Frontiers in neurology · 2026
Interpretable polar-flow decomposition for torsional nystagmus lateralization in posterior-canal BPPV.
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Li Yanjun, Xu Xiaomin, Gao Lidan, Shao Qiqi, Chen Jie, Wang Wenhuan, Li Xiaoqing, Sun Congcong, Hou Shike, Yang Xiaokai
Аннотация
OBJECTIVE: Torsional nystagmus during the Dix-Hallpike maneuver represents a cardinal vestibulo-ocular reflex (VOR) sign in posterior-canal benign paroxysmal positional vertigo (pc-BPPV). This study develops an interpretable framework for automated classification of torsional nystagmus direction and temporal localization of abnormal events from clinical infrared recordings.
METHODS: Infrared Dix-Hallpike videos were processed via You Only Look Once version 8 nano (YOLOv8n) pupil localization, dynamic iris masking, and Recurrent All-Pairs Field Transforms (RAFT) optical flow. Flow vectors were projected into pupil-centered polar coordinates to extract tangential and radial motion features. A bidirectional gated recurrent unit with attention (BiGRU-attention) network performed segment-level three-class classification with sliding-window patient-level inference.
RESULTS: Five-fold cross-validation yielded segment-level accuracy of 94.19% ± 0.88% with balanced F1-scores across all three classes. On an independent 45-patient long-video test set, patient-level accuracy reached 97.78% at 60 frames per second (fps) and 100% (45/45) at 30 fps. Temporal localization achieved mean intersection-over-union (IoU) of 0.899 and 0.896, with hit rates of 96.8 and 100%, respectively.
CONCLUSION: The polar-flow framework enables physiologically interpretable and robust classification of pc-BPPV-related torsional-upbeat nystagmus. By explicitly decomposing eye movements into tangential and radial components, it provides reliable lateralization while demonstrating the potential for clinically meaningful temporal localization of abnormal nystagmus events.
METHODS: Infrared Dix-Hallpike videos were processed via You Only Look Once version 8 nano (YOLOv8n) pupil localization, dynamic iris masking, and Recurrent All-Pairs Field Transforms (RAFT) optical flow. Flow vectors were projected into pupil-centered polar coordinates to extract tangential and radial motion features. A bidirectional gated recurrent unit with attention (BiGRU-attention) network performed segment-level three-class classification with sliding-window patient-level inference.
RESULTS: Five-fold cross-validation yielded segment-level accuracy of 94.19% ± 0.88% with balanced F1-scores across all three classes. On an independent 45-patient long-video test set, patient-level accuracy reached 97.78% at 60 frames per second (fps) and 100% (45/45) at 30 fps. Temporal localization achieved mean intersection-over-union (IoU) of 0.899 and 0.896, with hit rates of 96.8 and 100%, respectively.
CONCLUSION: The polar-flow framework enables physiologically interpretable and robust classification of pc-BPPV-related torsional-upbeat nystagmus. By explicitly decomposing eye movements into tangential and radial components, it provides reliable lateralization while demonstrating the potential for clinically meaningful temporal localization of abnormal nystagmus events.