ArticleFrontiers in public health2025
Study on the path of combining music and digital health technology to promote the health of older adult groups.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Objective: As the global population ages, non-pharmacological interventions such as personalized music therapy show promise for wellbeing in older adults. We propose the Fusion-Attentive Temporal Network (FAT-Net). This dual-stream model processes minute level heart-rate and music on/off data alongside daily summary features to predict a composite health score. Methods: Data from 92 participants over 45 ± 10 days were augmented fourfold using jittering, time-warping, magnitude scaling, and SMOTE. The temporal stream uses Conv1D, BiLSTM, and self-attention pooling. The summary stream uses a three-layer MLP. Cross-modal attention fuses both embeddings. Results: Over ten runs, FAT-Net achieved RMSE = 0.35 ± 0.005 (22.7% reduction vs. Random Forest), MAE = 0.28 ± 0.005 (19.5% reduction), and Conclusion: FAT-Net's attention-based fusion provides a robust, interpretable approach for forecasting daily wellbeing in older adults.
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