Imperial College London (Davies et al.)
GPT-style decoder-only Transformer pretrained via next-token prediction on tokenized single-lead ECG time series, producing an interpretable general-purpose model that can be fine-tuned for tasks like arrhythmia screening and beat detection. Individual attention heads are shown to respond to physiologically meaningful features such as the P-wave, and token embeddings cluster by position in the cardiac cycle. A companion PPG-pretrained model (PPG-PT) is released in the same repository. Developed at Imperial College London.
Architecture
Transformer
GPT-style decoder-only transformer pretrained via next-token prediction on tokenized single-lead ECG time series
Framework
PyTorch
Added to catalog
2026-07-10
MIT
License for model weights only. Associated code may be licensed seperately, check code source for specific terms.
Imperial College HeartGPT single-lead ECG pretraining corpus
Large-scale tokenized single-lead ECG corpus used for next-token pretraining; constituent source datasets are not fully disclosed in the publication or repository.
Autoregressively generated continuation of a tokenized single-lead ECG time series (also usable as a general-purpose pretrained representation)