From the article: "Individuals with dementia often experience a decline in their ability to use language. Language problems have been reported in individuals with dementia caused by Alzheimer’s disease, Parkinson’s disease or degeneration of the fronto-temporal area. Acoustic properties are relatively easy to measure with software, which promises a cost-effective way to analyze larger discourses. We study the usefulness of acoustic features to distinguish the speech of German-speaking controls and patients with dementia caused by (a) Alzheimer’s disease, (b) Parkinson’s disease or (c) PPA/FTD. Previous studies have shown that each of these types affects speech parameters such as prosody, voice quality and fluency (Schulz 2002; Ma, Whitehill, and Cheung 2010; Rusz et al. 2016; Kato et al. 2013; Peintner et al. 2008). Prior work on the characteristics of the speech of individuals with dementia is usually based on samples from clinical tests, such as the Western Aphasia Battery or the Wechsler Logical Memory task. Spontaneous day-to-day speech may be different, because participants may show less of their vocal abilities in casual speech than in specifically designed test scenarios. It is unclear to what extent the previously reported speech characteristics are still detectable in casual conversations by software. The research question in this study is: how useful for classification are acoustic properties measured in spontaneous speech."
MULTIFILE
The design of healthcare facilities is a complex and dynamic process, which involves many stakeholders each with their own set of needs. In the context of healthcare facilities, this complexity exists at the intersection of technology and society because the very design of these buildings forces us to consider the technology–human interface directly in terms of living-space, ethics and social priorities. In order to grasp this complexity, current healthcare design models need mechanisms to help prioritize the needs of the stakeholders. Assistance in this process can be derived by incorporating elements of technology philosophy into existing design models. In this article, we develop and examine the Inclusive and Integrated Health Facilities Design model (In2Health Design model) and its foundations. This model brings together three existing approaches: (i) the International Classification of Functioning, Disability and Health, (ii) the Model of Integrated Building Design, and (iii) the ontology by Dooyeweerd. The model can be used to analyze the needs of the various stakeholders, in relationship to the required performances of a building as delivered by various building systems. The applicability of the In2Health Design model is illustrated by two case studies concerning (i) the evaluation of the indoor environment for older people with dementia and (ii) the design process of the redevelopment of an existing hospital for psychiatric patients.
Analysis of spontaneous speech is an important tool for clinical linguists to diagnose various types of neurodegenerative disease that affect the language processing areas. Prosody, fluency and voice quality may be affected in individuals with Parkinson's disease (PD, degradation of voice quality, unstable pitch), Alzheimer's disease (AD, monotonic pitch), and the non-fluent type of Primary Progressive Aphasia (PPA-NF, hesitant, non-fluent speech). In this study, the performance of a SVM classifier is evaluated that is trained on acoustic features only. The goal is to distinguish different types of brain damage based on recorded speech. Results show that the classifier can distinguish some dementia types (PPA-NF, AD), but not others (PD).
