A Wearable Patch to Enable Long-Term Monitoring of Environmental, Activity and Hemodynamics Variables
Open accessAbstract
We present a low power multi-modal patch designed for measuring activity, altitude (based on high-resolution barometric pressure), a single-lead electrocardiogram, and a tri-axial seismocardiogram (SCG). Enabled by a novel embedded systems design methodology, this patch offers a powerful means of monitoring the physiology for both patients with chronic cardiovascular diseases, and the general population interested in personal health and fitness measures. Specifically, to the best of our knowledge, this patch represents the first demonstration of combined activity, environmental context, and hemodynamics monitoring, all on the same hardware, capable of operating for longer than 48 hours at a time with continuous recording. The three-channels of SCG and one-lead ECG are all sampled at 500 Hz with high signal-to-noise ratio, the pressure sensor is sampled at 10 Hz, and all signals are stored to a microSD card with an average current consumption of less than 2 mA from a 3.7 V coin cell (LIR2450) battery. In addition to electronic characterization, proof-of-concept exercise recovery studies were performed with this patch, suggesting the ability to discriminate between hemodynamic and electrophysiology response to light, moderate, and heavy exercise.
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The e-tattoo achieves one of the lowest total device weights (2.5 g including battery) among wearable cardiac sensors developed in prior work.
“This form factor coupled with innovative firmware for sensor interfacing and transmission of data allows us to achieve one of the lowest total device weights (2.5 g including battery) and current draws (940 µ A) among wearable cardiac sensors developed in prior work as illustrated via Ashby plot in Figure 1e. [18-24]”
From A Chest‐Conformable, Wireless Electro‐Mechanical E‐Tattoo for Measuring Multiple Cardiac Time Intervals (2023) · cites this paper as [18]
The e-tattoo achieves one of the lowest current draws (940 μA) among wearable cardiac sensors developed in prior work.
“This form factor coupled with innovative firmware for sensor interfacing and transmission of data allows us to achieve one of the lowest total device weights (2.5 g including battery) and current draws (940 µ A) among wearable cardiac sensors developed in prior work as illustrated via Ashby plot in Figure 1e. [18-24]”
From A Chest‐Conformable, Wireless Electro‐Mechanical E‐Tattoo for Measuring Multiple Cardiac Time Intervals (2023) · cites this paper as [18]
The elevated T-wave is a result of the short inter-electrode distance and not an issue caused by the dry electrodes themselves.
“The elevated T-wave is a result of the short inter-electrode distance and not an issue caused by the dry electrodes themselves, evident both by the waveform acquired from the gel electrodes placed in the same location and in the literature. [18,32-34]”
From A Chest‐Conformable, Wireless Electro‐Mechanical E‐Tattoo for Measuring Multiple Cardiac Time Intervals (2023) · cites this paper as [18]
The System Specifications section describes a patch with three gel electrodes, and the PCB Design Rationale section mentions example ECG waveforms (page numbers unavailable). Neither addresses an elevated T-wave or attributes it to short inter-electrode distance rather than dry electrodes. Searches for T-wave, electrode spacing, and dry electrodes found no passage making that comparison. (LLM, conf=0.75)
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“Our group has previously developed [24] and studied a wearable patch for ambulatory monitoring in heart failure patients and found that it accurately reflects changes in clinical status [25], [26].”
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Self-citationA Novel Method for Aortic Valve Opening Phase Detection Using SCG Signal
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“Aplethora of works have been reported in literature regarding development wireless wearable sensors for health monitoring [27], [28], [29], [30], [31].”
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“Therefore, many recent research interests have moved to a kind of body-attachable devices including patch-type [3], [4] or sticker-type [5] devices, which can provide stable body contact and reliable electrode-”
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“The SCG signal presents the vibration due to the pressure within the body and the acceleration of the blood during the diastole and systole of the cardiac cycle [15,16].”
BackgroundShandhi, M. M. H., Hersek, S., Fan, J., Sander, E., Marco, T. D., Heller, J. A., Etemadi, M., Klein, L., & Inan, O. T. (2020) · Journal of Cardiac Failure · doi:10.1016/j.cardfail.2020.05.014 · Cited by 28 · see citing works
Self-citationBaniasadi, T., Kalhori, S. R. N., Ayyoubzadeh, S. M., Zakerabasali, S., & Pourmohamadkhan, M. (2018) · Journal of Telemedicine and Telecare · doi:10.1177/1357633x18804747 · Cited by 28 · see citing works
Kang, T. W., Lee, J., Kwon, Y., Lee, Y. J., & Yeo, W. (2024) · Advanced NanoBiomed Research · doi:10.1002/anbr.202300169 · Cited by 30 · see citing works
Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis
Vićentić, T., Rafajilović, M. R., Ilić, S. D., Koteska, B., Bogdanova, A. M., Pašti, I. A., Lehocki, F., & Spasenović, M. (2022) · Sensors · doi:10.3390/s22176326 · Cited by 26 · see citing works
Kimball, J. P., Zia, J. S., An, S., Rolfes, C., Hahn, J., Sawka, M. N., & Inan, O. T. (2021) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2021.3068619 · Cited by 24 · see citing works
Self-citationBaig, M. M., GholamHosseini, H., Gutiérrez, J., Ullah, E., & Lindén, M. (2021) · Applied Clinical Informatics · doi:10.1055/s-0040-1719043 · Cited by 22 · see citing works
Autocorrelated Differential Algorithm for Real-Time Seismocardiography Analysis
D’Mello, Y., Skoric, J., Xu, S., Akhras, M., Roche, P. J. R., Lortie, M. A., Gagnon, S., & Plant, D. V. (2019) · IEEE Sensors Journal · doi:10.1109/jsen.2019.2903449 · Cited by 22 · see citing works
“ments with ECG [21], [31], or that implement pre-training for calibration to the user [32], [33].”
BackgroundInfluentialContactless, Battery-free, and Stretchable Wearable for Continuous Recording of Seismocardiograms
Hesar, M. E., Khan, D., Seyedsadrkhani, N. S., & Ingebrandt, S. (2020) · ACS Applied Electronic Materials · doi:10.1021/acsaelm.0c00768 · Cited by 22 · see citing works
Toward Wearable Estimation of Tidal Volume via Electrocardiogram and Seismocardiogram Signals
Soliman, M. M., Ganti, V. G., & Inan, O. T. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3196601 · Cited by 21 · see citing works
“These physiological signals are captured using our 108 custom patch introduced in [34], [35], [36], and [37].”
MethodSelf-citationWearable Sensing of Cardiac Timing Intervals From Cardiogenic Limb Vibration Signals
Wiens, A. D., Johnson, A., & Inan, O. T. (2016) · IEEE Sensors Journal · doi:10.1109/jsen.2016.2643780 · Cited by 19 · see citing works
Self-citationKimball, J. P., Inan, O. T., Convertino, V. A., Cardin, S., & Sawka, M. N. (2022) · Sensors · doi:10.3390/s22020442 · Cited by 19 · see citing works
“chest-worn patch originally described in [59].”
MethodInfluentialSelf-citationA wearable 1-lead necklace ECG for continuous heart rate monitoring
Iskandar, A. A., Kolla, R., Schilling, K., & Voelker, W. (2016) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2016.7749480 · Cited by 17 · see citing works
“I. INTRODUCTION In 2012, WHO estimates that more than 17.5 million people died of cardiovascular diseases i.e. heart attack or stroke.”
BackgroundInfluentialA Differential BCG Sensor System for Long Term Health Monitoring Experiment on the ISS
Kulau, U., Rust, J., Szafranski, D., Drobczyk, M., & Albrecht, U. (2022) · International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) · doi:10.1109/dcoss54816.2022.00028 · Cited by 16 · see citing works
“According to this study, the sensor systems in [24], [25] used MEMS with a rather poor signal quality.”
MethodFan, X., Zhao, Y., Wang, H., & Tsui, K. (2019) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-019-1012-8 · Cited by 15 · see citing works
Contactless Fall Detection for the Elderly
Nahian, M. J. A., Raju, M. H., Tasnim, Z., Mahmud, M., Ahad, M., & Kaiser, M. (2021) · Intelligent systems reference library · doi:10.1007/978-3-030-68590-4_8 · Cited by 13 · see citing works
Models and Techniques for Temperature Robust Systems on a Reconfigurable Platform
Shah, S. S., Töreyin, H., Hasler, J., & Natarajan, A. (2017) · Journal of Low Power Electronics and Applications · doi:10.3390/jlpea7030021 · Cited by 14 · see citing works
Tuominen, J., Lehtonen, E., Tadi, M. J., Koskinen, J., Pänkäälä, M., & Koivisto, T. (2017) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2017.8050684 · Cited by 13 · see citing works
“access to mechanical cardiac monitoring, which has been used for example in atrial fibrillation detection [5], in monitoring the hemodynamics of heart failure patients [3], in determining quiescent phases in cardiac cycles for nuclear imaging [6], and in detecting myocardial infarction [7].”
BackgroundHayirlioglu, Y. Z., & Semiz, B. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3403846 · Cited by 13 · see citing works
“Furthermore, systems capable of multiple measurements have typically been limited to recording the signals solely from the location where the device is affixed, lacking mobility functionalities [21].”
BackgroundA Flexible Near-Field Biosensor for Multisite Arterial Blood Flow Detection
Mohammed, N., Cluff, K., Sutton, M., Villafana-Ibarra, B., Loflin, B. E., Griffith, J. L., Becker, R. A., Bhandari, S., Alruwaili, F., & Desai, J. (2022) · Sensors · doi:10.3390/s22218389 · Cited by 13 · see citing works
“In addition, DCG provides information on cardiac timing intervals, such as the pre-ejection period (PEP) and left ventricular ejection time (LVET) [26,47].”
BackgroundGeetha, V., Kamath, S. S., & Salvi, S. (2020) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-7998-5024-3.ch015 · Cited by 12 · see citing works
Javaid, A. Q., Dowling, S., Etemadi, M., Heller, J. A., Roy, S., Klein, L., & Inan, O. T. (2016) · Computing in cardiology · doi:10.22489/cinc.2016.224-428 · Cited by 11 · see citing works
“Based on the findings of this paper, features can be derived to correct for posture related changes in the measured SCG signals for accurate assessment of patients with HF at home.”
BackgroundSelf-citationPersonalized ECG monitoring and adaptive machine learning
Shusterman, V., & London, B. (2023) · Journal of Electrocardiology · doi:10.1016/j.jelectrocard.2023.12.006 · Cited by 10 · see citing works
Shandhi, M. M. H., Aras, M. A., Wynn, S., Fan, J., Heller, J. A., Etemadi, M., Klein, L., & Inan, O. T. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9176074 · Cited by 10 · see citing works
“To record SCG, we used an improved version of our previously developed wearable patch [16], which incorporates a 3-axis accelerometer, ECG sensing circuitry and environmental sensing (atmospheric temperature, pressure, and humidity).”
Self-citationA Flexible Wireless Sensor Patch for Real-Time Monitoring of Heart Rate and Body Temperature
Yun, S.-O., Lee, J. H., Lee, J., & Kim, C. (2019) · IEICE Transactions on Information and Systems · doi:10.1587/transinf.2018edl8167 · Cited by 10 · see citing works
“[12] presented a low power multi-modal patch for measuring activity, altitude, ECG, and seismocardiogram (SCG) under 2 mA current consumption.”
BackgroundTechnology Innovations, Challenges and Emerging Trends in Wearable Bio-Sensor Development
Gawali, D. H., & Wadhai, V. M. (2017) · International Conference on Computing Communication Control and automation · doi:10.1109/iccubea.2017.8463742 · Cited by 9 · see citing works
“In another approach, novel embedded systems based patch has been suggested which can be used for measuring activity, altitude, a single-lead ECG, and a tri-axial seismocardiogram (SCG) [21].”
MethodClustering of heartbeats from ECG recordings obtained with wireless body sensors
Rashkovska, A., Kocev, D., & Trobec, R. (2016) · International Convention on Information and Communication Technology, Electronics and Microelectronics · doi:10.1109/mipro.2016.7522188 · Cited by 9 · see citing works
“Currently, there are only a few similar devices, but none has competing services on such advanced level [12-15].”
BackgroundA wireless optoelectronic skin patch for light delivery and thermal monitoring
Kim, H., Jin, Y., Achavananthadith, S., Lin, R., & Ho, J. S. (2021) · iScience · doi:10.1016/j.isci.2021.103284 · Cited by 9 · see citing works
“…devices for blood flow monitoring have been developed based on electrical (Etemadi et al., 2015; Rosa et al., 2019; Cluff et al., 2017), mechanical (Etemadi et al., 2015; Wiens et al., 2014), acoustic (Rosa et al., 2019; Kenny 2021; Kenny et al., 2020), and optical (Abtahi et al. 2016; Saikia and…”
MethodInfluentialWireless wearable remote physiological signals monitoring system
Srinivasa, M. G., & Pandian, P. S. (2016) · International Conference on Circuits, Control, Communication and Computing (I4C) · doi:10.1109/cimca.2016.8053275 · Cited by 8 · see citing works
Lambert, T. P., Chan, M., Sanchez-Perez, J. A., Nikbakht, M. R., Lin, D. J., Nawar, A., Bashar, S. K., Kimball, J. P., Zia, J. S., Gazi, A. H., et al. (2024) · Biosensors · doi:10.3390/bios14020061 · Cited by 8 · see citing works
“(SCG), and re fl ective photoplethysmogram (RPPG) sensors have not only demonstrated the ability to be mounted onto a chest-worn patch [28] but demonstrate the ability to provide a reliable estimate for ABVS [17,29] and to classify hypovolemia into absolute vs. relative hypovolemia [17].”
BackgroundMethodSelf-citationPark, W., Yiu, C. K., Liu, Y., Wong, T. H., Huang, X., Zhou, J., Li, J., Yao, K., Huang, Y., Li, H., et al. (2021) · Biosensors · doi:10.3390/bios11110435 · Cited by 8 · see citing works
“Especially for hemodynamic status exhibiting the overall physiological condition, the usage of wearable electronics has drawn significant attention due to their availability for noninvasive [58], wireless, safe, and instantaneous measurement by simple wearing in contrast to the conventional imaging technologies [59,60…”
BackgroundA Portable Cardiac Dynamic Monitoring System in the Framework of Electro-Mechano-Acoustic Mapping
Gao, Z., Wang, Y., Xu, X., Zhang, C., Dai, Z., Zhang, H., Zhang, J., & Yang, H. (2023) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2023.3307188 · Cited by 7 · see citing works
“CombinedsignalanalysisofECGandSCG[15],[16],[17],[23], [24],ECGandPCG[12],[13],[14],[18],[19],[20],[21],ECG and PCG and SCG [22], PCG and SCG [30], [31], [32], [33], and SCG and GCG [29] were performed to reflect cardiac activity and hemodynamic changes.”
InfluentialOptimizing stations location for urban noise continuous intelligent monitoring
Huang, B., Zhen-kuan, P., Yang, H., Hou, G., & Wei, W. (2017) · Applied Acoustics · doi:10.1016/j.apacoust.2017.06.009 · Cited by 7 · see citing works
Chang, I. S. J., Javaid, A. Q., Boger, J. N., Arcelus, A., & Mihailidis, A. (2018) · Gerontechnology · doi:10.4017/gt.2018.17.2.002.00 · Cited by 7 · see citing works
Prediction of electrocardiography features points using seismocardiography data
Dürichen, R., Verma, K. D., Yee, S. Y., Rocznik, T., Schmidt, P., Bödecker, J., & Peters, C. (2018) · ACM International Symposium on Wearable Computers (ISWC) · doi:10.1145/3267242.3267283 · Cited by 7 · see citing works
“In recent years, research groups have developed different wearable sensor patches [2, 4], which often consist of a combination of SCG and ECG sensors.”
Background(2022) · doi:10.1109/embc48229.2022.9872005 · Cited by 7 · see citing works
Bio-inspired Topology of Wearable Sensor Fusion for Telemedical Application
Kańtoch, E., Grochala, D., & Kajor, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-59063-9_59 · Cited by 6 · see citing works
Mohammed, H., Chen, H., Li, Y., Sabor, N., Wang, J., & Wang, G. (2023) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2023.3334960 · Cited by 6 · see citing works
“Amongst the monitored hemodynamic parameters used to characterize cardiovascular system (CVS) health and performance are Blood Flow (F), Blood Pressure (BP), Stroke Volume (SV), and Cardiac Output (CO) [71], [72].”
BackgroundHeartbeat Detection Using Multidimensional Cardiac Motion Signals and Dynamic Balancing
Hurnanen, T., Kaisti, M., Tadi, M. J., Vähä-Heikkilä, M., Nieminen, S., Iftikhar, Z., Paukkunen, M., Pänkäälä, M., & Koivisto, T. (2017) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-981-10-5122-7_224 · Cited by 6 · see citing works
Wearable Sensing of Left Ventricular Function
Inan, O. T. (2017) · Springer eBooks · doi:10.1007/978-3-319-51394-2_14 · Cited by 6 · see citing works
Self-citation“Wear and Forget” patch for ambient assisted living
Ozgit, D., Butler, T., Oluwasanya, P. W., Occhipinti, L. G., & Hiralal, P. (2019) · IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS) · doi:10.1109/fleps.2019.8792270 · Cited by 6 · see citing works
“, [9] presented a PCB-based low power wearable patch for activity monitoring using a seismocardiogram and an electrocardiogram.”
MethodLong-term follow-up case study of atrial fibrillation after treatment
Jan, M., & Trobec, R. (2017) · International Convention on Information and Communication Technology, Electronics and Microelectronics · doi:10.23919/mipro.2017.7973438 · Cited by 5 · see citing works
“External cardiac monitors, such as (i) non-invasive but obtrusive Holter monitors, (ii) implantable cardiac monitors (ICM) or loop recorders [10], and currently, (iii) wireless ECG body sensors [11, 12], incorporated into a system of mobile cardiac patients monitoring [13], are among the most common approaches.”
BackgroundJohnson, E., Etemadi, M., Malaisrie, S. C., McCarthy, P. M., Markl, M., & Barker, A. J. (2019) · Journal of Cardiac Surgery · doi:10.1111/jocs.14289 · Cited by 5 · see citing works
“A custom built wearable device measuring electrocardiogram voltages and physical accelerations recorded the SCG.6 Acceleration frequencies up to 250Hz were recorded, above the typical SCG range.”
BackgroundSelf-citationAnalysis of physiological changes related to emotions during a zipline activity
Dupré, D., Andelic, N., Moore, D. S., Morrison, G., & McKeown, G. J. (2020) · Sports Engineering · doi:10.1007/s12283-020-00328-9 · Cited by 5 · see citing works
“The use of wearable sensors for exercise and sport performance monitoring have become common as the technology of the devices has improved [5].”
BackgroundAgam, A., Agam, A., Korsgaard, E., Haugstrup, T. Y., Kristensen, C. B., Møgelvang, R., Kragholm, K. H., Emerek, K. J. G., Søgaard, P., & Schmidt, S. E. (2025) · European Heart Journal - Digital Health · doi:10.1093/ehjdh/ztaf037 · Cited by 4 · see citing works
“The findings from this study, along with those Agam et al ., 20 Omar et al. , 21 Shandi et al ., 27 and Etemadi et al. 33 suggest that SCG could play a valuable role in the identification and monitoring of HF or hydration status in patients.”
Fog-Enabled Multimodal Chest-Worn Device for Systolic Blood Pressure Monitoring
Salas, P., Mejia, J. M., & González-Landaeta, R. (2025) · IEEE Access · doi:10.1109/access.2025.3571829 · Cited by 4 · see citing works
“Etemadi et al. [10] proposed a multimodal patch for the long-term monitoring of activity and hemodynamic variables, which included a single-lead ECG detected by three wet electrodes and a triaxial SCG detected by a triaxial accelerometer.”
Nawar, A., Gazi, A., Chan, M., Sanchez-Perez, J. A., Rahman, F. N., Ziegler, C., Daaboul, O., Haddad, G., Al-Abboud, O. A., Ahmed, H., et al. (2025) · ACM Trans. Comput. Heal. · doi:10.1145/3771549 · Cited by 6 · see citing works
“Similarly to the ECG, these cutoffs were chosen based on values used in prior work to reduce the effects of low-frequency baseline wander and high frequency noise [15, 22, 46].”
Self-citationJin, Y., Zhang, Y., Hu, L., Gu, Z., Zhao, J. P., Liu, Y., Lou, Y., Li, Y., Luo, Z., & Zeng, Y. (2023) · Analog Integrated Circuits and Signal Processing · doi:10.1007/s10470-023-02187-3 · Cited by 4 · see citing works
Wearable Systems for Unveiling Collective Intelligence in Clinical Settings
Pulcinelli, M., Pinnelli, M., Massaroni, C., Presti, D. L., Fortino, G., & Schena, E. (2023) · Sensors · doi:10.3390/s23249777 · Cited by 3 · see citing works
“When choosing a tri-axial accelerometer, three specific SCG components are provided [104].”
MethodRemote Patient Monitoring System Based on Wireless Wearable Chest Patch
Javed, F., Flood, J., Tellez, D., & Kirkpatrick, R. (2024) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc53108.2024.10782729 · Cited by 3 · see citing works
Multi-Modal Cardiopulmonary Sensing at the Chest Leveraging Hemodynamics and Cardiac Timings
Inan, O. T., Berkebile, J. A., Cook, J. M., Sanchez-Perez, J. A., Crane, H. T., & Ganti, V. G. (2025) · IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) · doi:10.1109/metroind4.0iot66048.2025.11121946 · Cited by 2 · see citing works
“In 2015, we first described a wearable patch system for the measurement of ECG, SCG, and environmental variables (temperature and ambient pressure) [5].”
Self-citationRANCANG BANGUN ALAT MONITORING ELEKTROKARDIOGRAM (ECG) PORTABEL BERBASIS ARDUINO
Nissa, H., Rachman, A. S., & Al, S. S. M. (2024) · TESLA Jurnal Teknik Elektro · doi:10.24912/tesla.v26i1.29356 · Cited by 1 · see citing works
A Compact Multimodal Patch for Continuous and Electrode-Free Cardiopulmonary Monitoring
Semiz, B. (2025) · Gazi University Journal of Science Part A Engineering and Innovation · doi:10.54287/gujsa.1737897 · Cited by 1 · see citing works
Zhao, Y., Xu, F., Fan, X., Wang, H., Tsui, K., & Guan, Y. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph191711136 · Cited by 1 · see citing works
Dual-Modality Electromechanical Physiology Source Mapping
Lu, G., Chen, K., Wang, Q., & Cai, X. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3382347 · Cited by 1 · see citing works
“Seismocardiography is a portable and unob-structive method to record cardiac vibrations on the thoracic wall through an accelerometer [8], which can be easily integrated with other modalities of cardiac measurement, such as ECG [9] and impedance cardiogram (ICG) [10].”
MethodJavaid, A. Q. (2016) · SMARTech Repository (Georgia Institute of Technology) · Cited by 1 · see citing works
Passive Physiological Monitoring via Ambient Sensors Embedded in a Home Environment
Chang, S.-J. I. (2019) · TSpace (University of Toronto) · Cited by 1 · see citing works
Case Study on State-of-the-Art Wellness and Health Tracker Devices
Vyas, S., & Gupta, S. (2022) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-7998-8786-7.ch020
Díaz, Y., Salas, P., González, C. C., Mejía-Muñoz, J.-M., & González-Landaeta, R. (2025) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-031-82126-4_1
Bicen, A. O. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5374953
Cook, J. M., Chen, C., Inan, F. B., Nichols, C. J., Rahman, F. N., Nawar, A., Reichelt, L. J., Cho, M., Sangar, Y., Hester, J., et al. (2026) · IEEE Sensors Journal · doi:10.1109/jsen.2026.3702932
“The remaining five sensors described by [33], [34], [35], [36], and [37] incorporate varying combinations of ECG, SCG, PPG, and IMU / microphones.”
Self-citationGamage, P. T., Weerasinghe, Y., Weerasinghe, P., & Kaya, M. (2026) · Annals of Biomedical Engineering · doi:10.1007/s10439-026-04366-5
- Authors
- Etemadi, M., Inan, O. T., Heller, J. A., Hersek, S., Klein, L., & Roy, S.
- Affiliations
- University of California, San Francisco (US)
- Georgia Institute of Technology (US)
- Venue
- IEEE Transactions on Biomedical Circuits and Systems
- Published
- 2016-04
- Volume
- 10
- Issue
- 2
- Pages
- 280-288
- ISSN
- 1932-4545 (ISSN-L)
- 1940-9990
- PMC
- PMC4643430
- OpenAlex
- W2290287932
- Cited by
- 95
- References
- 32
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 7 · 2023: 6 · 2022: 10 · 2021: 9 · 2020: 11 · 2019: 12 · 2018: 5 · 2017: 15 · 2016: 11
- FWCI
- 5.14
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- IEEE Transactions on Biomedical Circuits and Systems (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- NIH MSTP fellowship ((T32GMO7618)
- NIH/NCRR UCSF-CTSI (UL1 RR024131)
- NIH STTR (1R41HL110466)
- FDA P50 (2P50FD003793)
- CIMIT 2012 Prize for Primary Healthcare Competition
- National Center for Advancing Translational Sciences, National Institutes of Health (UL1 TR000004)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- wearable patch, seismocardiography, single-lead ECG, altitude measurement, activity monitoring, long-term physiological monitoring, low-power embedded systems, exercise hemodynamics, post-exercise recovery, personal health monitoring
- MeSH terms
- Electrocardiography, Equipment Design, Hemodynamics, Humans, Kinetocardiography, Electric Power Supplies, Exercise
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