Linguists from the Department of English, Linguistics and Theatre Studies (ELTS) at the NUS Faculty of Arts and Social Sciences (FASS) led a study and discovered that early signs of dementia can be identified by analyzing the natural speech of elderly Singaporeans. The study showed that participants with mild cognitive impairment related to memory spoke less and used fewer, but more abstract, nouns, which is similar to the speech pattern of those with Alzheimer’s disease.
Researchers at the NUS Yong Loo Lin School of Medicine conducted a study comparing the speech of healthy individuals to those with mild cognitive impairment (MCI) in order to identify linguistic markers of dementia. The results showed that those with MCI spoke less and used fewer, but more abstract, nouns, which is a speech pattern consistent with patients diagnosed with Alzheimer’s disease. The principal investigator of the study, NUS Department of ELTS Professor Bao Zhimin, stated that this research is a groundbreaking step in understanding the speech patterns of senior Singaporeans.
g, pointed out that Singapore’s diverse linguistic landscape makes it an ideal setting for this research, with its four official languages and mix of dialects. He also mentioned that previous studies have mainly looked at small samples of language data using word-based fluency tests, structured interviews, and picture narrations. This study is unique because it focuses on unstructured and spontaneous speech, which is easier to gather and analyze.”
Another team member, Yeo Boon Khim from the Mind Science Centre (YBK MSC) and NUS Medicine’s Emeritus Professor Kua Ee Heok, a psychiatrist, emphasized the urgent need for this research.Looking for new ways to address the increasing occurrence of dementia in Singapore due to our aging population. The study used data from the YBK MSC project’s Community Health Intergenerational (CHI) Study, led by Dr Rathi Mahendran. The goal is to use the findings to help identify seniors at risk and implement interventions to support healthy aging. The study was released in the journal Alzheimer’s & Dementia: Diagnosis, Assessment and Disease Monitoring on April 18th. Compiling and analyzing natural spe
The research team collected speech data from 148 elderly individuals in their 60s and 70s in Singapore. Half of the participants were cognitively healthy, meaning they had the ability to think clearly, learn, and remember information. The other half of the participants had Mild Cognitive Impairment (MCI).
Out of the 74 participants with MCI, 38 were diagnosed with amnestic MCI, which specifically affects memory, while 36 were diagnosed with non-amnestic MCI, which affects thinking skills other than memory. Amnestic MCI is associated with a higher risk of developing Alzheimer’s disease, while non-amnestic MCI is linked to a higher risk of other dementias.
converted the transcriptions into a format that was suitable for analysis using natural language processing techniques. The data was then analyzed for linguistic features such as syntactic complexity, lexical diversity, and fluency. The results showed that individuals with MCI displayed lower syntactic complexity and lexical diversity compared to their healthy counterparts. This suggests that changes in language production may be an early indicator of cognitive decline in MCI. The findings of this study could have important implications for early detection and intervention for dementia.The word counts and concreteness scores of all labeled words were calculated per minute. “Early signs of dementia detected in people with amnestic MCI.” The study found that individuals with amnestic MCI spoke less and used fewer and more abstract nouns compared to those with non-amnestic MCI and healthy controls. Verbs were not impacted. A problem with imageability, which measures a word’s ability to evoke a mental image, was observed in the natural everyday speech of individuals with amnestic MCI. Dr. Luwen Cao, also from the NUS Department of ELTS, stated, “Our findings are a significant breakthrough as trad”Additional evaluations for dementia are typically conducted through a series of neuropsychological and neurological tests. Analyzing natural speech for linguistic indicators of early cognitive decline is a reliable, non-invasive, and cost-effective method that could potentially assist healthcare professionals in the early detection, treatment, and handling of the progressive disease. Going forward, the team intends to collaborate with neurologists at the YBK MSC to develop language-focused intervention techniques to address the language challenges faced by individuals with amnestic Mild Cognitive Impairment. Professor Bao stated, “Ultimately, our research aims to contribute to the improvement of health.”Healthy aging in Singapore is a growing concern due to the rapid increase in the number of older adults. With a quarter of the population being over 60 years old, it is essential to find new ways to diagnose and intervene in age-related health issues. By using innovative tools and strategies, we aim to enhance the quality of life for older individuals and alleviate the strain on healthcare systems. Our efforts are a crucial step in ensuring that the aging population can live longer and healthier lives.
