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

Motif discovery in speech: application to monitoring Alzheimer’s disease
Motif discovery in speech: application to monitoring Alzheimer’s disease
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.
Alzheimer’s disease, perseveration, bone-conducted speech, motif discovery, principal component analysis
1567-2050
951-959
Barney, Anna
bc0ee7f7-517a-4154-ab7d-57270de3e815
Nikolic, Dragana
772b3eb2-c994-440a-ab86-27e862bd39f7
Garrard, Peter
9016944f-8766-4df5-83bc-5fda650bd22e
Nemes, Vanda
193101ef-8b74-4bab-9830-2f07957f5029
Barney, Anna
bc0ee7f7-517a-4154-ab7d-57270de3e815
Nikolic, Dragana
772b3eb2-c994-440a-ab86-27e862bd39f7
Garrard, Peter
9016944f-8766-4df5-83bc-5fda650bd22e
Nemes, Vanda
193101ef-8b74-4bab-9830-2f07957f5029

Barney, Anna, Nikolic, Dragana, Garrard, Peter and Nemes, Vanda (2017) Motif discovery in speech: application to monitoring Alzheimer’s disease. Current Alzheimer Research, 14 (9), 951-959. (doi:10.2174/1567205014666170309121025).

Record type: Article

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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More information

Accepted/In Press date: 5 August 2016
e-pub ahead of print date: 31 August 2017
Published date: 1 September 2017
Keywords: Alzheimer’s disease, perseveration, bone-conducted speech, motif discovery, principal component analysis
Organisations: Signal Processing & Control Grp

Identifiers

Local EPrints ID: 399602
URI: https://eprints.soton.ac.uk/id/eprint/399602
ISSN: 1567-2050
PURE UUID: 78d12e59-befc-4121-91e4-c8560ad3882b
ORCID for Anna Barney: ORCID iD orcid.org/0000-0002-6034-1478

Catalogue record

Date deposited: 22 Aug 2016 10:11
Last modified: 14 Nov 2018 05:01

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