Raum:
Raum M6
Topic:
Wissenschaftliches Programm
Topic 01: Neurokognitive Erkrankungen, organische psychische Störungen, Demenz, F0
Topic 19: Früherkennung, Prävention und Gesundheitsförderung
Topic 22: Versorgungsforschung und Versorgungsmodelle
English programme
Format:
Symposium
Dauer:
90 Minuten
Digital assistive technology devices (ATD) usable at point of care (i.e., patients’ resident homes) have three potential key applications for older people with manifest or prodromal stages of dementia:
1. Continuous monitoring of the cognitive and functional status in everyday environment to identify early signs of pathological change in long-term prevention clinical studies.
2. Real world evidence on the effect of treatments on cognitive and functional abilities in intervention clinical trials.
3. Assisted living systems supporting seniors with cognitive decline to maintain everyday function and socially salient activities.
The symposium will cover concrete examples of user centered development of digital ATDs.
Jessica Janson will present a new ATD embedded in a lifestyle detection and counseling system. The system is being developed in the framework of the H2020 ITN Marie S. Curie project “BBDiag” in close cooperation with seniors with cognitive deficits, caregivers and other stakeholders.
Alexandra König will present a novel ATD for automatic speech analysis which can usefully be employed for monitoring social interaction and speech production during everyday activities To improve adherence, it is currently explored as a potential remote pre-screening and monitoring tool of patients in clinical trials.
Doreen Görß will present the development of a new ATD to help family caregivers to cope with challenging behavior of people with dementia. This system incorporates nursing care knowledge and automated detection of behavioral features in a digital expert system.
Themis Exarchos will present an outlook on digital ATD implementation in society and markets, related to ongoing and future developments of digital and computational biomarkers for early diagnosis and prognosis.
In summary, the symposium will present chances and challenges of digital ATDs for dementia care and research with a strong focus on user centered design and stakeholder involvement.
Lifestyle detection and counseling point of care device for older people at risk for dementia
Jessica Janson, Rom (Italy)
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Jessica Janson, Rom (Italy)
In Germany 1.5 million people live with dementia, this number will double until 2050 [1]. 60–70% of all cases of dementia are of the Alzheimer type [2]. The project “Blood Biomarker-based Diagnostic Tools for Early Stage Alzheimer’s Disease (BBDiag, H2020-EU.1.3.1.-MSCA-ITN-ETN-2016)” identifies and tests blood biomarkers in patients with mild cognitive impairment due to Alzheimer´s disease and develops ICT solutions to manage blood, neuropsychological, and lifestyle markers. Including patients, caregivers, and medical personnel in designing applications for their use [3] is integral in ensuring usability and acceptance of the developed programs [4]. Semi-structured interviews with all stakeholders were conducted using questions to gather qualitative and quantitative data concerning the attitudes of the intended users. For analysis of the qualitative data we used qualitative content analysis according to Mayring [5]. Quantitative data is used to summarize stakeholders’ attitudes. Caregivers and medical staff indicated an interest in mobile applications to support a healthy lifestyle, while patients were more sceptical of the new technology.
References
1. Hibbeler B (2015) Demenz: Weltweit fast zehn Millionen Neuerkrankungen. Arztebl (Deutsches Ärzteblatt)(112(37)): A-1470 / B-1239 / C-1211
2. World Health Organisation (2019) Dementia. https://www.who.int/news-room/fact-sheets/detail/dementia. Accessed 30 Aug 2019
3. Astell A, Alm N, Gowans G et al. (2009) Involving older people with dementia and their carers in designing computer based support systems: some methodological considerations. Univ Access Inf Soc 8(1): 49–58.
4. Garavand A, Samadbeik M, Kafashi M et al. (2017) Acceptance of Health Information Technologies, Acceptance of Mobile Health: A Review Article. J Biomed Phys Eng 7(4): 403–408
5. Mayring P (2015) Qualitative Inhaltsanalyse: Grundlagen und Techniken, 12., überarb. Aufl. Beltz Pädagogik. Beltz, Weinheim
Speech analysis technology for early screening and monitoring of cognition in clinical trials
Nicklas Linz, Kaiserslautern (Germany)
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Nicklas Linz, Kaiserslautern (Germany)
Currently, procedures for onboarding and monitoring participants in clinical dementia trials are rather lengthy, costly, invasive and characterized by high failure rates. Moreover, patients living in rural areas rarely enroll in trials due to the limited access to assessments at clinical sites. Today, there is an increasing need for harmonization and innovation of outcome measures in dementia trials; ecologically valid and sensitive methods are required to improve accessibility as frontline screening in the general population for clinical trials as well as remote disease tracking.
Hinging on recent advances in automatic speech analysis and computational linguistics, the European EIT health project „DeepSpa“ aims to explore the use of telecommunication based systems (phone, tablet & videoconferencing) empowered by artificial intelligence (AI) to facilitate remote large scale population based pre-screening and monitoring of potential trial participants.
For this, the already existing speech processing engine and interfaces have been adapted and are tested in two different sites (Netherlands/France) with observational studies (N=180) assessing feasibility and usability of such phone and telecommunication-based neurocognitive assessment. It consists of a short interview on how the particpants perceive their memory and overall mental state, a verbal (visual) memory task, executive function and fluency tasks. The predictive potential of information extracted from the participant’s speech during cognitive and narrative tasks are examined. Longitudinal and cross sectional data is collected and results extracted remotely validated against face-to-face (F2F) results. Moreover, the degree to which participants experience the phone/teleconference system-based as satisfactory as a F2F assessment will be evaluated with the help of qualitative interview at the end of the study.
Automated sensor-based detection of challenging behaviors in advanced stages of dementia in nursing homes
Doreen Görß, Rostock (Germany)
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Doreen Görß, Rostock (Germany)
The majority of persons with dementia (PwD) exhibit challenging behaviors during the course of their disease. Formal assessment instruments such as IdA® are available to assess the cause and triggers for challenging behaviors. With the project insideDEM we aimed to develop a computerized system of the IdA-tool to facilitate it`s application for non-professional caregivers. Smart algorithms for pre-selection of relevant questions as well as automatically generated, sensor-based information on behaviors of dementia patients in the background of the application were designed to improve the performance of the system.
The insideDEM project was conducted by a consortium of academic and industry partners between 2015 and 2018. For the development of algorithms for automated detection of behaviors based on accelerometric data, we set up a field study with 17 persons in advanced stages of dementia living in two different nursing homes. In parallel to the 24h/7d-sensor mounting over 4 weeks, behavior of all patients was observed over the same period during daytime from expert observers to obtain the ground truth.
We found it feasible to conduct a complex, multidimensional data-recording field study in the setting of nursing homes. Accelerometric data is associated with certain types of challenging behaviors and correlates with established scores (CMAI). We were not able to detect single instances of certain types of behaviors. Still, accelerometric data provides added value in predicting types of behavioral disturbances.
The development of intelligent assistive technologies in context of dementia care is challenging. Besides technological challenges, project management can be tricky due to the variety of involved experts and the need for constructive communication. Inclusion of versatile know-how from experts and prospective users bares high potential for innovative ideas and solutions. We claim that field studies like insideDEM are useful to derive real world evidence.
Digital assistive systems for dementia detection and care – a societal perspective
Themis Exarchos, Korfu (Greece)
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Themis Exarchos, Korfu (Greece)
Biomarkers are measurable and evaluable indicators of changeable signatures of biological conditions. They have the potential to predict disease initiation and progression. Classic biological techniques allow molecular profiling of certain individuals with extreme resolution, but biomarkers based on these technologies lack the ability to follow the dynamic progression of a disease or response to therapy. In contrast, digital biomarkers offer a new approach to biomarker discovery and design. Being able to integrate a large amount of data, digital biomarkers can be used to decipher disease prediction under a holistic framework with high sensitivity and specificity. Digital biomarkers can capture multidimensional features and offer a powerful tool in the armory of precision medicine. In the case of Alzheimer, digital biomarkers under current scrutiny include hand micromovements & micro-errors, gait micro-errors, posture changes, eye tracking, eye pupil dilation, dual task micro-errors and visuospatial navigation micro-errors. Such systems can gather more than 200 features generated from data recorded with high sampling frequency (up to 100Hz). This presentation aims to give insights into the advantages and challenges of current methods for digital biomarker detection, towards the prediction and early diagnosis of Alzheimer’s disease.