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

König, Alexandra; Linz, Nicklas; Zeghari, Radia; Klinge, Xenia; Tröger, J.; Alexandersson, Jan; Robert, Philippe

doi:10.3233/jad-181033

Cited by 46 publications

(41 citation statements)

References 47 publications

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“…It was not specified whether the event had to be experienced during COVID-19; thus, it was open to the participant to recall whatever event first came to mind. These free-speech tasks were used in previous studies [18,25] and allowed for a greater range of induced emotional effects, potentially sensitive to signs of stress and depression. The comparison of speech features between neutral and emotionally loaded questions may give insight into the affective state of participants.…”

Section: Methodsmentioning

confidence: 99%

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

König¹,

Riviere²,

Linz³

et al. 2021

J Med Internet Res

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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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Section: Methodsmentioning

confidence: 99%

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

König¹,

Riviere²,

Linz³

et al. 2021

J Med Internet Res

Self Cite

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“…The use of objective measures has been recommended for assessing apathy in clinical trials including actigraphy (Cummings et al, 2015). Galvanic skin response, heart rate (Treusch et al, 2015), and more recently, speech analysis (König et al, 2019) and their association with apathy have also been examined. Therefore, to measure rest and physical activity, all three groups have the GENEActiv wrist-worn accelerometer (Activinsights, Kimbolton, Cambridgeshire, UK) fitted for a period of 48 hours at baseline, this is repeated after follow-up.…”

Section: Baselinementioning

confidence: 99%

Virtual reality intervention to improve apathy in residential aged care: protocol for a multi-site trial

Saredakis¹,

Keage²,

Corlis³

et al. 2020

Preprint

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Background: Apathy is a prevalent neuropsychiatric symptom for older adults residing in aged care. Left untreated, apathy has been associated with accelerated cognitive decline and increased risk of mortality. Pharmacological interventions have not been established and can have side effects, placing a priority on the evaluation of non-pharmacological interventions. Reminiscence therapy, a psychosocial, person-centred intervention is commonly used in aged care and has demonstrated to reduce apathy. Traditional methods of reminiscence utilise physical objects and more recently technology including tablets and laptop computers have demonstrated potential. Virtual reality (VR) has successfully been used to treat psychological disorders, however there is little evidence on using VR for behavioural symptoms such as apathy in older adults. Using VR to deliver reminiscence therapy provides an immersive experience, and readily available applications provide access to a large range of content allowing easier delivery of therapy over traditional forms of therapy. This study aims to examine the effect of tailored reminiscence therapy using VR on apathy.Methods: In this multi-site trial, participants will be allocated to one of three groups; a reminiscence therapy intervention using VR; an active control using a laptop computer or physical items; and a passive control usual care group. A total of 45 participants will be recruited from residential aged care (15 in each group). The three groups will be compared at baseline and follow-up. The primary outcome is apathy, secondary outcomes include cognition and depression. Side effects from using head-mounted displays will also be examined in the VR group.Discussion: This study intends to establish if using VR reminiscence therapy improves levels of apathy compared to traditional reminiscence therapy or usual care. Results from this study will inform the therapeutic use of VR for older adults residing in aged care and provide knowledge for implementing VR into existing lifestyle activities in this context.Trial registration: This trial was registered in the Australian and New Zealand Clinical Trials Registry (ACTRN12619001510134). Registered 31 October 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378564&isReview=true

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“…Другая область применения анализа речипсихиатрия, где с помощью этой технологии определяют уровень стресса [17] и апатии у взрослых [18].…”

Section: анализ речиunclassified

“…В клинической практике используются голосовые помощники. Они дают возможность перевести речь врача в текст, например, при ведении медицинской документации, или выполнить простейшие действия на компьютере [18,19].…”

Section: анализ речиunclassified

Application of artificial intelligence in medical data analysis

Бурсов

2019

Alʹm. klin. med.

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

Cited by 46 publications

References 47 publications

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

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

Virtual reality intervention to improve apathy in residential aged care: protocol for a multi-site trial

Application of artificial intelligence in medical data analysis

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