{"oa_version":"Published Version","_id":"20707","file":[{"date_updated":"2025-12-01T07:19:06Z","access_level":"open_access","file_size":3045062,"checksum":"f793472a71d27012244567b499a4967f","date_created":"2025-12-01T07:19:06Z","file_name":"2025_ICMI_Gahtan.pdf","creator":"dernst","content_type":"application/pdf","file_id":"20713","relation":"main_file","success":1}],"doi":"10.1145/3716553.3750815","ddc":["000"],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png"},"OA_place":"publisher","date_updated":"2025-12-01T07:22:09Z","year":"2025","publication_identifier":{"isbn":["9798400714993"]},"citation":{"apa":"Gahtan, B., Vedula, S., Samuelly Leichtag, G., Kodesh, E., &#38; Bronstein, A. M. (2025). From lab to wrist: Bridging metabolic monitoring and consumer wearables for heart rate and oxygen consumption modeling. In <i>Proceedings of the 27th International Conference on Multimodal Interaction</i> (pp. 60–77). Canberra, Australia: Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3716553.3750815\">https://doi.org/10.1145/3716553.3750815</a>","mla":"Gahtan, Barak, et al. “From Lab to Wrist: Bridging Metabolic Monitoring and Consumer Wearables for Heart Rate and Oxygen Consumption Modeling.” <i>Proceedings of the 27th International Conference on Multimodal Interaction</i>, Association for Computing Machinery, 2025, pp. 60–77, doi:<a href=\"https://doi.org/10.1145/3716553.3750815\">10.1145/3716553.3750815</a>.","short":"B. Gahtan, S. Vedula, G. Samuelly Leichtag, E. Kodesh, A.M. Bronstein, in:, Proceedings of the 27th International Conference on Multimodal Interaction, Association for Computing Machinery, 2025, pp. 60–77.","ista":"Gahtan B, Vedula S, Samuelly Leichtag G, Kodesh E, Bronstein AM. 2025. From lab to wrist: Bridging metabolic monitoring and consumer wearables for heart rate and oxygen consumption modeling. Proceedings of the 27th International Conference on Multimodal Interaction. ICMI: International Conference on Multimodal Interaction, 60–77.","ieee":"B. Gahtan, S. Vedula, G. Samuelly Leichtag, E. Kodesh, and A. M. Bronstein, “From lab to wrist: Bridging metabolic monitoring and consumer wearables for heart rate and oxygen consumption modeling,” in <i>Proceedings of the 27th International Conference on Multimodal Interaction</i>, Canberra, Australia, 2025, pp. 60–77.","chicago":"Gahtan, Barak, Sanketh Vedula, Gil Samuelly Leichtag, Einat Kodesh, and Alex M. Bronstein. “From Lab to Wrist: Bridging Metabolic Monitoring and Consumer Wearables for Heart Rate and Oxygen Consumption Modeling.” In <i>Proceedings of the 27th International Conference on Multimodal Interaction</i>, 60–77. Association for Computing Machinery, 2025. <a href=\"https://doi.org/10.1145/3716553.3750815\">https://doi.org/10.1145/3716553.3750815</a>.","ama":"Gahtan B, Vedula S, Samuelly Leichtag G, Kodesh E, Bronstein AM. From lab to wrist: Bridging metabolic monitoring and consumer wearables for heart rate and oxygen consumption modeling. In: <i>Proceedings of the 27th International Conference on Multimodal Interaction</i>. Association for Computing Machinery; 2025:60-77. doi:<a href=\"https://doi.org/10.1145/3716553.3750815\">10.1145/3716553.3750815</a>"},"article_processing_charge":"No","external_id":{"arxiv":["2505.00101"]},"OA_type":"hybrid","language":[{"iso":"eng"}],"date_created":"2025-11-30T23:02:08Z","department":[{"_id":"AlBr"}],"scopus_import":"1","corr_author":"1","author":[{"full_name":"Gahtan, Barak","last_name":"Gahtan","first_name":"Barak"},{"full_name":"Vedula, Sanketh","last_name":"Vedula","first_name":"Sanketh"},{"last_name":"Samuelly Leichtag","first_name":"Gil","full_name":"Samuelly Leichtag, Gil"},{"full_name":"Kodesh, Einat","last_name":"Kodesh","first_name":"Einat"},{"first_name":"Alexander","last_name":"Bronstein","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","orcid":"0000-0001-9699-8730"}],"oa":1,"status":"public","publisher":"Association for Computing Machinery","page":"60-77","quality_controlled":"1","day":"12","title":"From lab to wrist: Bridging metabolic monitoring and consumer wearables for heart rate and oxygen consumption modeling","month":"10","file_date_updated":"2025-12-01T07:19:06Z","date_published":"2025-10-12T00:00:00Z","arxiv":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","has_accepted_license":"1","type":"conference","conference":{"name":"ICMI: International Conference on Multimodal Interaction","start_date":"2025-10-13","end_date":"2025-10-17","location":"Canberra, Australia"},"abstract":[{"text":"Understanding physiological responses during running is critical for performance optimization, tailored training prescriptions, and athlete health management. We introduce a comprehensive framework—what we believe to be the first capable of predicting instantaneous oxygen consumption (VO2) trajectories exclusively from consumer-grade wearable data. Our approach employs two complementary physiological models: (1) accurate modeling of heart rate (HR) dynamics via a physiologically constrained ordinary differential equation (ODE) and neural Kalman filter, trained on over 3 million HR observations, achieving 1-second interval predictions with mean absolute errors as low as 2.81 bpm (correlation 0.87); and (2) leveraging the principles of precise HR modeling, a novel VO2 prediction architecture requiring only the initial second of VO2 data for calibration, enabling robust, sequence-to-sequence metabolic demand estimation. Despite relying solely on smartwatch and chest-strap data, our method achieves mean absolute percentage errors of approximately 13%, effectively capturing rapid physiological transitions and steady-state conditions across diverse running intensities. Our synchronized dataset, complemented by blood lactate measurements, further lays the foundation for future noninvasive metabolic zone identification. By embedding physiological constraints within modern machine learning, this framework democratizes advanced metabolic monitoring, bridging laboratory-grade accuracy and everyday accessibility, thus empowering both elite athletes and recreational fitness enthusiasts.","lang":"eng"}],"publication":"Proceedings of the 27th International Conference on Multimodal Interaction","publication_status":"published"}