Exploiting Longitudinal Speech Sessions via Voice Assistant Systems for Early Detection of Cognitive Decline

TL;DR

This study demonstrates that longitudinal speech data collected via voice assistants over 18 months can significantly improve early detection of mild cognitive impairment and predict cognitive decline more accurately than single-time assessments.

Contribution

The paper introduces a novel longitudinal approach using voice assistant systems to collect multi-session speech data for early MCI detection and cognitive change prediction.

Findings

Incorporating historical data improves MCI detection F1-score by over 12%.

Speech-based methods achieve up to 75.1% F1-score in MCI detection.

Cognitive change prediction reaches an F1-score of 73.7%.

Abstract

Mild Cognitive Impairment (MCI) is an early stage of Alzheimer's disease (AD), a form of neurodegenerative disorder. Early identification of MCI is crucial for delaying its progression through timely interventions. Existing research has demonstrated the feasibility of detecting MCI using speech collected from clinical interviews or digital devices. However, these approaches typically analyze data collected at limited time points, limiting their ability to identify cognitive changes over time. This paper presents a longitudinal study using voice assistant systems (VAS) to remotely collect seven-session speech data at three-month intervals across 18 months. We propose two methods to improve MCI detection and the prediction of cognitive changes. The first method incorporates historical data, while the second predicts cognitive changes at two time points. Our results indicate improvements when incorporating historical data: the average F1-score for MCI detection improves from 58.6% to 71.2% (by 12.6%) in the case of acoustic features and from 62.1% to 75.1% (by 13.0%) in the case of linguistic features. Additionally, the prediction of cognitive changes achieves an F1-score of 73.7% in the case of acoustic features. These results confirm the potential of VAS-based speech sessions for early detection of cognitive decline.