{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T16:16:17Z","timestamp":1788020177573,"version":"build-2784847793"},"reference-count":11,"publisher":"Elsevier BV","issue":"2","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T00:00:00Z","timestamp":1781308800000},"content-version":"vor","delay-in-days":73,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008050","name":"University of Shanghai for Science and Technology","doi-asserted-by":"publisher","award":["SH2026296"],"award-info":[{"award-number":["SH2026296"]}],"id":[{"id":"10.13039\/501100008050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008050","name":"University of Shanghai for Science and Technology","doi-asserted-by":"publisher","award":["JXJY202609"],"award-info":[{"award-number":["JXJY202609"]}],"id":[{"id":"10.13039\/501100008050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008050","name":"University of Shanghai for Science and Technology","doi-asserted-by":"publisher","award":["SH2026295"],"award-info":[{"award-number":["SH2026295"]}],"id":[{"id":"10.13039\/501100008050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008050","name":"University of Shanghai for Science and Technology","doi-asserted-by":"publisher","award":["CFTD2026ZD17"],"award-info":[{"award-number":["CFTD2026ZD17"]}],"id":[{"id":"10.13039\/501100008050","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.es","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Clinical and Health Psychology"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.ijchp.2026.100706","type":"journal-article","created":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T03:37:10Z","timestamp":1781926630000},"page":"100706","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hierarchical deep Q-network for anomaly detection and interpretation in multidimensional time-series physical fitness data"],"prefix":"10.1016","volume":"26","author":[{"given":"Xiaoling","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingchen","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1056-8188","authenticated-orcid":false,"given":"Rende","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"2","key":"10.1016\/j.ijchp.2026.100706_bib0001","doi-asserted-by":"crossref","first-page":"3446","DOI":"10.1109\/JIOT.2023.3296809","article-title":"Explainable AI for event and anomaly detection and classification in healthcare monitoring systems","volume":"11","author":"Abououf","year":"2023","journal-title":"IEEE Internet of Things Journal"},{"key":"10.1016\/j.ijchp.2026.100706_bib0003","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.comcom.2021.07.010","article-title":"Reinforcement learning multi-agent system for faults diagnosis of microservices in industrial settings","volume":"177","author":"Belhadi","year":"2021","journal-title":"Computer Communications"},{"issue":"4","key":"10.1016\/j.ijchp.2026.100706_bib0004","doi-asserted-by":"crossref","first-page":"405","DOI":"10.3390\/bioengineering10040405","article-title":"Anomaly detection for sensor signals utilizing deep learning autoencoder-based neural networks","volume":"10","author":"Esmaeili","year":"2023","journal-title":"Bioengineering"},{"issue":"5","key":"10.1016\/j.ijchp.2026.100706_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.acalib.2025.103100","article-title":"Academic librarians in research competitions: A network analysis of resource provision and collaborative dynamics","volume":"51","author":"Li","year":"2025","journal-title":"The Journal of Academic Librarianship"},{"key":"10.1016\/j.ijchp.2026.100706_bib0006","series-title":"International Conference on Safety and Security in IoT","first-page":"111","article-title":"A novel transformer-based anomaly detection approach for ECG monitoring healthcare system","author":"Nguyen","year":"2023"},{"issue":"5","key":"10.1016\/j.ijchp.2026.100706_bib0008","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","article-title":"Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead","volume":"1","author":"Rudin","year":"2019","journal-title":"Nature Machine Intelligence"},{"issue":"1","key":"10.1016\/j.ijchp.2026.100706_bib0009","doi-asserted-by":"crossref","first-page":"2692","DOI":"10.1038\/s41598-025-85822-5","article-title":"Design of an integrated model with temporal graph attention and transformer-augmented RNNs for enhanced anomaly detection","volume":"15","author":"Veesam","year":"2025","journal-title":"Scientific Reports"},{"key":"10.1016\/j.ijchp.2026.100706_bib0011","first-page":"1","article-title":"MhaGNN: A novel framework for wearable sensor-based human activity recognition combining multi-head attention and graph neural networks","volume":"72","author":"Wang","year":"2023","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"issue":"13","key":"10.1016\/j.ijchp.2026.100706_bib0012","doi-asserted-by":"crossref","first-page":"4755","DOI":"10.3390\/s22134755","article-title":"Semi-supervised adversarial learning using LSTM for human activity recognition","volume":"22","author":"Yang","year":"2022","journal-title":"Sensors"},{"issue":"23","key":"10.1016\/j.ijchp.2026.100706_bib0013","doi-asserted-by":"crossref","first-page":"18775","DOI":"10.1007\/s00521-024-10536-0","article-title":"Agent-based dynamic thresholding for adaptive anomaly detection using reinforcement learning","volume":"37","author":"Yang","year":"2025","journal-title":"Neural Computing and Applications"},{"issue":"1","key":"10.1016\/j.ijchp.2026.100706_bib0016","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3691338","article-title":"Deep learning for time series anomaly detection: A survey","volume":"57","author":"Zamanzadeh Darban","year":"2025","journal-title":"ACM Computing Surveys"}],"container-title":["International Journal of Clinical and Health Psychology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1697260026000426?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1697260026000426?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T15:21:00Z","timestamp":1788016860000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1697260026000426"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":11,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["S1697260026000426"],"URL":"https:\/\/doi.org\/10.1016\/j.ijchp.2026.100706","relation":{},"ISSN":["1697-2600"],"issn-type":[{"value":"1697-2600","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Hierarchical deep Q-network for anomaly detection and interpretation in multidimensional time-series physical fitness data","name":"articletitle","label":"Article Title"},{"value":"International Journal of Clinical and Health Psychology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ijchp.2026.100706","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"100706"}}