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 temporomandibular
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.
Conclusion: 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.