Actigraphy-based detection of isolated REM sleep behavior disorder: multicenter validation across devices and populations

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The study validates actigraphy as a scalable method for detecting isolated REM sleep behavior disorder (iRBD) across multiple devices and populations.
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High-resolution wrist actigraphy achieved an AUC of 0.916 for identifying iRBD, while lower resolution devices showed AUCs of 0.838–0.865.
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The study involved 352 iRBD and 258 non-RBD participants from four centers, enhancing the generalizability of the findings.
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Combining actigraphy with synucleinopathy prodromes improved screening sensitivity and specificity for iRBD detection.
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The results indicate that actigraphy-based detection models can effectively generalize across different cohorts and devices, facilitating early diagnosis.

Npj Digital Medicine

by Li Zhou, Andreas Brink-Kjaer, Katarina Gunter, Salonee Marwaha, Ambra Stefani, Birgit Högl, Michele T. Hu, Emmanuel Mignot, Ankit Parekh, Qi Tang, Merve Aktan-Süzgün, Bei Huang, Shi Tang, Siyi Gong, Yuhua Yang, Xie Chen, Jianzhang Ni, Ningning Li, Zhixuan He, Yun Kwok Wing, Emmanuel During
October 29, 2025

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