To investigate the potential of automated speech analysis as a proxy for cognitive assessment in older adults, addressing the need for accessible screening tools.
Key Findings:
Speech analysis significantly improves cognitive assessment accuracy, enhancing early detection.
Automated speech analysis can serve as a low-cost, non-intrusive digital biomarker for cognitive decline.
The method is applicable for large-scale screening and clinical trial participant selection, potentially transforming cognitive health monitoring.
Interpretation:
The findings support the feasibility of using speech analysis for cognitive monitoring, potentially transforming early detection and intervention strategies for cognitive decline.
Limitations:
Voice recordings are considered personally identifiable information, limiting data sharing and replication.
The dataset cannot be fully deposited in public repositories, which may hinder further research.
Conclusion:
Automated speech analysis presents a promising avenue for cognitive assessment, warranting further research and validation.
