Real-Time Event-Driven Classification Technique for Early Detection and Prevention of Myocardial Infarction on Wearable Systems

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High-Accuracy Stress Detection Using Wrist-Worn PPG Sensors

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Energy-Aware Integrated Neural Architecture Search and Partitioning for Distributed Internet of Things (IoT)

Huang, B., Abtahi, A., & Aminifar, A. (2024) · IEEE transactions on circuits and systems for artificial intelligence. · doi:10.1109/tcasai.2024.3493036 · Cited by 15 · see citing works

Deep Learning Framework for Classification of Mental Stress from Multimodal Datasets

Shermadurai, P., & Thiyagarajan, K. (2023) · Revue d intelligence artificielle · doi:10.18280/ria.370119 · Cited by 12 · see citing works

A systematic review on artificial intelligence approaches for smart health devices

Aversano, L., Iammarino, M., Mancino, I., & Montano, D. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2232 · Cited by 11 · see citing works

Diversity-Aware Anonymization for Structured Health Data

Aminifar, A., Rabbi, F., Pun, K. I., & Lamo, Y. (2021) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc46164.2021.9629918 · Cited by 10 · see citing works

A Lightweight Method of Myocardial Infarction Detection and Localization From Single Lead ECG Features Using Machine Learning Approach

Anwar, S. M. S., Pal, D., Mukhopadhyay, S., & Gupta, R. (2024) · IEEE Sensors Letters · doi:10.1109/lsens.2024.3374790 · Cited by 9 · see citing works

IoT Based Heart attack Detection and Heart Rate Monitoring System

Prasath, T. A., Arif, M. M., Srinivasan, S., Muthumanojkumar, A., Sushmitha, M., & Sankaran, S. (2023) · Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) · doi:10.1109/accthpa57160.2023.10083383 · Cited by 9 · see citing works

Scalable Privacy-Preserving Distributed Extremely Randomized Trees for Structured Data With Multiple Colluding Parties

Aminifar, A., Rabbi, F., & Lamo, Y. (2021) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp39728.2021.9413632 · Cited by 9 · see citing works

Toward TinyDPFL systems for real-time cardiac healthcare: Trends, challenges, and system-level perspectives on AI algorithms, hardware, and edge intelligence

Akram, M. S., Varma, B. S., Javed, A., Harkin, J., & Finlay, D. (2025) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2025.103587 · Cited by 12 · see citing works

Advancements in Sensor Technology for Monitoring and Management of Chronic Coronary Syndrome

Cricco, R., Segreti, A., Ferro, A., Beato, S., Castaldo, G., Ciancio, M., Sacco, F. M., Pennazza, G., Ussia, G. P., & Grigioni, F. (2025) · Sensors · doi:10.3390/s25154585 · Cited by 9 · see citing works

Event-Triggered Sensing for High-Quality and Low-Power Cardiovascular Monitoring Systems

Surrel, G., Teijeiro, T., Aminifar, A., Atienza, D., & Chevrier, M. (2019) · IEEE Design and Test · doi:10.1109/mdat.2019.2951126 · Cited by 7 · see citing works

Harnessing Approximate Computing for Machine Learning

Shakibhamedan, S., Aminifar, A., Vassallo, L., & TaheriNejad, N. (2024) · IEEE Computer Society Annual Symposium on VLSI · doi:10.1109/isvlsi61997.2024.00110 · Cited by 6 · see citing works

Early Changes in Acute Myocardial Infarction in Pigs: Achieving Early Detection with Wearable Devices

Li, K., Morales‐Garza, M. A., Cardoso, C. D. O., Moctezuma-Ramirez, A., Burman, A., Titus, J., Elgalad, A., & Perin, E. C. (2023) · Diagnostics · doi:10.3390/diagnostics13061006 · Cited by 5 · see citing works

SafeDeep: A Scalable Robustness Verification Framework for Deep Neural Networks

Baninajjar, A., Hosseini, K., Rezine, A., & Aminifar, A. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10097028 · Cited by 5 · see citing works

RecogNoise: Machine-Learning-Based Recognition of Noisy Segments in Electrocardiogram Signals

Aminifar, A., Khooyooz, S., Jahanjoo, A., Shakibhamedan, S., & TaheriNejad, N. (2024) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas58744.2024.10558670 · Cited by 5 · see citing works

A Novel Score for mHealth Apps to Predict and Prevent Mortality: Further Validation and Adaptation to the US Population Using the US National Health and Nutrition Examination Survey Data Set

Elnakib, S., Vecino-Ortiz, A. I., Gibson, D. G., Agarwal, S., Trujillo, A. J., Zhu, Y., & Labrique, A. B. (2022) · Journal of Medical Internet Research · doi:10.2196/36787 · Cited by 5 · see citing works

EEG glasses for real-time brain electrical activity monitoring

Zanetti, R., Aminifar, A., & Atienza, D. (2025) · Scientific Reports · doi:10.1038/s41598-025-29893-4 · Cited by 6 · see citing works

Machine Learning-Based Approach for Myocardial Infarction

Maindarkar, P., & Reka, S. S. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-16-8542-2_2 · Cited by 3 · see citing works

Assessing ECG Interpretation Expertise in Medical Practitioners Through Eye Movement Data and Neuromorphic Models

Bokhari, S. M., Shafi, M., Noor, F., Sohaib, S., Alqahtany, S. S., & Donnelly, M. P. (2025) · IEEE Access · doi:10.1109/access.2025.3528253 · Cited by 3 · see citing works

Data Compression of Photoplethysmogram Signal for IoT Application

Sahoo, R. R., Lala, A., Kundu, P. K., & Ghosh, S. K. (2022) · IEEE International Conference of Electron Devices Society Kolkata Chapter (EDKCON) · doi:10.1109/edkcon56221.2022.10032860 · Cited by 2 · see citing works

Embedded DNN Classifier for Five Different Cardiac Diseases

Akram, M. S., Varma, B. S., & Finlay, D. (2024) · Irish Signals and Systems Conference · doi:10.1109/issc61953.2024.10602922 · Cited by 2 · see citing works

A Fast and Accurate Myocardial Infarction Detector

Martin, H., Izquierdo, W., Morar, U., Cabrerizo, M., Cabrera, A., & Adjouadi, M. (2020) · International Conference on Computational Science and Computational Intelligence (CSCI) · doi:10.1109/csci51800.2020.00147 · Cited by 2 · see citing works

Effectiveness of Family-oriented Education on Self-care behaviors of Patients with Acute Myocardial Infarction: A Randomized Clinical Trial.

Molazem, Z., Taheri, E., & Kalyani, M. N. (2024) · PubMed Central · doi:10.30476/ijcbnm.2023.99393.2299 · Cited by 2 · see citing works

Clinical Impact of Self-Recognition of Recurrent Acute Myocardial Infarction: From KRMI-RCC

Kim, K., Kim, M., Seo, C.-O., Kim, H., Kim, H. R., Kang, M. G., Koh, J., Park, J. R., Kim, R. B., Ryu, D. R., et al. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13164840 · Cited by 1 · see citing works

Low-Power Consumption Inference of ECG Signals Using Differential Logic Networks

Feng, C., Wang, X., & Ye, T. T. (2024) · IEEE Asia Pacific Conference on Circuits and Systems (APCCAS) · doi:10.1109/apccas62602.2024.10808521 · Cited by 1 · see citing works

Nonlinear Feature-Based MI Detection Supported by DWT and EMD on ECG: A High-Performance Decision Support Approach

Narin, A., & Keser, M. (2026) · Biosensors · doi:10.3390/bios16030150 · Cited by 1 · see citing works

Real time Heart Attack Detection Using Emerging Technologies

Butt, R., Ijaz, T., Iftikhar, N., Sharahili, F. M. A., Altouri, M. N., & Ashraf, M. U. (2023) · International Multi-Topic Conference · doi:10.1109/inmic60434.2023.10465935 · Cited by 1 · see citing works

An Enhanced Subject-Independent Approach for Hand-Based Micro Activities Recognition

Demrozi, F., & Machot, F. A. (2024) · IEEE International Conference on Omni-layer Intelligent Systems (COINS) · doi:10.1109/coins61597.2024.10622123 · Cited by 1 · see citing works

Health Care System for Disabled Patients- A Review

Anisha, M., Sindhuja, J. F. F., Majeeth, A. A., Surekha, S., Vigneshwari, N., Prasath, T. A., Elliot, C. J., Ponmozhi, K., Thiyam, D. B., & Jeyaseelan, A. S. (2021) · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · doi:10.1109/icacite51222.2021.9404722 · Cited by 1 · see citing works

2018 Index IEEE Transactions on Biomedical Circuits and Systems Vol. 12

(2018) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2019.2892906

EVALUATION OF WEARABLE HEALTH TECHNOLOGIES IN ALZHEIMER’S PATIENTS:A SYSTEMATIC REVIEW

YILMAZ, M. E., & Kalender, S. (2022) · International Journal of Health Management and Tourism · doi:10.31201/ijhmt.1108418 · Cited by 1 · see citing works

Scalable Machine Learning in Embedded Systems For Industry 4.0 Applications

Mariño, A. R. (2022) · doi:10.20868/upm.thesis.71942

Development of a Real-Time Single-Lead Single-Beat Frequency-Independent Myocardial Infarction Detector

Martin, H. (2021) · doi:10.25148/etd.fidc009685

ECG Acquisition and HRV Analysis of Myocardial Infarction

Rajagopal, R., Jayakumar, K., Bavankrishnan, V., & Dharunkumar, K. (2023) · International Conference on Intelligent Technologies for Sustainable Electric and Communications Systems (iTech SECOM) · doi:10.1109/itechsecom59882.2023.10435013

Exploring Machine Learning Algorithms for Myocardial Infarction Diagnosis

Omary, S. E., Lahrache, S., & Ouazzani, R. E. (2024) · International Conference on Intelligent Systems and Computer Vision (ISCV) · doi:10.1109/iscv60512.2024.10620080

Miyokard Enfarktüsü Hastalarının Tespitinde Doğrusal Olmayan Özniteliklerin Performans Analizi

Narin, A., & Keser, M. (2024) · Afyon Kocatepe University Journal of Sciences and Engineering · doi:10.35414/akufemubid.1427677

Self-organized channel attention network for myocardial infarction detection from single-lead ECG

Zhang, J., Wang, Y., Peng, Y., Song, Z., Chen, K., & Wu, H. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.110412

Architecture for Health Initiative (Arch4Health): Computational Challenges in Health-Related Applications and the Role of Computer Architecture in Addressing Them

Ghiasi, N. M., Koliogeorgi, K., & Mutlu, O. (2026) · International Conference on Supercomputing · doi:10.1145/3774895.3815158

Leveraging Deep and Machine Learning for Cardiovascular Disease Using Time, Spectral, and Non-linear Analysis Framework: A Systematic Review

Singh, R. S., Besfat, H. M., Awasthi, M., Kumar, J., & Srivastava, P. K. (2026) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-026-10732-2

Optimisation and Application of Kinetic Piezoelectric Energy Harvesters Aimed at Powering Autonomous Sensors

Zelenika, S., Gljušćić, P., Brusa, E. G. M., Benasciutti, D., Blažević, D., Doria, A., Kamenar, E., & Delprete, C. (2026) · Applied Sciences · doi:10.3390/app16168192

Interpretable multi-gradient flow design for inter-patient myocardial infarction detection using Single Lead ECG

Zhang, J., Zhang, Z., Xiong, P., Du, H., Zhao, S., Cao, X., & Liu, X. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.111317

LLM-Driven Optimization of Large Language Model Inference

Aminifar, A. (2026) · IFIP/IEEE International Conference on Very Large Scale Integration · doi:10.1109/vlsi-soc70418.2026.11740566

Real-time classification technique for early detection and prevention of myocardial infarction on wearable devices

Sopic, D., Aminifar, A., Aminifar, A., & Atienza, D. (2017) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2017.8325140 · Cited by 33 · see citing works

Energy-efficient Real-time Myocardial Infarction Detection on Wearable Devices

Rashid, N., & Faruque, M. A. A. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9175232 · Cited by 21 · see citing works

Advancements in Myocardial Infarction Detection and Classification Using Wearable Devices: A Comprehensive ReviewPreprint

Abhijith, S., Rajesh, A., Manoj, M., Kollannur, S. D., Sujitta, R. V., & Panachakel, J. T. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2411.18451

Real-Time Cardiac Infarction Prediction and Alert System

Ramya, J., Sabitha, T., & Sureshkumar, C. (2026) · International Conference on Expert Clouds and Applications (ICOECA) · doi:10.1109/icoeca68095.2026.11485591

Real-Time Myocardial Infarction Detection Approaches with a Microcontroller-Based Edge-AI Device

Gragnaniello, M., Borghese, A., Marrazzo, V. R., Maresca, L., Breglio, G., Irace, A., & Riccio, M. (2024) · Sensors · doi:10.3390/s24030828 · Cited by 37 · see citing works