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Cited by in F6Publishing
For: Shieh WY, Wang CM, Cheng HK, Wang CH. Using Wearable and Non-Invasive Sensors to Measure Swallowing Function: Detection, Verification, and Clinical Application. Sensors (Basel) 2019;19:E2624. [PMID: 31181864 DOI: 10.3390/s19112624] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Lee M, Lin G, Hoe Z, Pan C. Development of Piezoelectric Silk Sensors Doped with Graphene for Biosensing by Near-Field Electrospinning. Sensors 2022;22:9131. [DOI: 10.3390/s22239131] [Reference Citation Analysis]
2 Törmä S, Ihalainen T, Palovuori K, Sipilä E, Virkki J. Recognizing swallowing movements using a textile-based device. Textile Research Journal. [DOI: 10.1177/00405175221115470] [Reference Citation Analysis]
3 Costa BOID, Dantas AMX, Machado LDS, Silva HJD, Pernambuco L, Lopes LW. O uso de tecnologias vestíveis para análise e monitoramento de funções relacionadas à alimentação e comunicação. CoDAS 2022;34. [DOI: 10.1590/2317-1782/20212021278pt] [Reference Citation Analysis]
4 Costa BOID, Dantas AMX, Machado LDS, Silva HJD, Pernambuco L, Lopes LW. Wearable technology use for the analysis and monitoring of functions related to feeding and communication. CoDAS 2022;34. [DOI: 10.1590/2317-1782/20212021278en] [Reference Citation Analysis]
5 Polat B, Becerra LL, Hsu P, Kaipu V, Mercier PP, Cheng C, Lipomi DJ. Epidermal Graphene Sensors and Machine Learning for Estimating Swallowed Volume. ACS Appl Nano Mater 2021;4:8126-34. [DOI: 10.1021/acsanm.1c01378] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
6 Shieh WY, Wang CM, Cheng HK, Imbang TI. Noninvasive Measurement of Tongue Pressure and Its Correlation with Swallowing and Respiration. Sensors (Basel) 2021;21:2603. [PMID: 33917263 DOI: 10.3390/s21082603] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
7 Lee JT, Park E, Jung TD. Automatic Detection of the Pharyngeal Phase in Raw Videos for the Videofluoroscopic Swallowing Study Using Efficient Data Collection and 3D Convolutional Networks . Sensors (Basel) 2019;19:E3873. [PMID: 31500332 DOI: 10.3390/s19183873] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 3.7] [Reference Citation Analysis]