المؤلفون: Jessica Peter, Nicklas Linz, Johannes Tröger, Hali Lindsay, Jutta Kray, Mario Magued Mina, Stefan Klöppel

مصطلحات موضوعية: medicine.medical_specialty, Neuropsychological Tests, Audiology, behavioral disciplines and activities, 050105 experimental psychology, Task (project management), Executive Function, 03 medical and health sciences, 0302 clinical medicine, medicine, Humans, Semantic memory, Verbal fluency test, Cognitive Dysfunction, 0501 psychology and cognitive sciences, In patient, Latency (engineering), Control (linguistics), Set (psychology), Point (typography), General Neuroscience, 05 social sciences, Semantics, Psychiatry and Mental health, Clinical Psychology, 150 Psychologie, Neurology (clinical), Psychology, 610 Medizin und Gesundheit, 030217 neurology & neurosurgery

الوصف: Objective:Semantic verbal fluency (SVF) tasks require individuals to name items from a specified category within a fixed time. An impaired SVF performance is well documented in patients with amnestic Mild Cognitive Impairment (aMCI). The two leading theoretical views suggest either loss of semantic knowledge or impaired executive control to be responsible.Method:We assessed SVF 3 times on 2 consecutive days in 29 healthy controls (HC) and 29 patients with aMCI with the aim to answer the question which of the two views holds true.Results:When doing the task for the first time, patients with aMCI produced fewer and more common words with a shorter mean response latency. When tested repeatedly, only healthy volunteers increased performance. Likewise, only the performance of HC indicated two distinct retrieval processes: a prompt retrieval of readily available items at the beginning of the task and an active search through semantic space towards the end. With repeated assessment, the pool of readily available items became larger in HC, but not patients with aMCI.Conclusion:The production of fewer and more common words in aMCI points to a smaller search set and supports the loss of semantic knowledge view. The failure to improve performance as well as the lack of distinct retrieval processes point to an additional impairment in executive control. Our data did not clearly favour one theoretical view over the other, but rather indicates that the impairment of patients with aMCI in SVF is due to a combination of both.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96ce4e29fbe653cb195d5c036779cfb4Test

المؤلفون: Pascale Lemoine, Philippe Robert, Vincent Bultingaire, Alexandra König, Nicklas Linz, Radia Zeghari, Rachid Guerchouche, Inez H.G.B. Ramakers

المصدر: Alzheimer's & Dementia. 16

مصطلحات موضوعية: 0303 health sciences, Telemedicine, Epidemiology, business.industry, Remote patient monitoring, Health Policy, medicine.disease, 03 medical and health sciences, Psychiatry and Mental health, Cellular and Molecular Neuroscience, 0302 clinical medicine, Developmental Neuroscience, Medicine, Dementia, Neurology (clinical), Medical emergency, Geriatrics and Gerontology, business, 030217 neurology & neurosurgery, 030304 developmental biology

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::0cb638aff51460d2be335b03b85cdca4Test
https://doi.org/10.1002/alz.047345Test

المؤلفون: Jan Alexandersson, Johannes Tröger, Jutta Kray, Philippe Robert, Alexandra König, Nicklas Linz, Jessica Peter

المساهمون: Deutsches Forschungszentrum für Künstliche Intelligenz GmbH = German Research Center for Artificial Intelligence (DFKI), Cognition Behaviour Technology (CobTek), Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre Hospitalier Universitaire de Nice (CHU Nice)-Institut Claude Pompidou [Nice] (ICP - Nice), Spatio-Temporal Activity Recognition Systems (STARS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Psychiatric University Clinic [Bern] (UPD), Faculty of Medicine [Bern], University of Bern-University of Bern, Saarland University [Saarbrücken], This research was partially funded by the EIT Digital WellbeingActivity 17074, ELEMENT. The data was partially collected during theEU FP7 Dem@Care project, grant agreement 288199. The authors liketo thank Hali Lindsay and Katja Häuser for helpful feedback on anearlier version of the manuscript., Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre Hospitalier Universitaire de Nice (CHU Nice)-Institut Claude Pompidou [Nice] (ICP - Nice)-Université Côte d'Azur (UCA)

المصدر: Neuropsychologia
Neuropsychologia, Elsevier, 2019, 131, pp.53-61. ⟨10.1016/j.neuropsychologia.2019.05.007⟩
Neuropsychologia, 2019, 131, pp.53-61. ⟨10.1016/j.neuropsychologia.2019.05.007⟩

مصطلحات موضوعية: Male, Cognitive Neuroscience, Semantic analysis (machine learning), Experimental and Cognitive Psychology, Disease, Semantic speech analysis, Neuropsychological Tests, MCI (mild cognitive impairment), 050105 experimental psychology, Speech Disorders, 03 medical and health sciences, Behavioral Neuroscience, [SCCO]Cognitive science, 0302 clinical medicine, Qualitative analysis, Alzheimer Disease, medicine, Semantic memory, Dementia, Verbal fluency test, Humans, Speech, 0501 psychology and cognitive sciences, Control (linguistics), Aged, Aged, 80 and over, 05 social sciences, Alzheimer's disease, Temporal analysis, medicine.disease, Clinical Practice, Female, Psychology, 030217 neurology & neurosurgery, Cognitive psychology

الوصف: International audience; Contents lists available atScienceDirectNeuropsychologiajournal homepage:www.elsevier.com/locate/neuropsychologiaExploitation vs. exploration—computational temporal and semantic analysisexplains semantic verbalfluency impairment in Alzheimer's diseaseJohannes Trögera,∗, Nicklas Linza, Alexandra Königb, Philippe Robertb, Jan Alexanderssona,Jessica Peterc, Jutta KraydaGerman Research Center for Artificial Intelligence (DFKI), GermanybMemory Center, CoBTeK, IA CHU Université Côte d’Azur, FrancecUniversity Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, SwitzerlanddChair for Development of Language, Learning & Action, University of Saarland, GermanyARTICLE INFOKeywords:Alzheimer's diseaseMCI (mild cognitive impairment)Semantic speech analysisTemporal analysisABSTRACTImpaired Semantic Verbal Fluency (SVF) in dementia due to Alzheimer's Disease (AD) and its precursor MildCognitive Impairment (MCI) is well known. Yet, it remains open whether this impairment mirrors the break-down of semantic memory retrieval processes or executive control processes. Therefore, qualitative analysis ofthe SVF has been proposed but is limited in terms of methodology and feasibility in clinical practice.Consequently, research draws no conclusive picture which of these afore-mentioned processes drives the SVFimpairment in AD and MCI. This study uses a qualitative computational approach—combining temporal andsemantic information—to investigate exploitation and exploration patterns as indicators for semantic memoryretrieval and executive control processes. Audio SVF recordings of 20 controls (C, 66–81 years), 55 MCI (57–94years) and 20 AD subjects (66–82 years) were assessed while groups were matched according to age and edu-cation. All groups produced, on average, the same amount of semantically related items in rapid successionwithin word clusters. Conversely, towards AD, there was a clear decline in semantic as well as temporal ex-ploration patterns between clusters. Results strongly point towards preserved exploitation—semantic memoryretrieval processes—and hampered exploration—executive control processes—in AD and potentially in MCI.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b94614d2fe916c6cf12bab8784723924Test

المؤلفون: Hali Lindsay, Philippe Robert, Nicklas Linz, Julia Elbaum, Kevin Riviere, Alexandre Derreumaux, Roxane Fabre, Alexandra König

المساهمون: Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria), Spatio-Temporal Activity Recognition Systems (STARS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Hospitalier Universitaire de Nice (CHU Nice), ki:elements [Saarbrücken], Deutsches Forschungszentrum für Künstliche Intelligenz GmbH = German Research Center for Artificial Intelligence (DFKI), Cognition Behaviour Technology (CobTek), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre Hospitalier Universitaire de Nice (CHU Nice)-Institut Claude Pompidou [Nice] (ICP - Nice)-Université Côte d'Azur (UCA)

المصدر: Journal of Medical Internet Research, Vol 23, Iss 4, p e24191 (2021)
Journal of Medical Internet Research
Journal of Medical Internet Research, 2021, 23 (4), pp.e24191. ⟨10.2196/24191⟩
Journal of Medical Internet Research, JMIR Publications, 2021, 23 (4), pp.e24191. ⟨10.2196/24191⟩

مصطلحات موضوعية: Adult, Male, Health Personnel, speech, Computer applications to medicine. Medical informatics, 0206 medical engineering, R858-859.7, Pilot Projects, Health Informatics, 02 engineering and technology, Anxiety, Speech Acoustics, Voice analysis, phone monitoring, [SCCO]Cognitive science, 03 medical and health sciences, 0302 clinical medicine, Phone, Surveys and Questionnaires, Health care, medicine, Humans, Stress measures, Burnout, Professional, Pandemics, Original Paper, computer linguistics, SARS-CoV-2, business.industry, COVID-19, 020601 biomedical engineering, Telephone, 3. Good health, voice analysis, Female, Observational study, Public aspects of medicine, RA1-1270, medicine.symptom, business, Psychology, Psychosocial, 030217 neurology & neurosurgery, stress detection, Clinical psychology

الوصف: BackgroundDuring the COVID-19 pandemic, health professionals have been directly confronted with the suffering of patients and their families. By making them main actors in the management of this health crisis, they have been exposed to various psychosocial risks (stress, trauma, fatigue, etc). Paradoxically, stress-related symptoms are often underreported in this vulnerable population but are potentially detectable through passive monitoring of changes in speech behavior.ObjectiveThis study aims to investigate the use of rapid and remote measures of stress levels in health professionals working during the COVID-19 outbreak. This was done through the analysis of participants’ speech behavior during a short phone call conversation and, in particular, via positive, negative, and neutral storytelling tasks.MethodsSpeech samples from 89 health care professionals were collected over the phone during positive, negative, and neutral storytelling tasks; various voice features were extracted and compared with classical stress measures via standard questionnaires. Additionally, a regression analysis was performed.ResultsCertain speech characteristics correlated with stress levels in both genders; mainly, spectral (ie, formant) features, such as the mel-frequency cepstral coefficient, and prosodic characteristics, such as the fundamental frequency, appeared to be sensitive to stress. Overall, for both male and female participants, using vocal features from the positive tasks for regression yielded the most accurate prediction results of stress scores (mean absolute error 5.31).ConclusionsAutomatic speech analysis could help with early detection of subtle signs of stress in vulnerable populations over the phone. By combining the use of this technology with timely intervention strategies, it could contribute to the prevention of burnout and the development of comorbidities, such as depression or anxiety.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2dca6c3a053b0e42769a679c9562ebeTest
https://doi.org/10.2196/24191Test

المؤلفون: Dimitrios Kokkinakis, Nicklas Linz, Philippe Robert, Frank Rudzicz, Jan Alexandersson, Bai Li, Alexandra König, Kathleen C. Fraser, Kristina Lundholm Fors

المصدر: NAACL-HLT (1)

مصطلحات موضوعية: Domain adaptation, Training set, business.industry, Computer science, computer.software_genre, medicine.disease, Task (project management), 030507 speech-language pathology & audiology, 03 medical and health sciences, 0302 clinical medicine, medicine, Dementia, Language modelling, Language model, Artificial intelligence, 0305 other medical science, business, Set (psychology), computer, 030217 neurology & neurosurgery, Natural language processing

الوصف: There is growing evidence that changes in speech and language may be early markers of dementia, but much of the previous NLP work in this area has been limited by the size of the available datasets. Here, we compare several methods of domain adaptation to augment a small French dataset of picture descriptions (n = 57) with a much larger English dataset (n = 550), for the task of automatically distinguishing participants with dementia from controls. The first challenge is to identify a set of features that transfer across languages; in addition to previously used features based on information units, we introduce a new set of features to model the order in which information units are produced by dementia patients and controls. These concept-based language model features improve classification performance in both English and French separately, and the best result (AUC = 0.89) is achieved using the multilingual training set with a combination of information and language model features.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::f36e527a739665c9382b8af3ae241d45Test
https://doi.org/10.18653/v1/n19-1367Test

المؤلفون: Jan Alexandersson, Philippe Robert, Alexandra König, Nicklas Linz, Johannes Tröger

المصدر: PervasiveHealth

مصطلحات موضوعية: Computer science, business.industry, Word error rate, computer.software_genre, medicine.disease, 3. Good health, 03 medical and health sciences, Statistical classification, 0302 clinical medicine, Resource (project management), Pattern recognition (psychology), Classifier (linguistics), medicine, Dementia, Verbal fluency test, 030212 general & internal medicine, Artificial intelligence, Cognitive decline, business, computer, 030217 neurology & neurosurgery, Natural language processing

الوصف: Dementia has a large economic impact on our society as cost-effective population-wide screening for early signs of dementia is still an unsolved medical supply resource problem. A solution should be fast, require a minimum of external material, and automatically indicate potential persons at risk of cognitive decline. Despite encouraging results, leveraging pervasive sensing technologies for automatic dementia screening, there are still two main issues: significant hardware costs or installation efforts and the challenge of effective pattern recognition. Conversely, automatic speech recognition (ASR) and speech analysis have reached sufficient maturity and allow for low-tech remote telephone-based screening scenarios. Therefore, we examine the technologic feasibility of automatically assessing a neuropsychological test---Semantic Verbal Fluency (SVF)--via a telephone-based solution. We investigate its suitability for inclusion into an automated dementia frontline screening and global risk assessment, based on concise telephone-sampled speech, ASR and machine learning classification. Results are encouraging showing an area under the curve (AUC) of 0.85. We observe a relatively low word error rate of 33% despite phone-quality speech samples and a mean age of 77 years of the participants. The automated classification pipeline performs equally well compared to the classifier trained on manual transcriptions of the same speech data. Our results indicate SVF as a prime candidate for inclusion into an automated telephone-screening system.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::db927cef3a693060a6ddc3765aed10acTest
https://doi.org/10.1145/3240925.3240943Test

المؤلفون: Johannes Tröger, Nicklas Linz, Philippe Robert, Alexandra König, Maria Wolters, Jan Alexandersson

المساهمون: Deutsches Forschungszentrum für Künstliche Intelligenz GmbH = German Research Center for Artificial Intelligence (DFKI), Cognition Behaviour Technology (CobTek), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre Hospitalier Universitaire de Nice (CHU Nice)-Institut Claude Pompidou [Nice] (ICP - Nice)-Université Côte d'Azur (UCA), Spatio-Temporal Activity Recognition Systems (STARS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), University of Edinburgh, Université Nice Sophia Antipolis (... - 2019) (UNS)

المصدر: ICDM 2017-IEEE International Conference on Data Mining, Workshop on Data Mining for Aging, Rehabilitation and Independent Assisted Living
ICDM 2017-IEEE International Conference on Data Mining, Workshop on Data Mining for Aging, Rehabilitation and Independent Assisted Living, Nov 2017, New Orleans, United States. pp.719-728, ⟨10.1109/ICDMW.2017.100⟩
ICDM Workshops
Linz, N, Troeger, J, Alexandersson, J, Koenig, A, Robert, P & Wolters, M 2017, Predicting Dementia Screening and Staging Scores From Semantic Verbal Fluency Performance . in First Workshop on Data Mining for Aging, Rehabilitation and Independent Assisted Living . Institute of Electrical and Electronics Engineers (IEEE), 2017 IEEE International Conference on Data Mining Workshops, New Orleans, Louisiana, United States, 18/11/17 . https://doi.org/10.1109/ICDMW.2017.100Test

مصطلحات موضوعية: Mini–Mental State Examination, medicine.diagnostic_test, Clinical Dementia Rating, 05 social sciences, Regression analysis, Cognition, medicine.disease, 050105 experimental psychology, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], Cognitive test, 03 medical and health sciences, 0302 clinical medicine, mental disorders, medicine, Verbal fluency test, Dementia, 0501 psychology and cognitive sciences, Set (psychology), Psychology, 030217 neurology & neurosurgery, Clinical psychology

الوصف: International audience; The standard dementia screening tool Mini Mental State Examination (MMSE) and the standard dementia staging tool Clinical Dementia Rating Scale (CDR) are prominent methods for answering questions whether a person might have dementia and about the dementia severity respectively. These methods are time consuming and require well-educated personnel to administer. Conversely, cognitive tests, such as the Semantic Verbal Fluency (SVF), demand little time. With this as a starting point, we investigate the relation between SVF results and MMSE/CDR-SOB scores. We use regression models to predict scores based on persons' SVF performance. Over a set of 179 patients with different degree of dementia, we achieve a mean absolute error of of 2.2 for MMSE (range 0–30) and 1.7 for CDR-SOB (range 0–18). True and predicted scores agree with a Cohen's κ of 0.76 for MMSE and 0.52 for CDR-SOB. We conclude that our approach has potential to serve as a cheap dementia screening, possibly even in non-clinical settings.

وصف الملف: application/pdf

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea4a62da9cbde6bab99072d432da428cTest
https://inria.hal.science/hal-01672590Test

المؤلفون: Jan Alexandersson, Nicklas Linz, Philippe Robert, Kathleen C. Fraser, Francois Bremond, Alexandra König, Maria Wolters, Liam D. Kaufman, Johannes Tröger, Frank Rudzicz

المصدر: Alzheimer's & Dementia. 13

مصطلحات موضوعية: 030214 geriatrics, Basis (linear algebra), Epidemiology, Health Policy, Early detection, Cognition, medicine.disease, 03 medical and health sciences, Psychiatry and Mental health, Cellular and Molecular Neuroscience, 0302 clinical medicine, Developmental Neuroscience, medicine, Dementia, Neurology (clinical), Geriatrics and Gerontology, Psychology, 030217 neurology & neurosurgery, Cross linguistic, Cognitive psychology

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::fe28c0202ff15f467f8bb8074f5d32f5Test
https://doi.org/10.1016/j.jalz.2017.06.311Test