Publications by authors named "Nicklas Linz"

6 Publications

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Remote cognitive assessment of older adults in rural areas by telemedicine and automatic speech and video analysis: protocol for a cross-over feasibility study.

BMJ Open 2021 09 2;11(9):e047083. Epub 2021 Sep 2.

Cobtek (Cognition-Behaviour-Technology) Lab, FRIS, Universite Cote d'Azur, Nice, France.

Introduction: Early detection of cognitive impairments is crucial for the successful implementation of preventive strategies. However, in rural isolated areas or so-called 'medical deserts', access to diagnosis and care is very limited. With the current pandemic crisis, now even more than ever, remote solutions such as telemedicine platforms represent great potential and can help to overcome this barrier. Moreover, current advances made in voice and image analysis can help overcome the barrier of physical distance by providing additional information on a patients' emotional and cognitive state. Therefore, the aim of this study is to evaluate the feasibility and reliability of a videoconference system for remote cognitive testing empowered by automatic speech and video analysis.

Methods And Analysis: 60 participants (aged 55 and older) with and without cognitive impairment will be recruited. A complete neuropsychological assessment including a short clinical interview will be administered in two conditions, once by telemedicine and once by face-to-face. The order of administration procedure will be counterbalanced so half of the sample starts with the videoconference condition and the other half with the face-to-face condition. Acceptability and user experience will be assessed among participants and clinicians in a qualitative and quantitative manner. Speech and video features will be extracted and analysed to obtain additional information on mood and engagement levels. In a subgroup, measurements of stress indicators such as heart rate and skin conductance will be compared.

Ethics And Dissemination: The procedures are not invasive and there are no expected risks or burdens to participants. All participants will be informed that this is an observational study and their consent taken prior to the experiment. Demonstration of the effectiveness of such technology makes it possible to diffuse its use across all rural areas ('medical deserts') and thus, to improve the early diagnosis of neurodegenerative pathologies, while providing data crucial for basic research. Results from this study will be published in peer-reviewed journals.
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September 2021

Patients with amnestic MCI Fail to Adapt Executive Control When Repeatedly Tested with Semantic Verbal Fluency Tasks.

J Int Neuropsychol Soc 2021 Jun 30:1-8. Epub 2021 Jun 30.

University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.

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.
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June 2021

Measuring Stress in Health Professionals Over the Phone Using Automatic Speech Analysis During the COVID-19 Pandemic: Observational Pilot Study.

J Med Internet Res 2021 04 19;23(4):e24191. Epub 2021 Apr 19.

CoBteK (Cognition-Behaviour-Technology) Lab, La Fédération de Recherche Interventions en Santé, Université Côte d'Azur, Nice, France.

Background: During 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.

Objective: This 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.

Methods: Speech 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.

Results: Certain 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).

Conclusions: Automatic 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.
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April 2021

Detecting Apathy in Older Adults with Cognitive Disorders Using Automatic Speech Analysis.

J Alzheimers Dis 2019 ;69(4):1183-1193

CoBTeK (Cognition-Behaviour-Technology) Lab, Memory Center CHU, Université Côte d'Azur, Nice, France.

Background: Apathy is present in several psychiatric and neurological conditions and has been found to have a severe negative effect on disease progression. In older people, it can be a predictor of increased dementia risk. Current assessment methods lack objectivity and sensitivity, thus new diagnostic tools and broad-scale screening technologies are needed.

Objective: This study is the first of its kind aiming to investigate whether automatic speech analysis could be used for characterization and detection of apathy.

Methods: A group of apathetic and non-apathetic patients (n = 60) with mild to moderate neurocognitive disorder were recorded while performing two short narrative speech tasks. Paralinguistic markers relating to prosodic, formant, source, and temporal qualities of speech were automatically extracted, examined between the groups and compared to baseline assessments. Machine learning experiments were carried out to validate the diagnostic power of extracted markers.

Results: Correlations between apathy sub-scales and features revealed a relation between temporal aspects of speech and the subdomains of reduction in interest and initiative, as well as between prosody features and the affective domain. Group differences were found to vary for males and females, depending on the task. Differences in temporal aspects of speech were found to be the most consistent difference between apathetic and non-apathetic patients. Machine learning models trained on speech features achieved top performances of AUC = 0.88 for males and AUC = 0.77 for females.

Conclusions: These findings reinforce the usability of speech as a reliable biomarker in the detection and assessment of apathy.
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September 2020

Exploitation vs. exploration-computational temporal and semantic analysis explains semantic verbal fluency impairment in Alzheimer's disease.

Neuropsychologia 2019 08 20;131:53-61. Epub 2019 May 20.

Chair for Development of Language, Learning & Action, University of Saarland, Germany.

Impaired Semantic Verbal Fluency (SVF) in dementia due to Alzheimer's Disease (AD) and its precursor Mild Cognitive Impairment (MCI) is well known. Yet, it remains open whether this impairment mirrors the breakdown of semantic memory retrieval processes or executive control processes. Therefore, qualitative analysis of the 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 SVF impairment in AD and MCI. This study uses a qualitative computational approach-combining temporal and semantic information-to investigate exploitation and exploration patterns as indicators for semantic memory retrieval and executive control processes. Audio SVF recordings of 20 controls (C, 66-81 years), 55 MCI (57-94 years) and 20 AD subjects (66-82 years) were assessed while groups were matched according to age and education. All groups produced, on average, the same amount of semantically related items in rapid succession within word clusters. Conversely, towards AD, there was a clear decline in semantic as well as temporal exploration patterns between clusters. Results strongly point towards preserved exploitation-semantic memory retrieval processes-and hampered exploration-executive control processes-in AD and potentially in MCI.
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August 2019

Fully Automatic Speech-Based Analysis of the Semantic Verbal Fluency Task.

Dement Geriatr Cogn Disord 2018 8;45(3-4):198-209. Epub 2018 Jun 8.

Memory Clinic, Association IA, CoBTek Lab, CHU Université Côte d'Azur, Nice, France.

Background: Semantic verbal fluency (SVF) tests are routinely used in screening for mild cognitive impairment (MCI). In this task, participants name as many items as possible of a semantic category under a time constraint. Clinicians measure task performance manually by summing the number of correct words and errors. More fine-grained variables add valuable information to clinical assessment, but are time-consuming. Therefore, the aim of this study is to investigate whether automatic analysis of the SVF could provide these as accurate as manual and thus, support qualitative screening of neurocognitive impairment.

Methods: SVF data were collected from 95 older people with MCI (n = 47), Alzheimer's or related dementias (ADRD; n = 24), and healthy controls (HC; n = 24). All data were annotated manually and automatically with clusters and switches. The obtained metrics were validated using a classifier to distinguish HC, MCI, and ADRD.

Results: Automatically extracted clusters and switches were highly correlated (r = 0.9) with manually established values, and performed as well on the classification task separating HC from persons with ADRD (area under curve [AUC] = 0.939) and MCI (AUC = 0.758).

Conclusion: The results show that it is possible to automate fine-grained analyses of SVF data for the assessment of cognitive decline.
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November 2018