Motif discovery in speech: application to monitoring Alzheimer’s disease

Abstract

Background: Perseveration – repetition of words, phrases or questions in speech – is commonly described in Alzheimer’s disease (AD). Measuring perseveration is difficult, but may index cognitive performance, aiding diagnosis and disease monitoring. Continuous recording of speech would produce a large quantity of data requiring painstaking manual analysis, and risk violating patients’ and others’ privacy. A secure record and an automated approach to analysis are required.

Objectives: To record bone-conducted acoustic energy fluctuations from a subject’s vocal apparatus using an accelerometer, to describe the recording and analysis stages in detail, and demonstrate that the approach is feasible in AD.

Methods: Speech-related vibration was captured by an accelerometer, affixed above the temporo-mandibular joint. Healthy subjects read a script with embedded repetitions. Features were extracted from recorded signals and combined using Principal Component Analysis to obtain a one-dimensional representation of the feature vector. Motif discovery techniques were used to detect repeated segments. The equipment was tested in AD patients to determine device acceptability and recording quality.

Results: Comparison with the known location of embedded motifs suggests that, with appropriate parameter tuning, the motif discovery method can detect repetitions. The device was acceptable to patients and produced adequate signal quality in their home environments.

Conclusions: We established that continuously recording bone-conducted speech and detecting perseverative patterns were both possible. In future studies we plan to associate the frequency of verbal repetitions with stage, progression and type of dementia. It is possible that the method could contribute to the assessment of disease-modifying treatments.

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Identifiers

ORCID for Dragana Nikolic: orcid.org/0000-0002-9925-4814

ORCID for Anna Barney: orcid.org/0000-0002-6034-1478

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