Couplet Object Detection Dataset and Pre-Trained Model by UNM

Images

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Explore Dataset

Here are a few use cases for this project:

Healthcare Monitoring: Use Couplet to monitor patients' heart rhythms in real-time, detecting normal, couplet, or premature atrial contractions (PAC), helping healthcare professionals to quickly identify and address potential cardiac issues.
Wearable Health Tech: Integrate Couplet into wearable health technology devices such as smartwatches and fitness trackers to track users' heart rates and rhythm abnormalities, sending notifications of potential irregularities and prompting users to seek medical attention if necessary.
Telemedicine: Implement Couplet into telemedicine platforms as an additional diagnostic tool for remote health consultations. This could allow doctors to accurately assess patients' heart conditions through video calls, providing more accessible and efficient healthcare services to those in remote locations or with mobility issues.
Connected ECG Devices: Employ Couplet to enhance the analysis capabilities of connected ECG machines in hospitals, clinics, and healthcare facilities. The AI-driven computer vision model can automatically detect and classify heartbeats, improving both speed and accuracy of the diagnosis process.
Medical Research and Education: Utilize Couplet in academic and research settings to better understand the prevalence and manifestations of various types of arrhythmias in the population. The model can assist in analyzing large volumes of ECG data and automate the process of identifying heartbeat patterns, contributing to a deeper understanding of cardiovascular health issues.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            couplet-szrey_dataset,
                            title = { Couplet Dataset },
                            type = { Open Source Dataset },
                            author = { UNM },
                            howpublished = { \url{ https://universe.roboflow.com/unm-h474m/couplet-szrey } },
                            url = { https://universe.roboflow.com/unm-h474m/couplet-szrey },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { dec },
                            note = { visited on 2024-05-22 },
                            }