Speech changes in old age: Methodological considerations for speech-based discrimination of healthy ageing and Alzheimer's disease.

BACKGROUND: Recent evidence suggests that speech substantially changes in ageing. As a complex neurophysiological process, it can accurately reflect changes in the motor and cognitive systems underpinning human speech. Since healthy ageing is not always easily discriminable from early stages of dementia based on cognitive and behavioural hallmarks, speech is explored as a preclinical biomarker of pathological itineraries in old age. A greater and more specific impairment of neuromuscular activation, as well as  a specific cognitive and linguistic impairment in dementia, unchain discriminating changes in speech. Yet, there is no consensus on such discriminatory speech parameters, neither on how they should be elicited and assessed. AIMS: To provide a state-of-the-art on speech parameters that allow for early discrimination between healthy and pathological ageing; the aetiology of these parameters; the effect of the type of experimental stimuli on speech elicitation and the predictive power of different speech parameters; and the most promising methods for speech analysis and their clinical implications. METHODS & PROCEDURES: A scoping review methodology is used in accordance with the PRISMA model. Following a systematic search of PubMed, PsycINFO and CINAHL, 24 studies are included and analysed in the review. MAIN CONTRIBUTION: The results of this review yield three key questions for the clinical assessment of speech in ageing. First, acoustic and temporal parameters are more sensitive to changes in pathological ageing and, of these two, temporal variables are more affected by cognitive impairment. Second, different types of stimuli can trigger speech parameters with different degree of accuracy for the discrimination of clinical groups. Tasks with higher cognitive load are more precise in eliciting higher levels of accuracy. Finally, automatic speech analysis for the discrimination of healthy and pathological ageing should be improved for both research and clinical practice. CONCLUSIONS & IMPLICATIONS: Speech analysis is a promising non-invasive tool for the preclinical screening of healthy and pathological ageing. The main current challenges of speech analysis in ageing are the automatization of its clinical assessment and the consideration of the speaker's cognitive background during evaluation. WHAT THIS PAPER ADDS: What is already known on the subject Societal aging  goes hand in hand with the rising incidence of ageing-related neurodegenerations, mainly Alzheimer's disease (AD). This is particularly noteworthy in countries with longer life expectancies. Healthy ageing and early stages of AD share a set of cognitive and behavioural characteristics. Since there is no cure for dementias, developing methods for accurate discrimination of healthy ageing and early AD is currently a priority. Speech has been described as one of the most significantly impaired features in AD. Neuropathological alterations in motor and cognitive systems would underlie specific speech impairment in dementia. Since speech can be evaluated quickly, non-invasively and inexpensively, its value for the clinical assessment of ageing itineraries may be particularly high. What this paper adds to existing knowledge Theoretical and experimental advances in the assessment of speech as a marker of AD have developed rapidly over the last decade. Yet, they are not always known to clinicians. Furthermore, there is a need to provide an updated state-of-the-art on which speech features are discriminatory to AD, how they can be assessed, what kind of results they can yield, and how such results should be interpreted. This article provides an updated overview of speech profiling, methods of speech measurement and analysis, and the clinical power of speech assessment for early discrimination of AD as the most common cause of dementia. What are the potential or actual clinical implications of this work? This article provides an overview of the predictive potential of different speech parameters in relation to AD cognitive impairment. In addition, it discusses the effect that the cognitive state, the type of elicitation task and the type of assessment method may have on the results of the speech-based analysis in ageing.

Reading and lexical-semantic retrieval tasks outperforms single task speech analysis in the screening of mild cognitive impairment and Alzheimer's disease.

Age-related cognitive impairment have increased dramatically in recent years, which has risen the interes in developing screening tools for mild cognitive impairment and Alzheimer's disease. Speech analysis allows to exploit the behavioral consequences of cognitive deficits on the patient's vocal performance so that it is possible to identify pathologies affecting speech production such as dementia. Previous studies have further shown that the speech task used determines how the speech parameters are altered. We aim to combine the impairments in several speech production tasks in order to improve the accuracy of screening through speech analysis. The sample consists of 72 participants divided into three equal groups of healthy older adults, people with mild cognitive impairment, or Alzheimer's disease, matched by age and education. A complete neuropsychological assessment and two voice recordings were performed. The tasks required the participants to read a text, and complete a sentence with semantic information. A stepwise linear discriminant analysis was performed to select speech parameters with discriminative power. The discriminative functions obtained an accuracy of 83.3% in simultaneous classifications of several levels of cognitive impairment. It would therefore be a promising screening tool for dementia.

Many Changes in Speech through Aging Are Actually a Consequence of Cognitive Changes.

BACKGROUND: During aging, changes in human speech may arise because of the neurophysiological deterioration associated with age, or as the result of an impairment in the cognitive processes underlying speech production. Some speech parameters show specific alterations under the presence of dementia. The objective of our study is to identify which of these parameters change because of age, cognitive state, or the interaction of both. METHODS: The sample includes 400 people over 55 years old, who were divided into four groups, according to their age. The cognitive state of the participants was assessed through the MMSE test and three ranks were stablished. Gender was also considered in the analysis. RESULTS: Certain temporal, fluency, rhythm, amplitude and voice quality parameters were found to be related to the cognitive state, while disturbance parameters changed due to age. Frequency parameters were exclusively influenced by gender. CONCLUSIONS: Understanding how speech parameters are specifically affected by age, cognitive state, or the interaction of both, is determinant to advance in the use of speech as a clinical marker for the detection of cognitive impairments.

Speech biomarkers of risk factors for vascular dementia in people with mild cognitive impairment.

Introduction: In this study we intend to use speech analysis to analyze the cognitive impairments caused by pathologies of vascular origin such as diabetes, hypertension, hypercholesterolemia and heart disease, predictors of the development of vascular dementia. Methods: In this study, 40 participants with mild cognitive impairment were asked to read while being recorded and they were inquired about their history of the aforementioned conditions. Their speech was then analyzed. Results: We found that some speech parameters of frequencies and syllabic rhythm vary due to these pathologies. In addition, we conducted a discriminant analysis in which we found that diabetes and hypertension can be predicted with an accuracy over 95% with few speech parameters, and hypercholesterolemia and heart disease with an accuracy over 80%. Discussion: The predictor parameters found are heterogeneous, including voice quality, amplitude, frequency, and rhythm parameters. This result may lead to investigate why such important qualitative changes occur in the voice of older adults with these pathologies. Rather than trying to find a diagnostic procedure already existing in classical medicine, we expect this finding to contribute to explore the causes and concomitant pathologies of these diseases. We discuss the implications of behavioral traits, such as speech, as digital biomarkers.

Ten Years of Research on Automatic Voice and Speech Analysis of People With Alzheimer's Disease and Mild Cognitive Impairment: A Systematic Review Article.

Background: The field of voice and speech analysis has become increasingly popular over the last 10 years, and articles on its use in detecting neurodegenerative diseases have proliferated. Many studies have identified characteristic speech features that can be used to draw an accurate distinction between healthy aging among older people and those with mild cognitive impairment and Alzheimer's disease. Speech analysis has been singled out as a cost-effective and reliable method for detecting the presence of both conditions. In this research, a systematic review was conducted to determine these features and their diagnostic accuracy. Methods: Peer-reviewed literature was located across multiple databases, involving studies that apply new procedures of automatic speech analysis to collect behavioral evidence of linguistic impairments along with their diagnostic accuracy on Alzheimer's disease and mild cognitive impairment. The risk of bias was assessed by using JBI and QUADAS-2 checklists. Results: Thirty-five papers met the inclusion criteria; of these, 11 were descriptive studies that either identified voice features or explored their cognitive correlates, and the rest were diagnostic studies. Overall, the studies were of good quality and presented solid evidence of the usefulness of this technique. The distinctive acoustic and rhythmic features found are gathered. Most studies record a diagnostic accuracy over 88% for Alzheimer's and 80% for mild cognitive impairment. Conclusion: Automatic speech analysis is a promising tool for diagnosing mild cognitive impairment and Alzheimer's disease. The reported features seem to be indicators of the cognitive changes in older people. The specific features and the cognitive changes involved could be the subject of further research.

[Development of a subjective quality of life scale in nursing homes for older people (CVS-R).] / Desarrollo de una escala de calidad de vida subjetiva en residencias de personas mayores (CVS-R).

OBJECTIVE: The quality of life in nursing homes is a growing concern. Its assessment requires instruments that consider the subjective needs of residents, their families, and staff, such as the questionnaire (CVS-R) that has been developed and validated in the present study. METHODS: The original 100 items version was applied to 99 participants from three nursing homes (36,4% professionals, 30,30% residents and 33,33% family members). From the item analysis, a questionnaire with 27 questions and 9 dimensions was obtained, which, subsequently, 225 people from other nursing homes in Spain filled in online. Content validity was analyzed by expert judgment, and construct validity by factor analysis. Reliability was assessed by analyzing the internal consistency with Cronbach's alpha. RESULTS: The factorial analysis confirmed the existence of a single factor that explains 62.35% of the total variance of the questionnaire. Cronbach's alpha was 0.97. No relationship was found between sex and the final score of the questionnaire. CONCLUSIONS: The psychometric properties of the CVS-R support its use for the assessment of the subjective quality of life of nursing homes in Spain. The CVS-R considers, for the first time, the perception of residents, families and staff.

OBJETIVO: La calidad de vida en residencias de personas mayores es una preocupación creciente. Su evaluación requiere instrumentos que consideren las necesidades subjetivas de residentes, familias y profesionales, como el cuestionario (CVS-R) que se desarrolló y validó en el presente estudio. METODOS: La versión original de 100 ítems fue aplicada a 99 personas procedentes de tres residencias (36,4% profesionales, 30,30% residentes y 33,33% familiares). Del análisis de los ítems se obtuvo un cuestionario de 27 preguntas y 9 dimensiones que, posteriormente, rellenaron de forma online 225 personas de otras residencias de España (62% profesionales, 23% residentes y 14% familiares). Se analizó la validez de contenido mediante valoración por expertos y la validez de constructo mediante análisis factorial. Se evaluó la fiabilidad analizando la consistencia interna con el alfa de Cronbach. RESULTADOS: El análisis factorial confirmó la existencia de un solo factor que explica el 62,35% de la varianza total del cuestionario. El alfa de Cronbach fue de 0,97. No se encontró relación entre el sexo y la puntuación final del cuestionario. CONCLUSIONES: Las propiedades psicométricas del CVS-R apoyan su uso para la evaluación de la CV subjetiva de residencias de personas mayores de España. El CVS-R recoge, por primera vez, la percepción de residentes, familias y profesionales.

Changes in the Rhythm of Speech Difference between People with Nondegenerative Mild Cognitive Impairment and with Preclinical Dementia.

This study explores several speech parameters related to mild cognitive impairment, as well as those that might be flagging the presence of an underlying neurodegenerative process. Speech is an excellent biomarker because it is not invasive and, what is more, its analysis is rapid and economical. Our aim has been to ascertain whether the typical speech patterns of people with Alzheimer's disease are also present during the disorder's preclinical stages. To do so, we shall be using a task that involves reading out aloud. This is followed by an analysis of the recordings, looking for the possible parameters differentiating between those older people with MCI and a high probability of developing dementia and those with MCI that will not do so. We found that the disease's most differentiating parameters prior to its onset involve changes in speech duration and an alteration in rhythm rate and intensity. These parameters seem to be related to the first difficulties in lexical access among older people with AD.