{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T06:22:21Z","timestamp":1763446941436,"version":"3.45.0"},"reference-count":37,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1016\/j.engappai.2025.112802","type":"journal-article","created":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:20:20Z","timestamp":1761265220000},"page":"112802","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P1","title":["A physics-penalized neural network with asynchronous propagation and localization embedding for dynamic plantar pressure prediction in older adults"],"prefix":"10.1016","volume":"163","author":[{"given":"Madhumitha","family":"Sekaran","sequence":"first","affiliation":[]},{"given":"Kamalraj","family":"Subramaniam","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"8","key":"10.1016\/j.engappai.2025.112802_bib1","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1007\/s00158-024-03845-4","article-title":"Multidisciplinary optimization of shoe midsole structures using swarm intelligence","volume":"67","author":"Alam","year":"2024","journal-title":"Struct. Multidiscip. Optim."},{"key":"10.1016\/j.engappai.2025.112802_bib2","series-title":"Computer Methods in Biomechanics and Biomedical Engineering","first-page":"1","article-title":"Machine learning assisted classification between diabetic polyneuropathy and healthy subjects using plantar pressure and temperature data: a feasibility study","author":"Aman","year":"2024"},{"issue":"2","key":"10.1016\/j.engappai.2025.112802_bib3","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1016\/j.bbe.2022.03.001","article-title":"Fourier transform-based data augmentation in deep learning for diabetic foot thermograph classification","volume":"42","author":"Anaya-Isaza","year":"2022","journal-title":"Biocybern. Biomed. Eng."},{"issue":"10","key":"10.1016\/j.engappai.2025.112802_bib4","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1080\/14763141.2020.1743744","article-title":"Plantar pressure modifications in experienced runners following an exhaustive run","volume":"21","author":"Bercovitz","year":"2022","journal-title":"Sports Biomech."},{"issue":"21","key":"10.1016\/j.engappai.2025.112802_bib5","doi-asserted-by":"crossref","first-page":"7059","DOI":"10.3390\/s24217059","article-title":"Wearable technology applications and methods to assess clinical outcomes in foot and ankle disorders: achievements and perspectives","volume":"24","author":"Brognara","year":"2024","journal-title":"Sensors"},{"key":"10.1016\/j.engappai.2025.112802_bib6","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.107187","article-title":"Enhancing plantar pressure distribution reconstruction with conditional generative adversarial networks from multi-region foot pressure sensing","volume":"100","author":"Chan","year":"2025","journal-title":"Biomed. Signal Process Control"},{"issue":"2","key":"10.1016\/j.engappai.2025.112802_bib7","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1007\/s40477-023-00869-2","article-title":"Musculoskeletal disorders in padel: from biomechanics to sonography","volume":"27","author":"Cocco","year":"2024","journal-title":"J. Ultrasound"},{"key":"10.1016\/j.engappai.2025.112802_bib8","first-page":"1","article-title":"Static and dynamic optimisation of fluid-filled responsive orthotic insoles","author":"Cracknell","year":"2025","journal-title":"Biomech. Model. Mechanobiol."},{"year":"2022","series-title":"Pervasive Displays: Understanding the Future of Digital Signage","author":"Davies","key":"10.1016\/j.engappai.2025.112802_bib9"},{"key":"10.1016\/j.engappai.2025.112802_bib10","first-page":"1","article-title":"Application of texture-based features for text non-text classification in printed document images with novel feature selection algorithm","author":"Ghosh","year":"2022","journal-title":"Soft Comput."},{"issue":"3","key":"10.1016\/j.engappai.2025.112802_bib11","doi-asserted-by":"crossref","first-page":"1931","DOI":"10.1109\/JBHI.2024.3512546","article-title":"Estimation of ankle joint moment from plantar pressure through an optimized sensor layout using genetic algorithm and deep forest regression","volume":"29","author":"Gong","year":"2024","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"key":"10.1016\/j.engappai.2025.112802_bib12","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2022.104953","article-title":"Developing a physics-informed and physics-penalized neural network model for preliminary design of multi-stage friction pendulum bearings","volume":"113","author":"Habib","year":"2022","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"3","key":"10.1016\/j.engappai.2025.112802_bib13","doi-asserted-by":"crossref","first-page":"1763","DOI":"10.1007\/s00500-021-06073-w","article-title":"Plantar pressure image classification employing residual-network model-based conditional generative adversarial networks: a comparison of normal, planus, and talipes equinovarus feet","volume":"27","author":"Han","year":"2023","journal-title":"Soft Comput."},{"key":"10.1016\/j.engappai.2025.112802_bib14","first-page":"1","article-title":"ConvNeXt network with transfer learning for cumulative foot pressure images recognition","author":"Iskandar","year":"2024","journal-title":"Int. J. Inf. Technol."},{"issue":"1","key":"10.1016\/j.engappai.2025.112802_bib15","doi-asserted-by":"crossref","first-page":"14","DOI":"10.3390\/applbiosci3010002","article-title":"The integration of artificial intelligence into clinical practice","volume":"3","author":"Karalis","year":"2024","journal-title":"Appl. Biosci."},{"year":"2024","series-title":"AdaCred: adaptive causal decision transformers with feature crediting","author":"Kumawat","key":"10.1016\/j.engappai.2025.112802_bib16"},{"issue":"1","key":"10.1016\/j.engappai.2025.112802_bib17","article-title":"Migration-Crossover algorithm: a swarm-based metaheuristic enriched with crossover technique and unbalanced neighbourhood search","volume":"17","author":"Kusuma","year":"2024","journal-title":"International Journal of Intelligent Engineering & Systems"},{"issue":"5","key":"10.1016\/j.engappai.2025.112802_bib18","first-page":"4815","article-title":"Prototypical calibrating ambiguous samples for micro-action recognition","volume":"39","author":"Li","year":"2025","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"year":"2024","series-title":"Mmad: Multi-label micro-action detection in videos","author":"Li","key":"10.1016\/j.engappai.2025.112802_bib19"},{"issue":"18","key":"10.1016\/j.engappai.2025.112802_bib20","doi-asserted-by":"crossref","first-page":"28869","DOI":"10.1109\/JSEN.2024.3435884","article-title":"DCNN-SVM-Based Gait phase recognition with inertia, EMG, and insole plantar pressure sensing","volume":"24","author":"Liu","year":"2024","journal-title":"IEEE Sens. J."},{"issue":"1","key":"10.1016\/j.engappai.2025.112802_bib21","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s12984-022-00987-8","article-title":"Deep learning approach to estimate foot pressure distribution in walking with application for a cost-effective insole system","volume":"19","author":"Mun","year":"2022","journal-title":"J. NeuroEng. Rehabil."},{"issue":"16","key":"10.1016\/j.engappai.2025.112802_bib22","doi-asserted-by":"crossref","first-page":"3947","DOI":"10.3390\/en17163947","article-title":"An overview of the multilevel control scheme utilized by microgrids","volume":"17","author":"Mussetta","year":"2024","journal-title":"Energies"},{"issue":"1","key":"10.1016\/j.engappai.2025.112802_bib23","doi-asserted-by":"crossref","first-page":"1288","DOI":"10.1109\/TVCG.2022.3209400","article-title":"On-tube attribute visualization for multivariate trajectory data","volume":"29","author":"Russig","year":"2022","journal-title":"IEEE Trans. Visual. Comput. Graph."},{"key":"10.1016\/j.engappai.2025.112802_bib24","doi-asserted-by":"crossref","DOI":"10.1016\/j.jbiomech.2023.111604","article-title":"Impact of biomechanics on therapeutic interventions and rehabilitation for major chronic musculoskeletal conditions: a 50-year perspective","volume":"154","author":"Sacco","year":"2023","journal-title":"J. Biomech."},{"issue":"9","key":"10.1016\/j.engappai.2025.112802_bib25","doi-asserted-by":"crossref","first-page":"12355","DOI":"10.1109\/JIOT.2024.3520675","article-title":"Cost-efficient and portable IoMT solution for post-stroke rehabilitation: Inferring feet pressures with lower limbs IMUs","volume":"12","author":"Shahid","year":"2024","journal-title":"IEEE Internet Things"},{"key":"10.1016\/j.engappai.2025.112802_bib26","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.108414","article-title":"A data-driven approach to full-field stress reconstruction of ship hull structure using deep learning","volume":"133","author":"Sun","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"21","key":"10.1016\/j.engappai.2025.112802_bib27","doi-asserted-by":"crossref","first-page":"9938","DOI":"10.3390\/app14219938","article-title":"Footwear and foot health: unveiling the role of proper shoe fit in preventing podiatric issues and enhancing well-being","volume":"14","author":"Tedeschi","year":"2024","journal-title":"Appl. Sci."},{"key":"10.1016\/j.engappai.2025.112802_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.111598","article-title":"Design element extraction of plantar pressure imaging employing meta-learning-based graphic convolutional neural networks","volume":"158","author":"Wang","year":"2024","journal-title":"Appl. Soft Comput."},{"issue":"2","key":"10.1016\/j.engappai.2025.112802_bib29","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1080\/0954898X.2024.2413849","article-title":"Deep self-organizing map neural networks improve the segmentation for inadequate plantar pressure imaging data set. Network","volume":"36","author":"Wang","year":"2025","journal-title":"Comput. Neural Syst."},{"key":"10.1016\/j.engappai.2025.112802_bib30","series-title":"Proceedings of the 2021 International Conference on Management of Data","first-page":"2628","article-title":"Apan: asynchronous propagation attention network for real-time temporal graph embedding","author":"Wang","year":"2021"},{"year":"2025","series-title":"BVINet: unlocking blind video inpainting with zero annotations","author":"Wu","key":"10.1016\/j.engappai.2025.112802_bib31"},{"issue":"6","key":"10.1016\/j.engappai.2025.112802_bib32","first-page":"6180","article-title":"WaveFormer: wavelet transformer for noise-robust video inpainting","volume":"38","author":"Wu","year":"2024","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"issue":"6","key":"10.1016\/j.engappai.2025.112802_bib33","doi-asserted-by":"crossref","first-page":"2753","DOI":"10.1109\/TCSVT.2022.3225911","article-title":"Divide-and-conquer completion network for video inpainting","volume":"33","author":"Wu","year":"2022","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"10.1016\/j.engappai.2025.112802_bib34","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1109\/LSP.2021.3086400","article-title":"Dapc-net: deformable alignment and pyramid context completion networks for video inpainting","volume":"28","author":"Wu","year":"2021","journal-title":"IEEE Signal Process. Lett."},{"issue":"3","key":"10.1016\/j.engappai.2025.112802_bib35","doi-asserted-by":"crossref","first-page":"257","DOI":"10.3390\/diagnostics15030257","article-title":"Bone age assessment using various medical imaging techniques enhanced by artificial intelligence","volume":"15","author":"Yuan","year":"2025","journal-title":"Diagnostics"},{"key":"10.1016\/j.engappai.2025.112802_bib36","first-page":"100355","article-title":"Prediction of dynamic plantar pressure from insole intervention for diabetic patients based on patch-based multilayer perceptron with localization embedding","volume":"12","author":"Zhang","year":"2024","journal-title":"IEEE"},{"key":"10.1016\/j.engappai.2025.112802_bib37","doi-asserted-by":"crossref","DOI":"10.1016\/j.compeleceng.2022.107819","article-title":"Ore image classification based on improved CNN","volume":"99","author":"Zhou","year":"2022","journal-title":"Comput. Electr. Eng."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197625028337?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197625028337?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T06:17:18Z","timestamp":1763446638000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197625028337"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":37,"alternative-id":["S0952197625028337"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2025.112802","relation":{},"ISSN":["0952-1976"],"issn-type":[{"type":"print","value":"0952-1976"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A physics-penalized neural network with asynchronous propagation and localization embedding for dynamic plantar pressure prediction in older adults","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2025.112802","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"112802"}}