An ECG patch combining a customized ultra-low-power ECG SoC with Bluetooth low energy for long term ambulatory monitoring
Abstract
This paper presents the development of an ECG patch aiming at long term patient monitoring. The use of the recently standardized Bluetooth Low Energy (BLE) technology, together with a customized ultra-low-power ECG System on Chip (ECG SoC). including Digital Signal Processing (DSP) capabilities, enables the design of ultra low power systems able to continuously monitor patients, performing on board signal processing such as filtering, data compression, beat detection and motion artifact removal along with all the advantages provided by a standard radio technology such as Bluetooth. Early tests show how combining the ECG SoC and BLE leads to a total current consumption of only 500μA at 3.7V, while computing beat detection and transmitting heart rate remotely via BLE. This allows up to one month lifetime with a 400mAh Li-Po battery.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A single ECG pulse acquisition (assuming a 1-s acquisition) consumes around 6.1-17.4 μJ.
“A single ECG pulse acquisition (assuming a 1-s acquisition) consumes around 6.1–17.4 µJ63–65.”
From Flexible self-rectifying synapse array for energy-efficient edge multiplication in electrocardiogram diagnosis (2025) · cites this paper as [65]
Cites
Jakšić, M. M. (2007) · Electrochimica Acta · doi:10.1016/j.electacta.2007.09.034 · Cited by 153 · see citing works
Robust beat detector for ambulatory cardiac monitoring
Romero, I., Grundlehner, B., & Penders, J. (2009) · doi:10.1109/iembs.2009.5334543 · Cited by 50 · see citing works
Self-citationDevelopment and Evaluation of a Bluetooth EKG Monitoring Sensor
Proulx, J., Clifford, R., Sorensen, S. D., Lee, D.-J., & Archibald, J. K. (2006) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2006.74 · Cited by 48 · see citing works
Wireless ECG plaster for body sensor network
Munshi, M. C., Xu, X., Zou, X., Soetiono, E., Teo, C. S., & Lian, Y. (2008) · IEEE/EMBS International Summer School on Medical Devices and Biosensors (ISSS-MDBS) · doi:10.1109/issmdbs.2008.4575081 · Cited by 21 · see citing works
Development of Integrated Module using Wireless Accelerometer and ECG Sensor for ADL Monitoring
Lee, Y. B., Son, M., & Lee, M. (2007) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/health.2007.381664 · Cited by 4 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges
Serhani, M. A., Kassabi, H. T. E., Ismail, H., & Navaz, A. N. (2020) · Sensors · doi:10.3390/s20061796 · Cited by 373 · see citing works
Low-Power Wearable ECG Monitoring System for Multiple-Patient Remote Monitoring
Spano, E., Pascoli, S. D., & Iannaccone, G. (2016) · IEEE Sensors Journal · doi:10.1109/jsen.2016.2564995 · Cited by 256 · see citing works
Comprehensive survey of computational ECG analysis: Databases, methods and applications
Merdjanovska, E., & Rashkovska, A. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.117206 · Cited by 158 · see citing works
ECG patch monitors for assessment of cardiac rhythm abnormalities
Lobodzinski, S. S. (2013) · Progress in Cardiovascular Diseases · doi:10.1016/j.pcad.2013.08.006 · Cited by 119 · see citing works
Oudenhoven, J. F. M., Vullers, R. J. M., & van Schaijk, R. T. F. (2012) · International Journal of Energy Research · doi:10.1002/er.2949 · Cited by 74 · see citing works
Correlation Between Electrode-Tissue Impedance and Motion Artifact in Biopotential Recordings
Buxi, D., Kim, S., Helleputte, N. V., Altini, M., Wijsman, J., Yazıcıoğlu, R. F., Penders, J., & Hoof, C. A. V. (2012) · IEEE Sensors Journal · doi:10.1109/jsen.2012.2221163 · Cited by 72 · see citing works
Self-citationWang, Y., Doleschel, S., Wunderlich, R., & Heinen, S. J. (2015) · Journal of Medical Systems · doi:10.1007/s10916-015-0223-5 · Cited by 51 · see citing works
Evaluating Bluetooth Low Energy in realistic wireless environments
Kalaa, M. O. A., Balid, W., Bitar, N., & Refai, H. H. (2016) · IEEE Wireless Communications and Networking Conference · doi:10.1109/wcnc.2016.7564809 · Cited by 47 · see citing works
A method of REM-NREM sleep distinction using ECG signal for unobtrusive personal monitoring
Singh, J., Sharma, R. K., & Gupta, A. K. (2016) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2016.09.018 · Cited by 43 · see citing works
Bluetooth Low Energy for data streaming: Application-level analysis and recommendation
Giovanelli, D., Milosevic, B., & Farella, E. (2015) · International Workshop on Advances in Sensors and Interfaces (IWASI) · doi:10.1109/iwasi.2015.7184945 · Cited by 32 · see citing works
NFC-enabled, tattoo-like stretchable biosensor manufactured by “cut-and-paste” method
Jeong, H., Ha, T., Kuang, I., Shen, L., Dai, Z., Sun, N., & Lu, N. (2017) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2017.8037756 · Cited by 30 · see citing works
Reconstruction of 12-lead ECG Using a Single-patch Device
Lee, H. J., Lee, D., Kwon, H. B., Kim, D. Y., & Park, K. S. (2017) · Methods of Information in Medicine · doi:10.3414/me16-01-0067 · Cited by 27 · see citing works
Evaluation of Digital Compressed Sensing for Real-Time Wireless ECG System with Bluetooth low Energy
Wang, Y., Doleschel, S., Wunderlich, R., & Heinen, S. J. (2016) · Journal of Medical Systems · doi:10.1007/s10916-016-0526-1 · Cited by 20 · see citing works
Lee, Y., Rhee, H., Kim, G., Cheong, W. H., Kim, D. H., Song, H., Kay, S. N., Lee, J., & Kim, K. M. (2025) · Nature Communications · doi:10.1038/s41467-025-59589-2 · Cited by 19 · see citing works
Selection probability of data channels in Bluetooth Low Energy
Kalaa, M. O. A., & Refai, H. H. (2015) · International Wireless Communications and Mobile Computing Conference (IWCMC) · doi:10.1109/iwcmc.2015.7289073 · Cited by 16 · see citing works
Ambulatory cardiac bio-signals: From mirage to clinical reality through a decade of progress
Periyaswamy, T., & Balasubramanian, M. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.07.007 · Cited by 14 · see citing works
NCMB-Button: A Wearable Non-contact System for Long-Term Multiple Biopotential Monitoring
Li, X., & Sun, Y. (2017) · IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies · doi:10.1109/chase.2017.118 · Cited by 13 · see citing works
A wireless, low-power, smart sensor of cardiac activity for clinical remote monitoring
Massot, B., Risset, T., Michelet, G., & McAdams, E. T. (2015) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2015.7454552 · Cited by 11 · see citing works
Li, X., & Sun, Y. (2018) · Smart Health · doi:10.1016/j.smhl.2018.09.001 · Cited by 9 · see citing works
DIET: A Dynamic Energy Management Approach for Wearable Health Monitoring Devices
Yamin, N., Bhat, G., & Doppa, J. R. (2022) · Design, Automation, and Test in Europe · doi:10.23919/date54114.2022.9774553 · Cited by 9 · see citing works
Gatouillat, A., Massot, B., Badr, Y., Sejdić, E., & Géhin, C. (2018) · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · doi:10.5220/0006729101090118 · Cited by 8 · see citing works
Javaid, S., Fahim, H., Zeadally, S., & He, B. (2024) · Digital Communications and Networks · doi:10.1016/j.dcan.2024.11.012 · Cited by 9 · see citing works
Very long-term ECG monitoring patch with improved functionality and wearability
Martinez-Tabares, F. J., Gaviria-Gómez, N., & Castellanos-Dominguez, G. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6944987 · Cited by 7 · see citing works
Massot, B., Risset, T., Michelet, G., & McAdams, E. T. (2016) · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · doi:10.5220/0005843703030310 · Cited by 5 · see citing works
Role of 5G Networks in Healthcare Management System
Prasad, D., Kudva, V., Singh, A. K., Hegde, R. B., & Pradyumna, G. R. (2023) · Critical Reviews in Biomedical Engineering · doi:10.1615/critrevbiomedeng.2023047013 · Cited by 5 · see citing works
Heart Rate Detection on Single-Arm ECG by Using Dual-Median Approach
Orhan, U., & Aydın, A. (2020) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-020-04574-8 · Cited by 4 · see citing works
Craven, D., Jones, E., Glavin, M., & Kilmartin, L. (2012) · Irish Signals and Systems Conference · doi:10.1049/ic.2012.0209 · Cited by 4 · see citing works
Evaluation of a real-time low-power cardiorespiratory sensor for the IoT
Gatouillat, A., Massot, B., Badr, Y., Sejdić, E., & Géhin, C. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8513550 · Cited by 3 · see citing works
Personalized physical activity monitoring on the move
Altini, M., Penders, J., Vullers, R. J. M., & Amft, O. (2013) · Wireless Health · doi:10.1145/2534088.2534092 · Cited by 2 · see citing works
Self-citationUltra Low-Power System for Remote ECG Monitoring
Hafshejani, E. H., Rabbani, R., Azizi, Z., Barekatain, M., Khoram, E., & Fotowat‐Ahmady, A. (2021) · National and International Iranian Conference on Biomedical Engineering (ICBME) · doi:10.1109/icbme54433.2021.9750353 · Cited by 2 · see citing works
Anwar, S., Hendi, M., & Anderson, J. (2025) · ACM Workshop on CPS&IoT Security and Privacy (CPSIoTSec) · doi:10.1145/3733801.3764200 · Cited by 1 · see citing works
Design of Energy Efficient IoMT Electrocardiogram (ECG) Machine on 28 nm FPGA
Singh, P. P., Pandey, B., Bhandari, N., Bisht, S., Bisht, N., & Budhani, S. K. (2023) · Studies in big data · doi:10.1007/978-981-99-6034-7_3 · Cited by 1 · see citing works
Review Paper on Wireless Wearable Sensor System for Cardiac Activity Monitoring
Andurkar, G. K., Mohurley, M. J., & Borkar, V. (2017) · IJARCCE · doi:10.17148/ijarcce.2017.6332 · Cited by 1 · see citing works
Demonstration Paper: Personalized Physical Activity Monitoring on the Move
Altini, M., Penders, J., Vullers, R. J. M., & Amft, O. (2013)
Self-citationA Lead-Off Detection Design for an Improved Front of Bioelectrical Signal Acquisition
Tang, Y. F., Gu, X., Wu, R., Ding, J., Zhang, L., Yan, F., Ma, H., & Bu, X. (2018) · Proceedings of IEEE Sensors/Proceedings of IEEE Sensors ... · doi:10.1109/icsens.2018.8630302
Development of a New Wireless ECG Patch: A User Experience Survey
Sheikh-Ahmadi, F., Emami, K. H., Foroutan, V., Kooijman, L., Pedrammehr, S., & Asadi, H. (2024) · IEEE International Systems Conference (SysCon) · doi:10.1109/syscon61195.2024.10553539
- Authors
- Altini, M., Polito, S., Penders, J., Kim, H., Van Helleputte, N., Kim, S., & Yazicioglu, F.
- Affiliations
- Imec the Netherlands (NL)
- imec, Leuven, Belgium
- IMEC (BE)
- Venue
- Proceedings of the 2nd Conference on Wireless Health
- Publisher
- ACM
- Published
- 2011-10-10
- Pages
- 1-2
- OpenAlex
- W2085262805
- Cited by
- 36
- References
- 5
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 2 · 2022: 2 · 2021: 1 · 2020: 2 · 2019: 1 · 2018: 4 · 2017: 4 · 2016: 5 · 2015: 4 · 2014: 1 · 2013: 3 · 2012: 3
- FWCI
- 7.26
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Wireless Health (publishedVersion)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- ECG patch, Bluetooth Low Energy, Holter monitoring, onboard signal processing, beat detection, motion artifact removal, data compression, battery life
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review