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Cited by in F6Publishing
For: Asci F, Vivacqua G, Zampogna A, D'Onofrio V, Mazzeo A, Suppa A. Wearable Electrochemical Sensors in Parkinson's Disease. Sensors (Basel) 2022;22:951. [PMID: 35161694 DOI: 10.3390/s22030951] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Macdonald AR, Charlton F, Corrigan DK. Accelerating the development of implantable neurochemical biosensors by using existing clinically applied depth electrodes. Anal Bioanal Chem 2022. [DOI: 10.1007/s00216-022-04445-1] [Reference Citation Analysis]
2 Khaliq F, Oberhauser J, Wakhloo D, Mahajani S. Decoding degeneration: the implementation of machine learning for clinical detection of neurodegenerative disorders. Neural Regen Res 2023;18:1235-42. [PMID: 36453399 DOI: 10.4103/1673-5374.355982] [Reference Citation Analysis]
3 Parati M, Gallotta M, Muletti M, Pirola A, Bellafà A, De Maria B, Ferrante S. Validation of Pressure-Sensing Insoles in Patients with Parkinson’s Disease during Overground Walking in Single and Cognitive Dual-Task Conditions. Sensors 2022;22:6392. [DOI: 10.3390/s22176392] [Reference Citation Analysis]
4 O'sullivan S, Murray N, Rodrigues TB. A telehealth and sensor-based system for user-centered physical therapy in Parkinson's disease. Proceedings of the 13th ACM Multimedia Systems Conference 2022. [DOI: 10.1145/3524273.3535781] [Reference Citation Analysis]