be the method of choice. 16,17 Negative ageing effects on sleep added up in patients with IPD more markedly than in age-matched controls, and a particularly significant interaction was observed between age and sleep efficiency.…”

Section: Discussionmentioning

confidence: 99%

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Lack of polysomnographic Non‐REM sleep changes in early Parkinson's disease

et al. 2013

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BackgroundPolysomnography (PSG) data are rare in patients who have early stage idiopathic Parkinson’s disease (IPD).MethodsThirty-three patients who had IPD with a disease duration ≤3 years and 37 age-matched controls were recruited. PSG analysis was performed on current medication.ResultsPatients with IPD had a reduced mean percentage of muscle atonia during rapid eye movement (REM) sleep (80% vs 93%; P < 0.05). Total sleep time, sleep efficiency, indices/hour of arousals, awakenings, apnea/hypopnea, and periodic leg movements were similar in both groups. Age, but not dopaminergic medication, had a negative impact on sleep architecture in patients with IPD. There was no correlation between sleep efficiency assessed by PSG and sleep quality assessed by questionnaire.ConclusionsThe results confirmed a reduction in muscle atonia during REM sleep as a characteristic finding in early IPD. However, there were no further disease-inherent or medication-induced changes in sleep architecture. Although sleep disturbances are considered to be an integral part of IPD, PSG cannot yet identify them objectively at an early stage. © 2013 International Parkinson and Movement Disorder Society

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Section: Discussionsupporting

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Lack of polysomnographic Non‐REM sleep changes in early Parkinson's disease

et al. 2013

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“…1 However, the general and non-quantitative nature of this criterion has prompted a number of studies aiming at establishing more quantitative parameters for the defi nition of the so-called REM sleep without atonia (RSWA); based on both visual [2][3][4] and automati c [5][6][7][8] approaches. 9 These methods seem to show suffi cient sensitivity and specifi city for their application in both clinical practice and research settings and probably provide comparable results. 10 However, one of the aspects that needs to be further clarifi ed is that of the night-to-night variability of RSWA.…”

Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

Night-to-Night Variability of Automatic Quantitative Parameters of the Chin EMG Amplitude (Atonia Index) in REM Sleep Behavior Disorder

Ferri

Marelli

Cosentino

et al. 2013

Journal of Clinical Sleep Medicine

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The night-to-night variability of AI seems to be very low in normal controls and remains under 20% in RBD patients; that of the number of EMG activations is higher. However, even a single PSG recording provides high values of sensitivity and specificity when a threshold value of AI ≤ 0.9 is used to define abnormal chin EMG levels during REM sleep that increase only moderately when a second night recording is available.

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“…To provide clarity and consistency, Lapierre and Montplaisir (1992) first proposed scoring rules to quantify abnormal EMG tonic and phasic activity (Lapierre and Montplaisir 1992). This method was further developed (Dauvilliers et al 2007;Montplaisir et al 2010;Fulda et al 2013), but still required manual visual inspection to distinguish tonic and phasic movement. Automated RBD detection through RSWA has been proposed in a number of papers (Burns et al 2007;Kempfner et al 2013a;Frauscher et al 2014;Frandsen et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Detection of REM sleep behaviour disorder by automated polysomnography analysis

Cooray

Andreotti

et al. 2019

Clinical Neurophysiology

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Objective: Evidence suggests Rapid-Eye-Movement (REM) Sleep Behaviour Disorder (RBD) is an early predictor of Parkinson's disease. This study proposes a fully-automated framework for RBD detection consisting of automated sleep staging followed by RBD identification.Methods: Analysis was assessed using a limited polysomnography montage from 53 participants with RBD and 53 age-matched healthy controls. Sleep stage classification was achieved using a Random Forest (RF) classifier and 156 features extracted from electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) channels. For RBD detection, a RF classifier was trained combining established techniques to quantify muscle atonia with additional features that incorporate sleep architecture and the EMG fractal exponent.Results: Automated multi-state sleep staging achieved a 0.62 Cohen's Kappa score. RBD detection accuracy improved by 10% to 96% (compared to individual established metrics) when using manually annotated sleep staging. Accuracy remained high (92%) when using automated sleep staging.Conclusions: This study outperforms established metrics and demonstrates that incorporating sleep architecture and sleep stage transitions can benefit RBD detection. This study also achieved automated sleep staging with a level of accuracy comparable to manual annotation.Significance: This study validates a tractable, fully-automated, and sensitive pipeline for RBD identification that could be translated to wearable take-home technology. Highlights RBD detection benefits from an ensemble of metrics that incorporate sleep architecture. RBD detection remains successful using both manual and automated sleep scoring. Cohort outnumbers similar studies with 53 RBD participants and 53 aged-matched healthy controls.

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Scoring atonia during normal and pathological rapid eye movement sleep: Visual and automatic quantification methods

Cited by 16 publications

References 73 publications

Lack of polysomnographic Non‐REM sleep changes in early Parkinson's disease

Lack of polysomnographic Non‐REM sleep changes in early Parkinson's disease

Night-to-Night Variability of Automatic Quantitative Parameters of the Chin EMG Amplitude (Atonia Index) in REM Sleep Behavior Disorder

Detection of REM sleep behaviour disorder by automated polysomnography analysis

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