Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricos
Este estudio aborda el diseño, fabricación y evaluación de un dispositivo wearable (Tribosense) basado en nanogeneradores triboeléctricos (TENG) para medir niveles de presión en las yemas de los dedos y ángulos de flexión en la articulación PIP de la mano humana adulta. El proyecto comprende cuatro...
- Autores:
-
Ramirez Cepeda, Yaisa Catalina
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2025
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/75343
- Acceso en línea:
- https://hdl.handle.net/1992/75343
- Palabra clave:
- Dispositivo wearable
Flexión
Interfaz
PTFE
Sensor TENG
Silicona
Tacto
Ingeniería
- Rights
- openAccess
- License
- Attribution-NonCommercial 4.0 International
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Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricos |
| title |
Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricos |
| spellingShingle |
Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricos Dispositivo wearable Flexión Interfaz PTFE Sensor TENG Silicona Tacto Ingeniería |
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Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricos |
| title_full |
Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricos |
| title_fullStr |
Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricos |
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Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricos |
| title_sort |
Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricos |
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Ramirez Cepeda, Yaisa Catalina |
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Ávila Bernal, Alba Graciela |
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Ramirez Cepeda, Yaisa Catalina |
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Segura Quijano, Fredy Enrique |
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Dispositivo wearable |
| topic |
Dispositivo wearable Flexión Interfaz PTFE Sensor TENG Silicona Tacto Ingeniería |
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Flexión Interfaz PTFE Sensor TENG Silicona Tacto |
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Ingeniería |
| description |
Este estudio aborda el diseño, fabricación y evaluación de un dispositivo wearable (Tribosense) basado en nanogeneradores triboeléctricos (TENG) para medir niveles de presión en las yemas de los dedos y ángulos de flexión en la articulación PIP de la mano humana adulta. El proyecto comprende cuatro etapas clave: sensado, acondicionamiento, procesamiento y visualización en una interfaz móvil. En estas fases se demostró la viabilidad de sensores de bajo costo (menos de 0,5 USD), para detectar fuerzas entre 0 y 5 N, así como ángulos de flexión de 0° a 90°. Entre las configuraciones evaluadas, la combinación de silicona-PTFE destacó con variaciones de voltaje de hasta 1,4 V. Los sensores se integraron en un circuito de acondicionamiento montado en una PCB portátil ubicada en la muñeca del usuario. La información capturada se visualizó en una interfaz móvil con un desfase inferior a 0.5s, mostrando tanto las salidas de voltaje como su interpretación en estados de presión y flexión. Se identificaron oportunidades de mejora, particularmente en la optimización del diseño del guante para minimizar pérdidas de señal que dificultaron la detección de estados en los sensores de flexión. Los resultados incluyen la detección de estímulos reflejados en la interfaz móvil, lo que demuestra el potencial del dispositivo para aplicaciones en tecnología asistencial e interfaces humano-máquina. |
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Xianjie Pu et al. “Wearable Triboelectric Sensors for Biomedical Monitoring and Human-Machine Interface”. En: iScience 24.1 (2021), pag. 102027. doi:10.1016/j.isci.2020.102027. url: https://doi.org/10.1016/j.isci.2020.102027. Yang Luo et al. “Triboelectric bending sensor based smart glove towards intuitive multi-dimensional human-machine interfaces”. En: NanoEnergy 89 (2021), pag. 106330. issn: 2211-2855. doi: https://doi.org/10.1016/j.nanoen.2021.106330. url: https://www.sciencedirect.com/science/article/pii/S2211285521005851. Manuel Caeiro-Rodr´ıguez et al. “A Systematic Review of Commercial Smart Gloves: Current Status and Applications”. En: Sensors 21.8(2021). issn: 1424-8220. doi: 10.3390/s21082667. url: https://www.mdpi.com/1424-8220/21/8/2667. Ruiyang Yin et al. “Wearable Sensors-Enabled Human–Machine Interaction Systems: From Design to Application”. En: Advanced Functional Materials 31.11 (2021), pag. 2008936. doi: https://doiorg.ezproxy.uniandes.edu.co/10.1002/adfm.202008936. eprint: https://onlinelibrary-wiley-com.ezproxy.uniandes.edu.co/ doi/pdf/10.1002/adfm.202008936. url: https://onlinelibrarywiley-com.ezproxy.uniandes.edu.co/doi/abs/10.1002/adfm.202008936. Nathan W Moon, Paul MA Baker y Kenneth Goughnour. “Designing wearable technologies for users with disabilities: Accessibility, usability, and connectivity factors”. En: Journal of Rehabilitation and Assistive Technologies Engineering 6 (2019). PMID: 35186318, p´ ag. 2055668319862137. doi: 10.1177/2055668319862137. eprint: https://doi.org/10.1177/2055668319862137. url: https://doi.org/10.1177/2055668319862137. Xiong Pu, Chi Zhang y Zhong Lin Wang. “Triboelectric nanogenerators as wearable power sources and self-powered sensors”. En: National Science Review 10.1 (ago. de 2022), nwac170. issn: 2095-5138. doi:4410.1093/nsr/nwac170. eprint: https://academic.oup.com/nsr/article-pdf/10/1/nwac170/48728046/nwac170.pdf. url: https: //doi.org/10.1093/nsr/nwac170. Manuel Caeiro-Rodriguez et al. “A Systematic Review of Commercial Smart Gloves: Current Status and Applications”. En: Sensors 21.8(2021). issn: 1424-8220. doi: 10.3390/s21082667. url: https:// www.mdpi.com/1424-8220/21/8/2667 F. Wen, Z. Zhang, T. He et al. “AI enabled sign language recognition and VR space bidirectional communication using triboelectric smart glove”. En: Nature Communications 12.5378 (2021). doi: 10.1038/ s41467-021-25637-w. url: https://doi.org/10.1038/s41467021-25637-w. Jeong Ho Kim et al. “Differences in typing forces, muscle activity, comfort, and typing performance among virtual, notebook, and desktop keyboards”. En: Applied Ergonomics 45.6 (2014), p´ags. 1406-1413. issn: 0003-6870. doi: https://doi.org/10.1016/j.apergo.2014. 04.001. url: https://www.sciencedirect.com/science/article/pii/S000368701400043X. J. N. Leijnse, P. M. Quesada y C. W. Spoor. “Kinematic evaluation of the finger’s interphalangeal joints coupling mechanism–variability, flexion-extension differences, triggers, locking swanneck deformities, anthropometric correlations”. En: Journal of Biomechanics 43.12 (2010), pags. 2381-2393. doi: 10.1016/j.jbiomech.2010.04.021. url: https://doi.org/10.1016/j.jbiomech.2010.04.021. Deanna S. Asakawa et al. “Fingertip forces and completion time for index finger and thumb touchscreen gestures”. En: Journal of Electromyography and Kinesiology 34 (2017), p´ ags. 6-13. issn: 1050-6411. doi: https://doi.org/10.1016/j.jelekin.2017.02.007. url:https://www.sciencedirect.com/science/article/pii/S1050641116301225. Zhong Lin Wang. “Triboelectric nanogenerators as new energy technology and self-powered sensors– Principles, problems and perspectives”. En: Faraday Discuss. 176 (0 2014), p´ ags. 447-458. doi: 10.1039/ C4FD00159A. url: http://dx.doi.org/10.1039/C4FD00159A. R.L. Bulathsinghala, W. Ding y R.D.I.G. Dharmasena. “Triboelectric nanogenerators for wearable sensing applications: A system level analysis”. En: Nano Energy 116 (2023), p´ ag. 108792. issn: 22112855. doi: https://doi.org/10.1016/j.nanoen.2023.108792. 45url: https://www.sciencedirect.com/science/article/pii/S2211285523006298 Z. Zhang, T. He, M. Zhu et al. “Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications”. En: npj Flexible Electronics 4 (2020), p´ag. 29. doi: 10.1038/s41528-02000092-7. url: https://doi.org/10.1038/s41528-020-00092-7. Gaurav Khandelwal, Nirmal Prashanth Maria Joseph Raj y Sang-Jae Kim. “Materials Beyond Conventional Triboelectric Series for Fabrication and Applications of Triboelectric Nanogenerators”. En: Advanced Energy Materials 11.21 (2021), pag. 2101170. Dong Liu, Linlin Zhou, Shilei Cui et al. “Standardized measurement of dielectric materials’ intrinsic triboelectric charge density through the suppression of air breakdown”. En: Nature Communications 13.6019 (2022). doi: 10.1038/s41467-022-33766-z. Z. L. Wang et al. “Triboelectric nanogenerators: Fundamental physics and potential applications”. En: Energy Environmental Science 5.8 (2012), pags. 9285-9293. doi: 10.1039/c2ee22656e. Yonghai Li et al. “Recent Progress in Self-Powered Wireless Sensors and Systems Based on TENG”. En: Sensors 23.3 (2023), pag. 1329. doi:10.3390/s23031329. url: https://doi.org/10.3390/s23031329. Fifth Dimension Technologies. 5DT Data Glove Ultra. 5DT. [Online]. Available: https://5dt.com/5dt-data-glove-ultra/. [Accessed: 30-May2024]. 2024. Shutang Wang et al. “Stretchable and Wearable Triboelectric Nanogenerator Based on Kinesio Tape for Self-Powered Human Motion Sensing”. En: Nanomaterials 8.9 (2018). issn: 2079-4991. doi: 10.3390/nano8090657. url: https://www.mdpi.com/2079-4991/8/9/657. Haixu Wang et al. “Bioinspired Engineering towards Tailoring Advanced Lignin/Rubber Elastomers”. En: Polymers 10 (sep. de 2018),pag. 1033. doi: 10.3390/polym10091033. Smooth-On. Ecoflex Series Technical Bulletin. https://www.smoothon.com/tb/files/ECOFLEX_SERIES_TB.pdf. Accessed: 2024-11-14. Jinhao Si et al. “Recent Progress Regarding Materials and Structures of Triboelectric Nanogenerators for AR and VR”. En: Nanomaterials 12.8 (2022), p´ ag. 1385. doi: 10.3390/nano12081385. url: https: //doi.org/10.3390/nano12081385. Renyun Zhang y H˚ akan Olin. “Material choices for triboelectric nanogenerators: A critical review”. En: EcoMat 2.4 (2020), e12062. doi: 10.1002/eom2.12062.46 Jung-Hoon Noh. “Frequency-Response Analysis and Design Rules for Capacitive Feedback Transimpedance Amplifier”. En: IEEE Transactions on Instrumentation and Measurement 69.12 (2020), pags. 9408-9416. doi: 10.1109/TIM.2020.3006325. Microchip Technology Inc. MCP6021/2/3/4 Data Sheet: 10 MHz, Low Power Op Amp. Accessed: 2024-11-07. Sep. de 2007. url: https:// ww1.microchip.com/downloads/en/DeviceDoc/20001685E.pdf. Texas Instruments. ADS1113, ADS1114, ADS1115 Ultra-Small, Low Power, 16-Bit Analog-to-Digital Converter with Internal Reference Datasheet. Accessed: Sep. 19, 2024. 2022. url: https://www.ti.com/lit/ds/symlink/ads1115.pdf. Ryan Walden et al. “Textile-Triboelectric nanogenerators (T-TENGs) for wearable energy harvesting devices”. En: Chemical Engineering Journal 451 (2023), pag. 138741. issn: 1385-8947. doi: https:// doi.org/10.1016/j.cej.2022.138741. url: https://www.sciencedirect.com/science/article/pii/S138589472204222X. A. Nawaz, H.W. Choi, N. Sarwar et al. “Characterizing graphite-based pencil material for mechanical energy harvesting and sensing application”. En: Journal of Materials Science: Materials in Electronics 34 (2023), p´ag. 222. doi: 10.1007/s10854-022-09640-5. url: https: //doi.org/10.1007/s10854-022-09640-5. Kai-Hong Ke, Lin Lin y Chen-Kuei Chung. “Low-cost micro-graphite doped polydimethylsiloxane composite film for enhancement of mechanical to-electrical energy conversion with aluminum and its application”. En: Journal of the Taiwan Institute of Chemical Engineers 135 (2022),pag. 104388. issn: 1876-1070. doi: https://doi.org/10.1016/ j.jtice.2022.104388. url: https://www.sciencedirect.com/science/article/pii/S1876107022001857 |
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Ávila Bernal, Alba Gracielavirtual::21963-1Ramirez Cepeda, Yaisa CatalinaSegura Quijano, Fredy Enrique2025-01-10T20:42:57Z2025-01-10T20:42:57Z2025-01-10https://hdl.handle.net/1992/75343instname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/Este estudio aborda el diseño, fabricación y evaluación de un dispositivo wearable (Tribosense) basado en nanogeneradores triboeléctricos (TENG) para medir niveles de presión en las yemas de los dedos y ángulos de flexión en la articulación PIP de la mano humana adulta. El proyecto comprende cuatro etapas clave: sensado, acondicionamiento, procesamiento y visualización en una interfaz móvil. En estas fases se demostró la viabilidad de sensores de bajo costo (menos de 0,5 USD), para detectar fuerzas entre 0 y 5 N, así como ángulos de flexión de 0° a 90°. Entre las configuraciones evaluadas, la combinación de silicona-PTFE destacó con variaciones de voltaje de hasta 1,4 V. Los sensores se integraron en un circuito de acondicionamiento montado en una PCB portátil ubicada en la muñeca del usuario. La información capturada se visualizó en una interfaz móvil con un desfase inferior a 0.5s, mostrando tanto las salidas de voltaje como su interpretación en estados de presión y flexión. Se identificaron oportunidades de mejora, particularmente en la optimización del diseño del guante para minimizar pérdidas de señal que dificultaron la detección de estados en los sensores de flexión. Los resultados incluyen la detección de estímulos reflejados en la interfaz móvil, lo que demuestra el potencial del dispositivo para aplicaciones en tecnología asistencial e interfaces humano-máquina.Pregrado49 páginasapplication/pdfspaUniversidad de los AndesIngeniería ElectrónicaFacultad de IngenieríaDepartamento de Ingeniería Eléctrica y ElectrónicaAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Desarrollo de un dispositivo wearable para la mano con sensores triboeléctricosTrabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_7a1fTexthttp://purl.org/redcol/resource_type/TPDispositivo wearableFlexiónInterfazPTFESensor TENGSiliconaTactoIngenieríaXianjie Pu et al. “Wearable Triboelectric Sensors for Biomedical Monitoring and Human-Machine Interface”. En: iScience 24.1 (2021), pag. 102027. doi:10.1016/j.isci.2020.102027. url: https://doi.org/10.1016/j.isci.2020.102027.Yang Luo et al. “Triboelectric bending sensor based smart glove towards intuitive multi-dimensional human-machine interfaces”. En: NanoEnergy 89 (2021), pag. 106330. issn: 2211-2855. doi: https://doi.org/10.1016/j.nanoen.2021.106330. url: https://www.sciencedirect.com/science/article/pii/S2211285521005851.Manuel Caeiro-Rodr´ıguez et al. “A Systematic Review of Commercial Smart Gloves: Current Status and Applications”. En: Sensors 21.8(2021). issn: 1424-8220. doi: 10.3390/s21082667. url: https://www.mdpi.com/1424-8220/21/8/2667.Ruiyang Yin et al. “Wearable Sensors-Enabled Human–Machine Interaction Systems: From Design to Application”. En: Advanced Functional Materials 31.11 (2021), pag. 2008936. doi: https://doiorg.ezproxy.uniandes.edu.co/10.1002/adfm.202008936. eprint: https://onlinelibrary-wiley-com.ezproxy.uniandes.edu.co/ doi/pdf/10.1002/adfm.202008936. url: https://onlinelibrarywiley-com.ezproxy.uniandes.edu.co/doi/abs/10.1002/adfm.202008936.Nathan W Moon, Paul MA Baker y Kenneth Goughnour. “Designing wearable technologies for users with disabilities: Accessibility, usability, and connectivity factors”. En: Journal of Rehabilitation and Assistive Technologies Engineering 6 (2019). PMID: 35186318, p´ ag. 2055668319862137. doi: 10.1177/2055668319862137. eprint: https://doi.org/10.1177/2055668319862137. url: https://doi.org/10.1177/2055668319862137.Xiong Pu, Chi Zhang y Zhong Lin Wang. “Triboelectric nanogenerators as wearable power sources and self-powered sensors”. En: National Science Review 10.1 (ago. de 2022), nwac170. issn: 2095-5138. doi:4410.1093/nsr/nwac170. eprint: https://academic.oup.com/nsr/article-pdf/10/1/nwac170/48728046/nwac170.pdf. url: https: //doi.org/10.1093/nsr/nwac170.Manuel Caeiro-Rodriguez et al. “A Systematic Review of Commercial Smart Gloves: Current Status and Applications”. En: Sensors 21.8(2021). issn: 1424-8220. doi: 10.3390/s21082667. url: https:// www.mdpi.com/1424-8220/21/8/2667F. Wen, Z. Zhang, T. He et al. “AI enabled sign language recognition and VR space bidirectional communication using triboelectric smart glove”. En: Nature Communications 12.5378 (2021). doi: 10.1038/ s41467-021-25637-w. url: https://doi.org/10.1038/s41467021-25637-w.Jeong Ho Kim et al. “Differences in typing forces, muscle activity, comfort, and typing performance among virtual, notebook, and desktop keyboards”. En: Applied Ergonomics 45.6 (2014), p´ags. 1406-1413. issn: 0003-6870. doi: https://doi.org/10.1016/j.apergo.2014. 04.001. url: https://www.sciencedirect.com/science/article/pii/S000368701400043X.J. N. Leijnse, P. M. Quesada y C. W. Spoor. “Kinematic evaluation of the finger’s interphalangeal joints coupling mechanism–variability, flexion-extension differences, triggers, locking swanneck deformities, anthropometric correlations”. En: Journal of Biomechanics 43.12 (2010), pags. 2381-2393. doi: 10.1016/j.jbiomech.2010.04.021. url: https://doi.org/10.1016/j.jbiomech.2010.04.021.Deanna S. Asakawa et al. “Fingertip forces and completion time for index finger and thumb touchscreen gestures”. En: Journal of Electromyography and Kinesiology 34 (2017), p´ ags. 6-13. issn: 1050-6411. doi: https://doi.org/10.1016/j.jelekin.2017.02.007. url:https://www.sciencedirect.com/science/article/pii/S1050641116301225.Zhong Lin Wang. “Triboelectric nanogenerators as new energy technology and self-powered sensors– Principles, problems and perspectives”. En: Faraday Discuss. 176 (0 2014), p´ ags. 447-458. doi: 10.1039/ C4FD00159A. url: http://dx.doi.org/10.1039/C4FD00159A.R.L. Bulathsinghala, W. Ding y R.D.I.G. Dharmasena. “Triboelectric nanogenerators for wearable sensing applications: A system level analysis”. En: Nano Energy 116 (2023), p´ ag. 108792. issn: 22112855. doi: https://doi.org/10.1016/j.nanoen.2023.108792. 45url: https://www.sciencedirect.com/science/article/pii/S2211285523006298Z. Zhang, T. He, M. Zhu et al. “Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications”. 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