BasketHAR is a publicly released multimodal dataset of professional basketball training activities captured with inertial sensors, physiological signals, and video, accompanied by a baseline alignment method.
URL https://www.sciencedirect.com/science/ article/pii/S1877050917312899
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Sonata is a small hybrid world model pre-trained to predict future IMU states that outperforms autoregressive baselines on clinical discrimination, fall-risk prediction, and cross-cohort transfer while fitting on-device wearables.
Gated-CNN applies independent 1D convolutions and sigmoid gating to IMU streams from smartwatches, achieving 90-93% F1 on five datasets and 97% F1 with zero missed falls in real-time Pixel Watch testing, outperforming Transformer baselines.
citing papers explorer
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BasketHAR: A Multimodal Dataset for Human Activity Recognition and Sport Analysis in Basketball Training Scenarios
BasketHAR is a publicly released multimodal dataset of professional basketball training activities captured with inertial sensors, physiological signals, and video, accompanied by a baseline alignment method.
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Sonata: A Hybrid World Model for Inertial Kinematics under Clinical Data Scarcity
Sonata is a small hybrid world model pre-trained to predict future IMU states that outperforms autoregressive baselines on clinical discrimination, fall-risk prediction, and cross-cohort transfer while fitting on-device wearables.
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You Don't Need Attention: Gated Convolutional Modeling for Watch-Based Fall Detection
Gated-CNN applies independent 1D convolutions and sigmoid gating to IMU streams from smartwatches, achieving 90-93% F1 on five datasets and 97% F1 with zero missed falls in real-time Pixel Watch testing, outperforming Transformer baselines.