{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T14:20:58Z","timestamp":1783606858742,"version":"3.55.0"},"reference-count":46,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"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":["Microelectronics Journal"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.mejo.2026.107294","type":"journal-article","created":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T16:34:51Z","timestamp":1780590891000},"page":"107294","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["An FPGA accelerator for lightweight dual-path spatial attention network targeting real-time cuffless blood pressure estimation"],"prefix":"10.1016","volume":"175","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6730-3167","authenticated-orcid":false,"given":"Gaoming","family":"Du","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tiancong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6949-0592","authenticated-orcid":false,"given":"Yongqiang","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9920-2435","authenticated-orcid":false,"given":"Zhenmin","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.mejo.2026.107294_b1","article-title":"Blood pressure variability and cardiovascular disease: systematic review and meta-analysis","volume":"354","author":"Stevens","year":"2016","journal-title":"Bmj"},{"issue":"2","key":"10.1016\/j.mejo.2026.107294_b2","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1088\/0967-3334\/37\/2\/227","article-title":"Impact of heart disease and calibration interval on accuracy of pulse transit time\u2013based blood pressure estimation","volume":"37","author":"Ding","year":"2016","journal-title":"Physiol. Meas."},{"issue":"10304","key":"10.1016\/j.mejo.2026.107294_b3","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1016\/S0140-6736(21)01330-1","article-title":"Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants","volume":"398","author":"Zhou","year":"2021","journal-title":"Lancet"},{"issue":"33","key":"10.1016\/j.mejo.2026.107294_b4","doi-asserted-by":"crossref","first-page":"3021","DOI":"10.1093\/eurheartj\/ehy339","article-title":"2018 Esc\/esh guidelines for the management of arterial hypertension: The task force for the management of arterial hypertension of the european society of cardiology (esc) and the european society of hypertension (esh)","volume":"39","author":"Williams","year":"2018","journal-title":"Eur. Heart J."},{"issue":"6","key":"10.1016\/j.mejo.2026.107294_b5","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1038\/hr.2017.4","article-title":"Analysis of beat-to-beat blood pressure variability response to the cold pressor test in the offspring of hypertensive and normotensive parents","volume":"40","author":"Wu","year":"2017","journal-title":"Hypertension Res."},{"key":"10.1016\/j.mejo.2026.107294_b6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13054-014-0644-4","article-title":"Accuracy of invasive arterial pressure monitoring in cardiovascular patients: an observational study","volume":"18","author":"Romagnoli","year":"2014","journal-title":"Crit. Care"},{"key":"10.1016\/j.mejo.2026.107294_b7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13054-016-1354-x","article-title":"The accuracy of blood pressure measured by arterial line and non-invasive cuff in critically ill children","volume":"20","author":"Joffe","year":"2016","journal-title":"Crit. Care"},{"issue":"3","key":"10.1016\/j.mejo.2026.107294_b8","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1186\/cc1489","article-title":"Clinical review: complications and risk factors of peripheral arterial catheters used for haemodynamic monitoring in anaesthesia and intensive care medicine","volume":"6","author":"Scheer","year":"2002","journal-title":"Crit. Care"},{"issue":"1","key":"10.1016\/j.mejo.2026.107294_b9","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1038\/s41746-019-0136-7","article-title":"The use of photoplethysmography for assessing hypertension","volume":"2","author":"Elgendi","year":"2019","journal-title":"NPJ Digit. Med."},{"issue":"4","key":"10.1016\/j.mejo.2026.107294_b10","first-page":"195","article-title":"A review on wearable photoplethysmography sensors and their potential future applications in health care","volume":"4","author":"Castaneda","year":"2018","journal-title":"Int. J. Biosens. Bioelectron."},{"issue":"5","key":"10.1016\/j.mejo.2026.107294_b11","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1109\/JBHI.2016.2614962","article-title":"A chair\u2013based unobtrusive cuffless blood pressure monitoring system based on pulse arrival time","volume":"21","author":"Tang","year":"2016","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"7","key":"10.1016\/j.mejo.2026.107294_b12","doi-asserted-by":"crossref","first-page":"2179","DOI":"10.1109\/TBME.2014.2318779","article-title":"An armband wearable device for overnight and cuff-less blood pressure measurement","volume":"61","author":"Zheng","year":"2014","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"4","key":"10.1016\/j.mejo.2026.107294_b13","doi-asserted-by":"crossref","first-page":"1068","DOI":"10.1109\/JBHI.2017.2714674","article-title":"Cuff-less blood pressure estimation using pulse waveform analysis and pulse arrival time","volume":"22","author":"Yoon","year":"2017","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"12","key":"10.1016\/j.mejo.2026.107294_b14","doi-asserted-by":"crossref","first-page":"5772","DOI":"10.1109\/JBHI.2022.3171918","article-title":"Edge2analysis: A novel aiot platform for atrial fibrillation recognition and detection","volume":"26","author":"Chen","year":"2022","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"3","key":"10.1016\/j.mejo.2026.107294_b15","doi-asserted-by":"crossref","first-page":"919","DOI":"10.3390\/s22030919","article-title":"A shallow u-net architecture for reliably predicting blood pressure (bp) from photoplethysmogram (ppg) and electrocardiogram (ecg) signals","volume":"22","author":"Mahmud","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.mejo.2026.107294_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.artmed.2020.101919","article-title":"Continuous blood pressure measurement from one-channel electrocardiogram signal using deep-learning techniques","volume":"108","author":"Miao","year":"2020","journal-title":"Artif. Intell. Med."},{"issue":"1","key":"10.1016\/j.mejo.2026.107294_b17","doi-asserted-by":"crossref","DOI":"10.2174\/0118741207322107240808095414","article-title":"Blood pressure estimation from wavelet scalogram of ppg signals using convolutional neural networks","volume":"18","author":"Maharajan","year":"2024","journal-title":"Open Biomed. Eng. J."},{"issue":"17","key":"10.1016\/j.mejo.2026.107294_b18","doi-asserted-by":"crossref","first-page":"10000","DOI":"10.1109\/JSEN.2020.2990864","article-title":"Pp-net: A deep learning framework for ppg-based blood pressure and heart rate estimation","volume":"20","author":"Panwar","year":"2020","journal-title":"IEEE Sensors J."},{"issue":"1","key":"10.1016\/j.mejo.2026.107294_b19","doi-asserted-by":"crossref","first-page":"16450","DOI":"10.1038\/s41598-024-66514-y","article-title":"Continuous blood pressure prediction system using conv-lstm network on hybrid latent features of photoplethysmogram (ppg) and electrocardiogram (ecg) signals","volume":"14","author":"Kamanditya","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.mejo.2026.107294_b20","series-title":"2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society","first-page":"6765","article-title":"Cuffless blood pressure estimation by error-correcting output coding method based on an aggregation of adaboost with a photoplethysmograph sensor","author":"Suzuki","year":"2009"},{"key":"10.1016\/j.mejo.2026.107294_b21","series-title":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","first-page":"6385","article-title":"A feature exploration methodology for learning based cuffless blood pressure measurement using photoplethysmography","author":"Duan","year":"2016"},{"issue":"4","key":"10.1016\/j.mejo.2026.107294_b22","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1109\/TBME.2016.2580904","article-title":"Cuffless blood pressure estimation algorithms for continuous health-care monitoring","volume":"64","author":"Kachuee","year":"2016","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"10.1016\/j.mejo.2026.107294_b23","series-title":"2018 IEEE EMBS International Conference on Biomedical & Health Informatics","first-page":"323","article-title":"Long-term blood pressure prediction with deep recurrent neural networks","author":"Su","year":"2018"},{"issue":"19","key":"10.1016\/j.mejo.2026.107294_b24","doi-asserted-by":"crossref","first-page":"5606","DOI":"10.3390\/s20195606","article-title":"Real-time cuffless continuous blood pressure estimation using deep learning model","volume":"20","author":"Li","year":"2020","journal-title":"Sensors"},{"issue":"1","key":"10.1016\/j.mejo.2026.107294_b25","doi-asserted-by":"crossref","first-page":"96","DOI":"10.3390\/s21010096","article-title":"Beat-to-beat continuous blood pressure estimation using bidirectional long short-term memory network","volume":"21","author":"Lee","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.mejo.2026.107294_b26","series-title":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society","first-page":"4295","article-title":"A hardware-based lightweight ann for real-time wearable blood pressure estimation","author":"Zhang","year":"2022"},{"issue":"8","key":"10.1016\/j.mejo.2026.107294_b27","doi-asserted-by":"crossref","first-page":"4145","DOI":"10.3390\/s23084145","article-title":"A ppg-based calibration-free cuffless blood pressure estimation method using cardiovascular dynamics","volume":"23","author":"Samimi","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.mejo.2026.107294_b28","series-title":"2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","first-page":"1","article-title":"Causal inference based hierarchical regression model for cuffless blood pressure estimation","author":"Song","year":"2024"},{"key":"10.1016\/j.mejo.2026.107294_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.106741","article-title":"A paralleled cnn and transformer network for ppg-based cuff-less blood pressure estimation","volume":"99","author":"Tian","year":"2025","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.mejo.2026.107294_b30","doi-asserted-by":"crossref","DOI":"10.1016\/j.mejo.2024.106247","article-title":"High-performance convolutional neural network emulation via fpga-integrated memristive circuitry","volume":"150","author":"Yang","year":"2024","journal-title":"Microelectron. J."},{"key":"10.1016\/j.mejo.2026.107294_b31","first-page":"106961","article-title":"A residual attention neural network for multi-circuit analog parameter prediction and analysis","author":"Sun","year":"2025","journal-title":"Microelectron. J."},{"key":"10.1016\/j.mejo.2026.107294_b32","doi-asserted-by":"crossref","first-page":"106903","DOI":"10.1016\/j.mejo.2025.106903","article-title":"Low-power and area-efficient cim: an sram-based fully-digital computing-in-memory hardware acceleration processor with approximate adder tree for multi-precision sparse neural networks","author":"Fang","year":"2025","journal-title":"Microelectron. J."},{"key":"10.1016\/j.mejo.2026.107294_b33","doi-asserted-by":"crossref","DOI":"10.1109\/LSSC.2026.3668853","article-title":"Emo-cim: An input\/stationary-data similarity-aware computing-in-memory design for variable vector-wise computation in edge multi-operator ai acceleration","author":"Wang","year":"2026","journal-title":"IEEE Solid-State Circuits Lett."},{"issue":"5","key":"10.1016\/j.mejo.2026.107294_b34","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1097\/CCM.0b013e31820a92c6","article-title":"Multiparameter intelligent monitoring in intensive care ii: a public-access intensive care unit database","volume":"39","author":"Saeed","year":"2011","journal-title":"Crit. Care Med."},{"key":"10.1016\/j.mejo.2026.107294_b35","series-title":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society","first-page":"504","article-title":"Energy-efficient blood pressure monitoring based on single-site photoplethysmogram on wearable devices","author":"Lin","year":"2021"},{"key":"10.1016\/j.mejo.2026.107294_b36","series-title":"2021 20th IEEE International Conference on Machine Learning and Applications","first-page":"1495","article-title":"Bp-net: Efficient deep learning for continuous arterial blood pressure estimation using photoplethysmogram","author":"Vardhan","year":"2021"},{"key":"10.1016\/j.mejo.2026.107294_b37","doi-asserted-by":"crossref","first-page":"3501","DOI":"10.1007\/s00542-020-04946-y","article-title":"A fast digital chip implementing a real-time noise-resistant algorithm for estimating blood pressure using a non-invasive, cuffless ppg sensor","volume":"26","author":"Wang","year":"2020","journal-title":"Microsyst. Technol."},{"issue":"8","key":"10.1016\/j.mejo.2026.107294_b38","doi-asserted-by":"crossref","first-page":"4300","DOI":"10.1109\/JSEN.2019.2961411","article-title":"Blood pressure estimation using photoplethysmogram signal and its morphological features","volume":"20","author":"Hasanzadeh","year":"2019","journal-title":"IEEE Sensors J."},{"key":"10.1016\/j.mejo.2026.107294_b39","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2020.101942","article-title":"Investigation on the effect of womersley number, ecg and ppg features for cuff less blood pressure estimation using machine learning","volume":"60","author":"Thambiraj","year":"2020","journal-title":"Biomed. Signal Process. Control."},{"issue":"5","key":"10.1016\/j.mejo.2026.107294_b40","doi-asserted-by":"crossref","first-page":"2096","DOI":"10.1109\/JBHI.2021.3128229","article-title":"Continuous ppg-based blood pressure monitoring using multi-linear regression","volume":"26","author":"Haddad","year":"2021","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.mejo.2026.107294_b41","series-title":"2024 IEEE Biomedical Circuits and Systems Conference (BioCAS)","first-page":"1","article-title":"Optimization and deployment of deep neural networks for ppg-based blood pressure estimation targeting low-power wearables","author":"Burrello","year":"2024"},{"key":"10.1016\/j.mejo.2026.107294_b42","series-title":"2022 3rd International Conference on Electronics, Communications and Information Technology","first-page":"7","article-title":"Design and optimization of mobilenet neural network acceleration system based on fpga","author":"Qin","year":"2022"},{"key":"10.1016\/j.mejo.2026.107294_b43","series-title":"2022 International Conference on Informatics, Networking and Computing","first-page":"81","article-title":"A high performance fpga-based accelerator for mobilenet","author":"Zhang","year":"2022"},{"key":"10.1016\/j.mejo.2026.107294_b44","series-title":"International Symposium on Applied Reconfigurable Computing","first-page":"55","article-title":"Squeezejet: High-level synthesis accelerator design for deep convolutional neural networks","author":"Mousouliotis","year":"2018"},{"key":"10.1016\/j.mejo.2026.107294_b45","series-title":"2024 3rd International Conference on Artificial Intelligence and Computer Information Technology","first-page":"1","article-title":"Fpga implementation of an improved shufflenetv2 rice diseases identification algorithm","author":"Xiong","year":"2024"},{"key":"10.1016\/j.mejo.2026.107294_b46","series-title":"2023 20th International SoC Design Conference","first-page":"173","article-title":"Hybrid cnn-lstm network for ecg classification and its software-hardware co-design approach","author":"Tang","year":"2023"}],"container-title":["Microelectronics Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S187923912600250X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S187923912600250X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T13:42:25Z","timestamp":1783604545000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S187923912600250X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":46,"alternative-id":["S187923912600250X"],"URL":"https:\/\/doi.org\/10.1016\/j.mejo.2026.107294","relation":{},"ISSN":["1879-2391"],"issn-type":[{"value":"1879-2391","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"An FPGA accelerator for lightweight dual-path spatial attention network targeting real-time cuffless blood pressure estimation","name":"articletitle","label":"Article Title"},{"value":"Microelectronics Journal","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.mejo.2026.107294","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"107294"}}