دورية أكاديمية
Pulse2AI: An Adaptive Framework to Standardize and Process Pulsatile Wearable Sensor Data for Clinical Applications
| العنوان: | Pulse2AI: An Adaptive Framework to Standardize and Process Pulsatile Wearable Sensor Data for Clinical Applications |
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| المؤلفون: | Sicong Huang, Roozbeh Jafari, Bobak J. Mortazavi |
| المصدر: | IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 330-338 (2024) |
| بيانات النشر: | IEEE, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Medical technology |
| مصطلحات موضوعية: | IoMT, ML for Healthcare, Bridge2AI, wearable pulsatile signals, signal processing, Computer applications to medicine. Medical informatics, R858-859.7, Medical technology, R855-855.5 |
| الوصف: | Goal: To establish Pulse2AI as a reproducible data preprocessing framework for pulsatile signals that generate high-quality machine-learning-ready datasets from raw wearable recordings. Methods: We proposed an end-to-end data preprocessing framework that adapts multiple pulsatile signal modalities and generates machine-learning-ready datasets agnostic to downstream medical tasks. Results: a dataset preprocessed by Pulse2AI improved systolic blood pressure estimation by 29.58%, from 11.41 to 8.03 mmHg in root-mean-square-error (RMSE) and its diastolic counterpart by 26.01%, from 7.93 to 5.87 mmHg in RMSE. For respiration rate (RR) estimation, Pulse2AI boosted performance by 19.69%, from 1.47 to 1.18 breaths per minute (BrPM) in mean-absolute-error (MAE). Conclusion: Pulse2AI turns pulsatile signals into machine learning (ML) ready datasets for arbitrary remote health monitoring tasks. We tested Pulse2AI on multiple pulsatile modalities and demonstrated its efficacy in two medical applications. This work bridges valuable assets in remote sensing and internet of medical things to ML-ready datasets for medical modeling. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2644-1276 |
| Relation: | https://ieeexplore.ieee.org/document/10522883/; https://doaj.org/toc/2644-1276 |
| DOI: | 10.1109/OJEMB.2024.3398444 |
| URL الوصول: | https://doaj.org/article/83ae2e3e5af44f9fa8560b1b7ad09656 |
| رقم الأكسشن: | edsdoj.83ae2e3e5af44f9fa8560b1b7ad09656 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 26441276 |
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| DOI: | 10.1109/OJEMB.2024.3398444 |