journal article·2024-10-25

Wearable Pressure Sensor Based on the Melamine Formaldehyde Resin Sponge with Graphene/MWCNTs/PDMS for Medical Assisting of Patients with Amyotrophic Lateral Sclerosis

Xiaohui Guo, Jiangtao Hu, Qiang Long, Tianxu Zhang, Zhuoyang Li, Fei Wu, Xiaowen Zhu, Congguang He, Yinuo Chen, Shenxin Zhu, Hua Ru, Yanbo He, Lianyue Zhang, Jiashun Wu, Weiqiang Hong, Qi Hong, Yaohua Xu, Yunong Zhao

ACS Applied Nano Materials· Volume 7· Issue 20
Publisher page

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal degenerative disease of the central nervous system characterized by progressive muscle weakness over time and space. Assessing the severity of a patient’s condition and establishing effective communication strategies postloss of speech are vital for providing optimal care to ALS patients. In this article, a capacitive pressure sensor based on the melamine formaldehyde resin sponge (MFRS) and graphene/MWCNTs/PDMS mixture is proposed. The MFRS pressure sensor (MFRSPS) boasts good sensitivity (0.22 kPa –1 ), wide range (0–500 kPa), rapid response/relaxation time (45 ms/45 ms), and low detection limit (7 Pa). Additionally, it exhibits robust temperature resistance and repeatability (600 cycles under various pressures). Leveraging the impressive performance of the MFRSPS, two distinct systems have been designed for ALS patients: the medical assistive system and the Morse code representation system. The medical assistive system aids in diagnosing the disease, while the Morse code representation system facilitates the patient’s communication with the outside world. This work provides an effective method for accessing the condition of ALS patients, supporting their rehabilitation and enabling their communication with the external environment.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Neuroscience and Neural Engineering

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Integrated Circuits, Anhui University, Hefei 230601, PR China

East China Optoelectronic Integrated Device Research Institute, Bengbu 233000, PR China

State Key Laboratory of High-Performance Precision Manufacturing, Dalian University of Technology, Dalian 116024, PR China

Key Laboratory for Micro/Nano Technology and System of Liaoning Province, Dalian University of Technology, Dalian 116024, PR China

Funding

National Natural Science Foundation of China · Central Government Will Guide Local Special Funds for Scientific and Technological Development · University Synergy Innovation Program of Anhui Province · Anhui Provincial Natural Science Foundation

References (52)

Show source-provided references
1. 10.1038/s41467-023-40917-310.1038/s41467-023-40917-3 ↗
2. 10.1080/21678421.2022.211986910.1080/21678421.2022.2119869 ↗
3. 10.1016/S0140-6736(22)01272-710.1016/S0140-6736(22)01272-7 ↗
4. 10.1016/j.neurol.2021.03.00110.1016/j.neurol.2021.03.001 ↗
5. 10.1002/adma.20240732910.1002/adma.202407329 ↗
6. 10.1007/s40820-023-01176-510.1007/s40820-023-01176-5 ↗
7. 10.1038/s41378-024-00680-x10.1038/s41378-024-00680-x ↗
8. 10.1021/acsanm.4c0028610.1021/acsanm.4c00286 ↗
9. 10.1021/acsanm.4c0306010.1021/acsanm.4c03060 ↗
10. 10.1021/acsanm.4c0263110.1021/acsanm.4c02631 ↗
11. 10.1021/acsanm.4c0165410.1021/acsanm.4c01654 ↗
12. 10.1021/acsanm.2c0224210.1021/acsanm.2c02242 ↗
13. 10.1016/j.carbpol.2023.12098310.1016/j.carbpol.2023.120983 ↗
14. 10.1007/s12274-022-5084-x10.1007/s12274-022-5084-x ↗
15. 10.1007/s12274-023-5537-x10.1007/s12274-023-5537-x ↗
16. 10.1016/j.sna.2019.07.00410.1016/j.sna.2019.07.004 ↗
17. 10.1016/j.carbpol.2023.12125010.1016/j.carbpol.2023.121250 ↗
18. 10.1002/smll.20230154410.1002/smll.202301544 ↗
19. 10.20517/ss.2022.2610.20517/ss.2022.26 ↗
20. 10.1038/s41928-023-01091-y10.1038/s41928-023-01091-y ↗
21. 10.1016/j.jmst.2023.06.04710.1016/j.jmst.2023.06.047 ↗
22. 10.1016/j.compositesa.2022.10724010.1016/j.compositesa.2022.107240 ↗
23. 10.1021/acsnano.4c0906210.1021/acsnano.4c09062 ↗
24. 10.1007/s42765-023-00324-110.1007/s42765-023-00324-1 ↗
25. 10.1021/acsami.3c0809310.1021/acsami.3c08093 ↗
26. 10.29026/oea.2023.22017210.29026/oea.2023.220172 ↗
27. 10.1016/j.cej.2023.14507510.1016/j.cej.2023.145075 ↗
28. 10.1002/admt.20230056110.1002/admt.202300561 ↗
29. 10.1016/j.mtchem.2023.10169610.1016/j.mtchem.2023.101696 ↗
30. 10.1007/s42765-023-00350-z10.1007/s42765-023-00350-z ↗
31. 10.1016/j.jcis.2024.09.07510.1016/j.jcis.2024.09.075 ↗
32. 10.1021/acsami.9b1651110.1021/acsami.9b16511 ↗
33. 10.1002/smll.20220304410.1002/smll.202203044 ↗
34. 10.1016/j.compscitech.2022.10983710.1016/j.compscitech.2022.109837 ↗
35. 10.1002/adma.20230407010.1002/adma.202304070 ↗
36. 10.1016/j.cej.2023.14553210.1016/j.cej.2023.145532 ↗
37. 10.1016/j.apsusc.2023.15802110.1016/j.apsusc.2023.158021 ↗
38. 10.1021/acssuschemeng.2c0737010.1021/acssuschemeng.2c07370 ↗
39. 10.1007/s42114-022-00581-510.1007/s42114-022-00581-5 ↗
40. 10.1016/j.cej.2020.12441510.1016/j.cej.2020.124415 ↗
41. 10.1021/acsami.7b0611910.1021/acsami.7b06119 ↗
42. 10.1002/smll.20170036810.1002/smll.201700368 ↗
43. 10.1002/adma.20150140810.1002/adma.201501408 ↗
44. 10.1021/acsami.1c1682810.1021/acsami.1c16828 ↗
45. 10.1016/j.compositesa.2021.10667110.1016/j.compositesa.2021.106671 ↗
46. 10.1021/acsami.0c2139210.1021/acsami.0c21392 ↗
47. 10.1039/D2RA06487A10.1039/D2RA06487A ↗
48. 10.1016/j.compositesa.2022.10717110.1016/j.compositesa.2022.107171 ↗
49. 10.1039/D1NR05017F10.1039/D1NR05017F ↗
50. 10.1002/mame.20210025110.1002/mame.202100251 ↗
51. 10.1039/D1TB01467F10.1039/D1TB01467F ↗
52. 10.1021/acsami.2c1673010.1021/acsami.2c16730 ↗