Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96979
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dc.contributorSchool of Fashion and Textilesen_US
dc.contributorCollege of Professional and Continuing Educationen_US
dc.contributorResearch Institute for Intelligent Wearable Systemsen_US
dc.creatorWang, Fen_US
dc.creatorZhu, Ben_US
dc.creatorShu, Len_US
dc.creatorLi, Yen_US
dc.creatorLai, Xen_US
dc.creatorMa, Len_US
dc.creatorJi, Pen_US
dc.creatorZhou, Qen_US
dc.creatorYu, Ten_US
dc.creatorTao, Xen_US
dc.date.accessioned2023-01-09T07:28:35Z-
dc.date.available2023-01-09T07:28:35Z-
dc.identifier.urihttp://hdl.handle.net/10397/96979-
dc.language.isoenen_US
dc.publisherWiley-VCH Verlag GmbH & Co. KGaAen_US
dc.rights© 2022 The Authors. Advanced Sensor Research published by Wiley-VCH GmbHen_US
dc.rightsThis is the peer reviewed version of the following article: Wang, F., Zhu, B., Shu, L., Li, Y., Lai, X., Ma, L., Ji, P., Zhou, Q., Yu, T. and Tao, X. (2023), Smart Clothing with Built-In Soft Sensing Network for Measuring Temporal and Spatial Distribution of Pressure under Impact Scenarios. Adv. Sensor Res., 2: 2200019, which has been published in final form at https://doi.org/10.1002/adsr.202200019. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.en_US
dc.subjectCrash dummiesen_US
dc.subjectImpact testsen_US
dc.subjectIn situ measurementen_US
dc.subjectPressure sensorsen_US
dc.subjectSmart clothingen_US
dc.subjectStrain rateen_US
dc.titleSmart clothing with built-in soft sensing network for measuring temporal and spatial distribution of pressure under impact scenariosen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume2en_US
dc.identifier.issue2en_US
dc.identifier.doi10.1002/adsr.202200019en_US
dcterms.abstractNowadays, the need for protective devices at man–machine interfaces is increasing in the fields of traffic, sports, construction, and military, etc. Dynamic pressure sensing technology with wide measuring range, high sensitivity, softness, and fast response is crucial for evaluation and optimization of the personal protective equipment under impact scenarios. However, current sensors hardly possess all the aforesaid required characteristics. For the first time, this article reports the evaluation and application of an innovative soft pressure sensor with modulus of 2 MPa, maximum pressure of 8 MPa, and over 500-Hz frequency. A theoretical model, taking strain rate into consideration, is established to characterize the dynamic sensing behavior. A sensing network in the form of smart clothing is developed and used in a sled crash test, which is a standard approach to evaluate the safety of automobiles in collisions. The pressure distribution over the dummy's surface during the crash is acquired in real-time, and compared with numerical simulations. This work is important to the study of occupant injury and crashworthiness design for vehicles, and it will benefit the automotive industry. With the built-in sensing network, the smart clothing has promising applications in the pressure mapping of 3D flexible man–machine interface under impact scenarios.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAdvanced sensor research, Feb. 2023, v. 2, no. 2, 2200019en_US
dcterms.isPartOfAdvanced sensor researchen_US
dcterms.issued2023-02-
dc.identifier.eissn2751-1219en_US
dc.identifier.artn2200019en_US
dc.description.validate202301 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera1881-n05-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe Innovation and Technology Fund of Innovation and Technology Commission, Hong Kong SAR; The Endowed Professorship Scheme of The Hong Kong Polytechnic University; The Hong Kong Research Institute of Textiles and Apparel Limited; Shenzhen NanHua Electronic Technology Corporation Ltd.; Joint Sensor Instruments (Hong Kong) Ltd.; TAL Apparel Ltd.; Postgraduate scholarship from The Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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