2018
DOI: 10.2174/1567205014666170829111942
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Use of Speech Analyses within a Mobile Application for the Assessment of Cognitive Impairment in Elderly People

Abstract: Our results indicate the potential value of vocal analytics and the use of a mobile application for accurate automatic differentiation between SCI, MCI and AD. This tool can provide the clinician with meaningful information for assessment and monitoring of people with MCI and AD based on a non-invasive, simple and low-cost method.

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Cited by 98 publications
(101 citation statements)
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“…Automated analysis of speech, in particular speech that is produced during a standard clinical assessment, might be a prime candidate for such a tool [9-14]. Several research groups demonstrated the interest of adopting an automated approach to speech analysis for clinical assessment of older people [15-19]. Overall, reported work either uses speech from conversations, spontaneous speech tasks, reading or repetition tasks, and fluency tasks.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Automated analysis of speech, in particular speech that is produced during a standard clinical assessment, might be a prime candidate for such a tool [9-14]. Several research groups demonstrated the interest of adopting an automated approach to speech analysis for clinical assessment of older people [15-19]. Overall, reported work either uses speech from conversations, spontaneous speech tasks, reading or repetition tasks, and fluency tasks.…”
Section: Introductionmentioning
confidence: 99%
“…annotating turns, or trimming the audio file, in order to prepare it for further computational learning which is not useful for an application in daily clinical practice. Moreover, in order to detect in speech early subtle changes of cognition, it seems crucial to induce a minimum of cognitive effort in a vocal task [15, 20]. …”
Section: Introductionmentioning
confidence: 99%
“…Similar results were found in [12], where acoustic features extracted from speech recordings provided high accuracy rates in classifying healthy versus AD (87%), MCI versus AD (80%), and healthy versus MCI (79%). Even higher classification accuracies were found in a subsequent work of the same group, in which speech analysis was performed on a mobile application, but still in a controlled environment [13].…”
Section: Introductionmentioning
confidence: 75%
“…In a parallel study, the same research group (König et al, 2017) introduced a technology for speech analyses for the assessment of cognitive impairment in older adults. They recorded 165 participants with subjective cognitive impairment (SCI), MCI, AD and mixed dementia with a mobile application while they performed a range of verbal tasks, including verbal fluency.…”
Section: Verbal Fluency Tasksmentioning
confidence: 99%