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For: Altini M, Casale P, Penders J, Amft O. Cardiorespiratory fitness estimation in free-living using wearable sensors. Artif Intell Med 2016;68:37-46. [PMID: 26948954 DOI: 10.1016/j.artmed.2016.02.002] [Cited by in Crossref: 15] [Cited by in F6Publishing: 7] [Article Influence: 2.5] [Reference Citation Analysis]
Number Citing Articles
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2 Naseri Jahfari A, Tax D, Reinders M, van der Bilt I. Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View. JMIR Med Inform 2022;10:e29434. [PMID: 35044316 DOI: 10.2196/29434] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Yang HI, Cho W, Lee DH, Suh SH, Jeon JY. Development of a New Submaximal Walk Test to Predict Maximal Oxygen Consumption in Healthy Adults. Sensors (Basel) 2021;21:5726. [PMID: 34502615 DOI: 10.3390/s21175726] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 De Cannière H, Corradi F, Smeets CJP, Schoutteten M, Varon C, Van Hoof C, Van Huffel S, Groenendaal W, Vandervoort P. Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation. Sensors (Basel) 2020;20:E3601. [PMID: 32604829 DOI: 10.3390/s20123601] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
5 Szczegielniak J, Latawiec KJ, Łuniewski J, Stanisławski R, Bogacz K, Krajczy M, Rydel M. A study on nonlinear estimation of submaximal effort tolerance based on the generalized MET concept and the 6MWT in pulmonary rehabilitation. PLoS One 2018;13:e0191875. [PMID: 29425213 DOI: 10.1371/journal.pone.0191875] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 1.3] [Reference Citation Analysis]
6 Derungs A, Schuster-Amft C, Amft O. Longitudinal Walking Analysis in Hemiparetic Patients Using Wearable Motion Sensors: Is There Convergence Between Body Sides? Front Bioeng Biotechnol 2018;6:57. [PMID: 29904628 DOI: 10.3389/fbioe.2018.00057] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
7 Nag N, Pandey V, Putzel PJ, Bhimaraju H, Krishnan S, Jain R. Cross-Modal Health State Estimation. Proc ACM Int Conf Multimed 2018;2018:1993-2002. [PMID: 31131378 DOI: 10.1145/3240508.3241913] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 2.3] [Reference Citation Analysis]
8 Kwon SB, Ahn JW, Lee SM, Lee J, Lee D, Hong J, Kim HC, Yoon HJ. Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study. JMIR Mhealth Uhealth 2019;7:e13327. [PMID: 31199336 DOI: 10.2196/13327] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 2.3] [Reference Citation Analysis]