Natural speech as a digital biomarker in preclinical Alzheimer’s disease: Usability of a remote burst speech assessment

Abstract

AbstractBackgroundSpeech is a complex process, relying on multiple interacting cognitive functions. Fine‐grained speech analysis offers the potential for measuring subtle cognitive deficits in early‐stage Alzheimer’s disease (AD). As such, digital recordings of natural speech are a promising digital biomarker, particularly when measured in bursts (repeated short measurements). This pilot study focused on the usability of remote speech bursts to assess natural speech in cognitively normal (CN) adults with and without AD pathologic change. Additionally, the association between amyloid‐beta (Aβ)‐pathology and speech characteristics was examined.MethodWe included 49 CN older adults from AMYPAD‐PNHS(location VUmc), SCIENCe, and Amsterdam Dementia Cohort (Age mean(M) = 68±standard deviation(SD) = 6, n = 28(57%) female, n = 23(47%) Aβ‐positive, Table 1). Aβ‐status was based on local cut‐offs for Aβ1‐42‐concentrations in cerebrospinal‐fluid or visual inspection of amyloid positron emission tomography (PET)‐imaging. The remote burst assessment comprised seventeen tablet‐based a)picture description, b)journal‐prompt storytelling and c)verbal‐fluency subtasks, administered over five consecutive days in an unsupervised home‐setting. Daily administration time was approximately 10 minutes. To assess usability, participants completed the system usability scale (SUS). Various acoustic features, including silent pauses, pause‐to‐word‐ratio and mean intensity (i.e., perceived loudness), were extracted from the voice recordings, and mean burst scores were calculated over the five‐day period. The association between Aβ‐status and acoustic features was investigated using two‐sample t‐tests stratified by subtask.ResultsThe 49 participants rated usability with a mean SUS‐score of 86(SD = 10). For example, 46(94%) participants thought the assessment‐app was easy to use (Figure 1). Ratings were lower in Aβ‐positive (M = 83±10) than Aβ‐negative individuals (M = 88±9, p = 0.02), reflecting good and excellent usability respectively. Regarding the association between Aβ‐status and acoustic features, more silent pauses were observed for Aβ‐positive (M = 0.30±0.09) compared to Aβ‐negative individuals (M = 0.25±0.06, p = 0.025, Figure 2) in the storytelling subtask. No group differences for pause‐to‐word‐ratio or mean intensity were observed (p>0.05).ConclusionRemote burst assessment of speech is feasible in CN Aβ‐positive and Aβ‐negative adults. Additionally, preliminary results demonstrated that Aβ‐pathology was related to more silent pauses, indicating its potential as a digital AD biomarker. These findings support remote burst speech assessments in monitoring cognitive changes, for example in observational studies and decentralized clinical trials of preclinical AD.