RECHERCHE & DEVELOPPEMENT

La recherche occupe une place essentielle à Physip.

Elle nous permet de faire avancer en permanence les algorithmes d’analyse existants et d’en développer de nouveaux pour répondre à de nouveaux besoins scientifiques et industriels.

La R&D à Physip est essentiellement collaborative. C’est en travaillant avec des équipes médicales compétentes, reconnues que nous avons pu amener nos solutions d’analyse à leur niveau de performance actuel.

 

 

PROJETS DE RECHERCHE

Nos projets de recherche se répartissent entre deux grands domaines, le sommeil et l’éveil, et entre les projets de développement -validation des algorithmes, et ceux où nos analyses sont utilisées sur des thématiques larges : cognition, vieillissement, syndrome post traumatique, performances, monitoring de la somnolence dans les transports.

Scoal : Sommeil, Cognition et troubles de la mémoire dans la maladie d’Alzheimer, 2011-2015

Objectif

L’enjeu du projet SCOAL est de mieux comprendre les troubles du sommeil (changements de l’architecture du sommeil et/ou apparition de troubles du sommeil) avant-coureurs dans les troubles cognitifs légers et leur contribution potentielle à une éventuelle détérioration cognitive progressive.

Pour Physip, il s’agit de rechercher dans l’EEG de sommeil des marqueurs diagnostiques et pronostiques de la maladie d’Alzheimer.

 

Partenaires

Le projet est piloté par l’unité CNRS Sanpsy, avec Patricia Sagaspe et Jacques Taillard notamment.

Il réunit, outre Physip,

 

Financement

Le projet est financé par le programme ANR MALZ.

Résultats

Des premiers résultats ont été publiés au congrès de l’ESRS 2014 à Tallinn.

Sagaspe P, Taillard J, Chaufton C, Berthomier C, Brandewinder M, Amiéva H, Dartigues J-F, Philip P.
Polysomnographic data in patients with isolated memory complaints or mild cognitive impairment.
J. Sleep Res., 23 Suppl. 1:240, 2014

ESRS-2014-Poster-SCOAL-Sagaspe-211x300-

Meegaperf : Monitoring EEG automatique des PERFormances, 2011-2015

Objectif

Meegaperf vise à identifier de façon automatique dans l’EEG des marqueurs de risques de performances dégradées au niveau physique et cognitif.
Le projet consiste à enregistrer l’EEG de sujets au cours de tâches cognitives et physiques propices aux baisses ou ruptures de performances, pour repérer les signes dans l’activité cérébrales qui permettent d’anticiper ces ruptures de performances.

 

Financement

Meegaperf est un projet RAPID, Régime d’Aide aux Projets d’Innovation Duale, financé par la DGA et la DGCIS devenue DGE. Didier Bazalgette, responsable Facteurs Humains de la MRIS (DGA) accompagne ce projet.

Partenaires

Le travail sur les performances physiques a nécessité d’imaginer un dispositif complexe, permettant l’enregistrement synchronisé de plusieurs signaux physiologiques, rapportés à la performance physique évaluée par la fréquence de pédalage d’un ergocycle. La conception et la réalisation du dispositif d’acquisition ont réuni tous les partenaires et des compétences variées pour aboutir à des données exceptionnelles.

Meegaperf, piloté par Physip, réunit :

  • l’unité Inserm U1028, du Centre de Recherche Neurologique de Lyon :
    Jérémie Mattout, Aline Bompas, Emmanuel Maby, Patrick Bouchet, travaillent ou ont travaillé pour le projet pour le volet performances cognitives et l’enregistrement des signaux EEG du volet performances physiques.
  • le département TSI de Telecom ParisTech :
    Slim Essid, Cecilia Damon, François Rigaud, Alexis Benichoux pour le travail sur les artefacts EEG lors d’acquisitions en mouvement.

En s’appuyant sur cette objectivation des performances physiques, Physip développe l’algorithmie EEG de détection des marqueurs EEG de rupture de performances.

Drowsimeter, 2011

Objectif
Développer une méthode d’analyse de la pression de sommeil mesurée par KDT (Karolinska Drowsiness Test).

Partenaires
Drowsimeter a été réalisée avec l’équipe Sanpsy, Jacques Taillard en particulier.

Soutien et financement

Le projet a fait l’objet d’un financement AIMA, BPICentre Francilien de l’Innovation.

Résultats

Une méthode de réjection automatique d’artefact a été développée et validée. Elle permet de réaliser de façon rapide, objective, reproductible, le travail de prétraitement indispensable préalable au calcul de la puissance spectrale dans la bande 4-7Hz.

Les résultats ont été présentés en communication au Congrès du Sommeil à Marseille en 2013.

DAM : Drowsiness Automatic Monitoring, 2006-2008

Le projet DAM était à l’origine une étude de faisabilité d’un algorithme de mesure automatique et temps réel de la somnolence à partir d’une dérivation d’EEG.

Partenaires

Le Dr Alain Muzet et Forenap ont participé au projet DAM, pour l’acquisition des données sur simulateurs de conduite et la lecture visuelle des tracés.

Financement

DAM a été financé par la DGA, sous la forme d’un contrat REI, Recherche Exploratoire et Innovation.

Résultats

Le projet DAM a abouti à l’algorithme DAM, capable de décrire de façon automatique et temps réel la somnolence d’un sujet sur une échelle de 0 – veille alerte, à 4 – forte somnolence, l’état d’un sujet actif.

Les résultats ont été présentés au congrès de l’ESRS en 2008, et au Congrès du Sommeil en 2008.

Berthomier C, Muzet A, Berthomier P, Prado J, Mattout J, Real-Time Automatic Measurement of Drowsiness based on a Single EEG Channel

Drowsiness-monitoring-ESRS08-poster-2-st-724x1024

 

Validation sujets sains, 2003-2005

Objectif

L’objectif de l’étude est de valider les performances de la technologie ASEEGA®, en comparant l’analyse automatique avec la lecture de deux médecins expérimentés, spécialistes de la lecture de tracés de sommeil, sur 15 tracés de PSG de sujets sains.

Partenaires

Les enregistrements de sommeil et l’analyse visuelle des tracés de PSG ont été réalisés par l’équipe du laboratoire d’explorations fonctionnelles de l’Hôpital Henri Mondor : Marie-Pia d’Ortho, Xavier Drouot, Maria Stoïca, Djibril Bokar-Thire.

Financement

L’étude a été financée par une subvention du Bio-CRITT d’Ile de France, devenu Paris Région Entreprises.

Résultats

Les résultats de l’étude détaillant les performances de la technologie ASEEGA® ont été publiés dans la revue Sleep en 2007 :
Automatic analysis of single-channel sleep EEG: validation in healthy individuals.
Berthomier C, Drouot X, Herman-Stoïca M, Berthomier P, Prado J, Bokar-Thire D, Benoit O, Mattout J, d’Ortho MP.
Sleep. 2007 Nov;30(11):1587-95.

 

PUBLICATIONS

EDITORIAL

Berthomier C. & Brandewinder M., EOG-based auto-staging: less is more, Sleep Breath., 2015

Berthomier C, Brandewinder M, EOG-based auto-staging: less is more, Sleep Breath. Sleep Breath. 19 (3):791-793, 2015

This issue of Sleep and Breathing presents the validation results of a new automated wake/sleep staging method based on EOG activity, developed by Jussi Virkkala from the Finnish Institute of Occupational Health. Classically, the automated method is compared to visual analysis, on an epoch by epoch basis. It reaches a level of global concordance of 88 % with a Kappa of 0.57. In other words, on the 248,696 epochs of the validation dataset, 212,138 were scored correctly in wake/sleep, that is as the human expert did it, and on 36,558 epochs, the two scorings differ.

> Accéder à l’article complet

Berthomier C. & Brandewinder M., Sleep scoring: man vs. machine ? Sleep Breath., 2013

Berthomier C, Brandewinder M, Sleep scoring: man vs. machine ?, Sleep Breath. 17 (2):461-462, 2013

The automated analysis of sleep has grown in interest in the past decade. Advances in computing have brought the needed intensive calculations within reach [1]; while simultaneously, there is an increasing demand for sleep diagnosis and analysis. The prevalence of sleep troubles is high, and the awareness of their consequences is spreading among patients, health authorities, and clinicians. This awareness is directing more and more patients to sleep centers. The upward trend in demand for sleep evaluations concerns not only sleep specialists. Sleep appears to be an extremely promising territory for other fields, such as cardiology and nutrition for example [2]. Needs exceed capacities by this far. Data analysis has been identified as one of the bottlenecks in the sleep evaluation process, making clear the importance of developing tools to facilitate analysis. These developments have an impact that is medical, as well as economical and social.

> Accéder à l’article complet



UTILISATION

Dang-Vu T. T., et al. Sleep spindles may predict response to cognitive behavioral therapy for chronic insomnia, Sleep Med., 2017

Dang-Vu TT, Hatch B, Salimi A, Mograss M, Boucetta S, O’byrne J, Brandewinder M, Berthomier C, Gouin JP, Sleep spindles may predict response to cognitive behavioral therapy for chronic insomnia, Sleep Med. Sleep Medicine 39 (2017) 54-⁠61

Highlights

• Spindles may predict responsiveness to cognitive-behavioral therapy for insomnia (CBT-I).
• Lower spindle density was prospectively associated with smaller responses to CBT-I.
• Spindles might thus constitute a biomarker identifying patients less responsive to CBT-I.

> Accéder à l’abstract

Reichert C. F., et al., Cognitive brain responses during circadian wake-promotion: evidence for sleep-pressure-dependent hypothalamic activation, Sci Rep., 2017

Reichert CF, Maire M, Gabel V, Viola AU, Götz T, Scheffler K, Klarhöfer M, Berthomier C, Strobel W, Phillips C, Salmon E, Cajochen C, Schmidt C, Cognitive brain responses during circadian wake-promotion: evidence for sleep-pressure-dependent hypothalamic activation, Sci Rep. 2017 Jul 17;7(1):5620. doi: 10.1038/s41598-017-05695-1.

The two-process model of sleep-wake regulation posits that sleep-wake-dependent homeostatic processes interact with the circadian timing system to affect human behavior. The circadian timing system is fundamental to maintaining stable cognitive performance, as it counteracts growing homeostatic sleep pressure during daytime. Using magnetic resonance imaging, we explored brain responses underlying working memory performance during the time of maximal circadian wake-promotion under varying sleep pressure conditions. Circadian wake-promoting strength was derived from the ability to sleep during an evening nap. Hypothalamic BOLD activity was positively linked to circadian wake-promoting strength under normal, but not under disproportionally high or low sleep pressure levels. Furthermore, higher hypothalamic activity under normal sleep pressure levels predicted better performance under sleep loss. Our results reappraise the two-process model by revealing a homeostatic-dose-dependent association between circadian wake-promotion and cognition-related hypothalamic activity.

> Accéder à l’article complet

Vallat R., et al., Increased Evoked Potentials to Arousing Auditory Stimuli during Sleep: Implication for the Understanding of Dream Recall, Front. Hum. Neurosci., 2017

Raphael Vallat, Tarek Lajnef, Jean-Baptiste Eichenlaub, Christian Berthomier, Karim Jerbi, Dominique Morlet and Perrine M. Ruby, Increased Evoked Potentials to Arousing Auditory Stimuli during Sleep: Implication for the Understanding of Dream Recall, Front. Hum. Neurosci., 21 March 2017 | https://doi.org/10.3389/fnhum.2017.00132

High dream recallers (HR) show a larger brain reactivity to auditory stimuli during wakefulness and sleep as compared to low dream recallers (LR) and also more intra-sleep wakefulness (ISW), but no other modification of the sleep macrostructure. To further understand the possible causal link between brain responses, ISW and dream recall, we investigated the sleep microstructure of HR and LR, and tested whether the amplitude of auditory evoked potentials (AEPs) was predictive of arousing reactions during sleep. Participants (18 HR, 18 LR) were presented with sounds during a whole night of sleep in the lab and polysomnographic data were recorded. Sleep microstructure (arousals, rapid eye movements (REMs), muscle twitches (MTs), spindles, KCs) was assessed using visual, semi-automatic and automatic validated methods. AEPs to arousing (awakenings or arousals) and non-arousing stimuli were subsequently computed. No between-group difference in the microstructure of sleep was found. In N2 sleep, auditory arousing stimuli elicited a larger parieto-occipital positivity and an increased late frontal negativity as compared to non-arousing stimuli. As compared to LR, HR showed more arousing stimuli and more long awakenings, regardless of the sleep stage but did not show more numerous or longer arousals. These results suggest that the amplitude of the brain response to stimuli during sleep determine subsequent awakening and that awakening duration (and not arousal) is the critical parameter for dream recall. Notably, our results led us to propose that the minimum necessary duration of an awakening during sleep for a successful encoding of dreams into long-term memory is approximately 2 min.

> Accéder à l’article complet

Dang-Vu T. T., et al., Sleep spindles predict stress-related increases in sleep disturbances, Front. Hum. Neurosci., 2015

Dang-Vu T. T., Salimi A., Boucetta S., Wenzel K., O’Byrne J., M. Brandewinder M., Berthomier C. and Gouin J.-P.. Sleep spindles predict stress-related increases in sleep disturbances. Front. Hum. Neurosci., 10 February 2015 | doi: 10.3389/fnhum.2015.00068

The aim of this study was to prospectively assess whether spindle density would predict the worsening of sleep disturbances in response to a standardized stressor. We chose to follow a population of undergraduate university students during a period of increasing academic stress. In this context, assessing students at the beginning of the semester, corresponding to a lower stress period, and reevaluating them during a follow-up in the week preceding the final examinations, a period of higher stress, provides a unique opportunity to examine individual differences in the evolution of insomnia symptoms in response to a standardized stressor.

> Accéder à l’article complet

O'Byrne J, et al., Spindles and slow waves predict treatment responses to cognitive-behavioural therapy for chronic primary insomnia, J. Sleep Res. 2014, Tallinn, Estonia.

O’Byrne J, Boucetta S, Reed L,Malhi O, Zhang V, Arcelin A, Wenzel K, Brandewinder M, Berthomier C, Gouin J-P, Dang-Vu TT. Spindles and slow waves predict treatment responses to cognitive-behavioural therapy for chronic primary insomnia. J. Sleep Res., 23 Suppl. 1:209, 2014


Sagaspe P, et al., Polysomnographic data in patients with isolated memory complaints or mild cognitive impairment, J. Sleep Res. 2014, Tallinn, Estonia.

Sagaspe P, Taillard J, Chaufton C, Berthomier C, Brandewinder M, Amiéva H, Dartigues J-F, Philip P. Polysomnographic data in patients with isolated memory complaints or mild cognitive impairment. J. Sleep Res., 23 Suppl. 1:240, 2014


Eichenlaub JB, et al., Brain Reactivity Differentiates Subjects with High and Low Dream Recall Frequencies during Both Sleep and Wakefulness, Cereb. Cortex 2014

Eichenlaub JB, Bertrand O, Morlet D, Ruby P. Brain Reactivity Differentiates Subjects with High and Low Dream Recall Frequencies during Both Sleep and Wakefulness. Cereb. Cortex 24 (5): 1206-1215. 2014

The neurophysiological correlates of dreaming remain unclear. According to the « arousal-retrieval » model, dream encoding depends on intrasleep wakefulness. Consistent with this model, subjects with high and low dream recall frequency (DRF) report differences in intrasleep awakenings. This suggests a possible neurophysiological trait difference between the 2 groups. To test this hypothesis, we compared the brain reactivity (evoked potentials) of subjects with high (HR, N = 18) and low (LR, N = 18) DRF during wakefulness and sleep. During data acquisition, the subjects were presented with sounds to be ignored (first names randomly presented among pure tones) while they were watching a silent movie or sleeping. Brain responses to first names dramatically differed between the 2 groups during both sleep and wakefulness. During wakefulness, the attention-orienting brain response (P3a) and a late parietal response were larger in HR than in LR. During sleep, we also observed between-group differences at the latency of the P3a during N2 and at later latencies during all sleep stages. Our results demonstrate differences in the brain reactivity of HR and LR during both sleep and wakefulness. These results suggest that the ability to recall dreaming is associated with a particular cerebral functional organization, regardless of the state of vigilance.

> résumé PubMed


Ruby P, et al., Alpha Reactivity to Complex Sounds Differs during REM Sleep and Wakefulness, PLoS ONE 2013

Ruby P, Blochet C, Eichenlaub J-B, Bertrand O, Morlet D, Bidet-Caulet A. Alpha Reactivity to Complex Sounds Differs during REM Sleep and Wakefulness. PLoS ONE 8(11): e79989, 2013.

We aimed at better understanding the brain mechanisms involved in the processing of alerting meaningful sounds during sleep, investigating alpha activity. During EEG acquisition, subjects were presented with a passive auditory oddball paradigm including rare complex sounds called Novels (the own first name – OWN, and an unfamiliar first name – OTHER) while they were watching a silent movie in the evening or sleeping at night. During the experimental night, the subjects’ quality of sleep was generally preserved. During wakefulness, the decrease in alpha power (8–12 Hz) induced by Novels was significantly larger for OWN than for OTHER at parietal electrodes, between 600 and 900 ms after stimulus onset. Conversely, during REM sleep, Novels induced an increase in alpha power (from 0 to 1200 ms at all electrodes), significantly larger for OWN than for OTHER at several parietal electrodes between 700 and 1200 ms after stimulus onset. These results show that complex sounds have a different effect on the alpha power during wakefulness (decrease) and during REM sleep (increase) and that OWN induce a specific effect in these two states. The increased alpha power induced by Novels during REM sleep may 1) correspond to a short and transient increase in arousal; in this case, our study provides an objective measure of the greater arousing power of OWN over OTHER, 2) indicate a cortical inhibition associated with sleep protection. These results suggest that alpha modulation could participate in the selection of stimuli to be further processed during sleep.

> Accéder à l’article complet


Ruby P, et al., Alpha reactivity to first names differs in subjects with high and low dream recall frequency, Front Psychol 2013

Ruby P, Blochet C, Eichenlaub JB, Bertrand O, Morlet D, Bidet-Caulet A. Alpha reactivity to first names differs in subjects with high and low dream recall frequency. Front Psychol.;4:419, 2013.

Studies in cognitive psychology showed that personality (openness to experience, thin boundaries, absorption), creativity, nocturnal awakenings, and attitude toward dreams are significantly related to dream recall frequency (DRF). These results suggest the possibility of neurophysiological trait differences between subjects with high and low DRF. To test this hypothesis we compared sleep characteristics and alpha reactivity to sounds in subjects with high and low DRF using polysomnographic recordings and electroencephalography (EEG). We acquired EEG from 21 channels in 36 healthy subjects while they were presented with a passive auditory oddball paradigm (frequent standard tones, rare deviant tones and very rare first names) during wakefulness and sleep (intensity, 50 dB above the subject’s hearing level). Subjects were selected as High-recallers (HR, DRF = 4.42 ± 0.25 SEM, dream recalls per week) and Low-recallers (LR, DRF = 0.25 ± 0.02) using a questionnaire and an interview on sleep and dream habits. Despite the disturbing setup, the subjects’ quality of sleep was generally preserved. First names induced a more sustained decrease in alpha activity in HR than in LR at Pz (1000–1200 ms) during wakefulness, but no group difference was found in REM sleep. The current dominant hypothesis proposes that alpha rhythms would be involved in the active inhibition of the brain regions not involved in the ongoing brain operation. According to this hypothesis, a more sustained alpha decrease in HR would reflect a longer release of inhibition, suggesting a deeper processing of complex sounds than in LR during wakefulness. A possibility to explain the absence of group difference during sleep is that increase in alpha power in HR may have resulted in awakenings. Our results support this hypothesis since HR experienced more intra sleep wakefulness than LR (30 ± 4 vs. 14 ± 4 min). As a whole our results support the hypothesis of neurophysiological trait differences in high and low-recallers.

> Accéder à l’article complet


Schmidt C, et al., Circadian and homeostatic modulation of cognition-related cerebral activity in humans, J. Sleep Res. 2013

Schmidt C, Maire M, Reichert C F, Scheffler K, Klarhoefer M, Strobel W, Krebs J, Berthomier P, Berthomier C, Cajochen C. Circadian and homeostatic modulation of cognition-related cerebral activity in humans. J. Sleep Res. 21 (Suppl. 1), 1-371, 2012.


Schmidt C, et al., Circadian preference modulates the neural substrate of conflict processing across the day, PLoS One 2012

Schmidt C, Peigneux P, Leclercq Y, Sterpenich V, Vandewalle G, Philips C, Berthomier P, Berthomier C, Tinguely G, Gais S, Schabus M, Desseilles M, Dang-Vu T, Salmon E, Degueldre C, Balteau E, Luxen A, Cajochen C, Maquet P, Collette F. Circadian preference modulates the neural substrate of conflict processing across the day. PLoS One. 2012;7(1):e29658. 2012 Jan 4. PLoS One. 2012;7(1):e29658. 2012 Jan 4.

Human morning and evening chronotypes differ in their preferred timing for sleep and wakefulness, as well as in optimal daytime periods to cope with cognitive challenges. Recent evidence suggests that these preferences are not a simple by-product of socio-professional timing constraints, but can be driven by inter-individual differences in the expression of circadian and homeostatic sleep-wake promoting signals. Chronotypes thus constitute a unique tool to access the interplay between those processes under normally entrained day-night conditions, and to investigate how they impinge onto higher cognitive control processes. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on conflict processing-related cerebral activity throughout a normal waking day. Sixteen morning and 15 evening types were recorded at two individually adapted time points (1.5 versus 10.5 hours spent awake) while performing the Stroop paradigm. Results show that interference-related hemodynamic responses are maintained or even increased in evening types from the subjective morning to the subjective evening in a set of brain areas playing a pivotal role in successful inhibitory functioning, whereas they decreased in morning types under the same conditions. Furthermore, during the evening hours, activity in a posterior hypothalamic region putatively involved in sleep-wake regulation correlated in a chronotype-specific manner with slow wave activity at the beginning of the night, an index of accumulated homeostatic sleep pressure. These results shed light into the cerebral mechanisms underlying inter-individual differences of higher-order cognitive state maintenance under normally entrained day-night conditions.

> Accéder à l’article complet


Schmidt C, et al., Working memory load affects chronotype- and time-of-day dependent cerebral activity modulations, J. Sleep Res. 2010

Schmidt C, Peigneux P, Leclercq Y, Sterpenich V, Van Dewalle G, Philips C, Tinguely G, Gais S, Schabus M, Desseilles M, Dang-Vu T, Salmon E, Balteau E, Luxen A, Cajochen C, Maquet P, Collette F. Working memory load affects chronotype- and time-of-day dependent cerebral activity modulations. J. Sleep Res., 19: P541,2010.


Sterpenich V, et al., Conditioned auditory cues delivered during phasic REM sleep enhance adult human brain plasticity, J. Sleep Res. 2010

Sterpenich V, Schmidt C, Albouy G, Matarazzo L, Van Haudenhuyse A, Boveroux P, Vaessen N, Berthomier P, Berthomier C, Degueldre C, Leclercq Y, Balteau E, Collette F,Luxen A, Philips C, Maquet P. Conditioned auditory cues delivered during phasic REM sleep enhance adult human brain plasticity. J. Sleep Res., 19: O310,2010.


Schmidt C, et al., Homeostatic sleep pressure and responses to sustained attention in the suprachiasmatic area, Science 2009

Schmidt C, Collette F, Leclercq Y, Sterpenich V, Vandewalle G, Berthomier P, Berthomier C, Philipps C, Tinguely G, Darsaud A, Gais S, Schabus M, Desseilles M, Dang-Vu T, Salmon E, Balteau E, Degueldre C, Luxen A, Maquet P, Cajochen C, Peigneux P. Homeostatic sleep pressure and responses to sustained attention in the suprachiasmatic area. Science, 324 (5926):516-9, 2009.

Throughout the day, cognitive performance is under the combined influence of circadian processes and homeostatic sleep pressure. Some people perform best in the morning, whereas others are more alert in the evening. These chronotypes provide a unique way to study the effects of sleep-wake regulation on the cerebral mechanisms supporting cognition. Using functional magnetic resonance imaging in extreme chronotypes, we found that maintaining attention in the evening was associated with higher activity in evening than morning chronotypes in a region of the locus coeruleus and in a suprachiasmatic area (SCA) including the circadian master clock. Activity in the SCA decreased with increasing homeostatic sleep pressure. This result shows the direct influence of the homeostatic and circadian interaction on the neural activity underpinning human behavior.

> vers PubMed


Schmidt C, et al., Stroop-related cerebral activity is modulated by time of day and chronotype, NeuroImage, 47:S39-S41, 2009

Schmidt C, Peigneux P, Leclercq Y, Sterpenich V, Vandewalle G, Berthomier P, Berthomier C, Philipps C, Tinguely G, Gais S, Schabus M, Balteau E, Luxen A, Maquet P, Cajochen C and Collette F. Stroop-related cerebral activity is modulated by time of day and chronotype. NeuroImage, 47:S39-S41, 2009.


VALIDATION


Berthomier C, et al., Assessment of an automatic analysis method of the Karolinska drowsiness test, J. Sleep Res. 2012

Berthomier C, Berthomier P, Brandewinder M, Mattout J, Philip P, Taillard J. Assessment of an automatic analysis method of the Karolinska drowsiness test. J. Sleep Res. 21 (Suppl. 1), 1-371, 2012.


Van Beers P, et al., HRV Analysis during Sleep: Clinical Interest of a New Automatic Sleep Analysis. Sleep 2009, Seattle, WA, USA.

Van Beers P, Berthomier C, Prado J, Berthomier P, Coste O. HRV Analysis during Sleep: Clinical Interest of a New Automatic Sleep Analysis. Sleep, 32:A374, 2009.


Berthomier C, et al., Real-Time Automatic Measure of Drowsiness based on a Single EEG Channel. J. Sleep Res. 2008, Glasgow, UK.

Berthomier C, Muzet A, Berthomier P, Prado J, Mattout J, Real-Time Automatic Measure of Drowsiness based on a Single EEG Channel. J. Sleep Res., 17:P434, 2008.


Berthomier C, et al., Real-Time Automatic Wake/Sleep Scoring based on a Single EEG Channel. Sleep, 2008, Baltimore, MD, USA.

Berthomier C, Herman-Stoïca M, Berthomier P, Drouot X, Prado J, Mattout J, d’Ortho MP, Real-Time Automatic Wake/Sleep Scoring based on a Single EEG Channel. Sleep, 31:A338, 2008.


Berthomier C, et al., Automatic Analysis of Single-Channel Sleep EEG: Validation in Healthy Individuals. Sleep, 2007.

Berthomier C, Drouot X, Herman-Stoïca M, Berthomier P, Prado J, Bokar-thiré D, Benoit O, Mattout J, d’Ortho M-P, Automatic Analysis of Single-Channel Sleep EEG: Validation in Healthy Individuals. Sleep, 30(11):1587-95, 2007.

STUDY OBJECTIVE: To assess the performance of automatic sleep scoring software (ASEEGA) based on a single EEG channel comparatively with manual scoring (2 experts) of conventional full polysomnograms.
DESIGN: Polysomnograms from 15 healthy individuals were scored by 2 independent experts using conventional R&K rules. The results were compared to those of ASEEGA scoring on an epoch-by-epoch basis.
SETTING: Sleep laboratory in the physiology department of a teaching hospital.
PARTICIPANTS: Fifteen healthy volunteers.
MEASUREMENTS AND RESULTS: The epoch-by-epoch comparison was based on classifying into 2 states (wake/sleep), 3 states (wake/REM/ NREM), 4 states (wake/REM/stages 1-2/SWS), or 5 states (wake/REM/ stage 1/stage 2/SWS). The obtained overall agreements, as quantified by the kappa coefficient, were 0.82, 0.81, 0.75, and 0.72, respectively. Furthermore, obtained agreements between ASEEGA and the expert consensual scoring were 96.0%, 92.1%, 84.9%, and 82.9%, respectively. Finally, when classifying into 5 states, the sensitivity and positive predictive value of ASEEGA regarding wakefulness were 82.5% and 89.7%, respectively. Similarly, sensitivity and positive predictive value regarding REM state were 83.0% and 89.1%.
CONCLUSIONS: Our results establish the face validity and convergent validity of ASEEGA for single-channel sleep analysis in healthy individuals. ASEEGA appears as a good candidate for diagnostic aid and automatic ambulant scoring.

> Vers l’article complet


Berthomier C, et al., Real-Time Automatic Measurement of Recorded Sleep Time. Chest 2007, Chicago, Il, USA.

Berthomier C, Berthomier P, Herman-Stoïca M, Drouot X, Prado J, Benoit O, Mattout J, d’Ortho MP, Real-Time Automatic Measurement of Recorded Sleep Time. Chest, 132(4):649S, 2007.


Berthomier C,et al., Wake-REM-NREM Automatic Classification based on a Single EEG Channel: Epoch-by-Epoch Comparison with Human Sleep Scoring in Patients. J. Sleep Res. 2006, Innsbruck, Austria.

Berthomier C, Drouot X, Herman-Stoïca M, Berthomier P, Prado J, Benoit O, Mattout J, d’Ortho M-P, Wake-REM-NREM Automatic Classification based on a Single EEG Channel: Epoch-by-Epoch Comparison with Human Sleep Scoring in Patients. J. Sleep Res., 15:P295, 2006.


Berthomier C, et al., Single Channel based Brain Monitoring: Sleep/Wakefulness classification. Int. conf. of SENSATION/ESRS on Monitoring sleep and sleepiness - from physiology to new sensors, 2006, Basel, Switzerland.

Berthomier C, Drouot X, Herman-Stoïca M, Berthomier P, Prado J, Mattout J, d’Ortho M-P, Single Channel based Brain Monitoring: Sleep/Wakefulness classification. Int. conf. of SENSATION/ESRS on Monitoring sleep and sleepiness – from physiology to new sensors, 2006.


Berthomier C, et al., A Wake-REM-NREM Automatic Analysis Using a Single EEG Channel: Epoch by Epoch Comparison with Human Sleep Scoring in Healthy Subjects. Sleep Medicine 2005, Berlin, Germany.

Berthomier C, Drouot X, Herman-Stoïca M, Berthomier P, Prado J, Mattout J, d’Ortho MP, A Wake-REM-NREM Automatic Analysis Using a Single EEG Channel: Epoch by Epoch Comparison with Human Sleep Scoring in Healthy Subjects. Sleep Medicine, 6:S194, 2005.


Berthomier C, Prado J & Benoit O, Automatic sleep EEG analysis using filter banks, Biomedical Sciences Instrumentation 1999.

Berthomier C, Prado J and Benoit O, Automatic sleep EEG analysis using filter banks, in Biomedical Sciences Instrumentation, 35():241-6, 1999.

Filter banks analysis is an easy and quick computing way to implement time-scale methods, these being well suited for short events as well as for large waveforms detection tasks. We propose a non-uniform oversampled filter banks to analyze sleep EEG single channel signal, the different subbands matching the classical EEG rhythms. In order to preserve the temporal shapes information, filter banks are oversampled. Coupling the informations conveyed by the different outputs allow to perform an automatic hypnogram.

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Berthomier C, Prado J & Benoit O, EEG analysis using non-uniform oversampled filter banks, Biomedical Sciences Instrumentation 1998.

Berthomier C, Prado J and Benoit O, EEG analysis using non-uniform oversampled filter banks, in Biomedical Sciences Instrumentation, 34():119-24, 1997.

Time-frequency or time-scale methods are well suited for short events as well as for large waveforms detection tasks. Filter banks analysis is an easy and quick computing way to implement these methods. We propose a non-uniform oversampled filter banks to analyze EEG single channel signal, the different subbands matching the classical EEG rhythms. We use oversampled filter banks to preserve the temporal shapes information. In order to illustrate this method, we show different spindle temporal structures as also their meaning in terms of sleep stage detection.

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