The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
A Systematic Review of Wearable Patient Monitoring Systems–Current Challenges and Opportunities for Clinical Adoption
Abstract
The aim of this review is to investigate barriers and challenges of wearable patient monitoring (WPM) solutions adopted by clinicians in acute, as well as in community, care settings. Currently, healthcare providers are coping with ever-growing healthcare challenges including an ageing population, chronic diseases, the cost of hospitalization, and the risk of medical errors. WPM systems are a potential solution for addressing some of these challenges by enabling advanced sensors, wearable technology, and secure and effective communication platforms between the clinicians and patients. A total of 791 articles were screened and 20 were selected for this review. The most common publication venue was conference proceedings (13, 54%). This review only considered recent studies published between 2015 and 2017. The identified studies involved chronic conditions (6, 30%), rehabilitation (7, 35%), cardiovascular diseases (4, 20%), falls (2, 10%) and mental health (1, 5%). Most studies focussed on the system aspects of WPM solutions including advanced sensors, wireless data collection, communication platform and clinical usability based on a specific area or disease. The current studies are progressing with localized sensor-software integration to solve a specific use-case/health area using non-scalable and 'silo' solutions. There is further work required regarding interoperability and clinical acceptance challenges. The advancement of wearable technology and possibilities of using machine learning and artificial intelligence in healthcare is a concept that has been investigated by many studies. We believe future patient monitoring and medical treatments will build upon efficient and affordable solutions of wearable technology.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
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?
In the citing paper
“Wearable technology enables remote monitoring of patients and personalized care.”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [4]
In the citing paper
“In addition, they can significantly reduce healthcare costs by reducing the number of hospitalizations and emergency room visits, which can be expensive for both individuals and the healthcare system.”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [4]
In the citing paper
“For instance, these algorithms were employed to predict the onset of chronic diseases, such as diabetes, cardiovascular disease, and mental health issues, by measuring heart rate and blood glucose meters [4,186].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [4]
In the citing paper
“Integration with smartphones and mobile devices enhances the accessibility of wearable ECG monitors for real-time monitoring, data storage, and cloud-based analytics, enabling seamless integration into telemedicine and remote patient monitoring systems [4,16,17].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [4]
Citations
Cites
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & the PRISMA Group* (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-151-4-200908180-00135 · Cited by 37,554
A review of wearable sensors and systems with application in rehabilitation
Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2012) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-9-21 · Cited by 2,396
A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis
Pantelopoulos, A., & Bourbakis, N. G. (2010) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2009.2032660 · Cited by 2,296
Wearable Sensors for Human Activity Monitoring: A Review
Mukhopadhyay, S. C. (2015) · IEEE Sensors Journal · doi:10.1109/jsen.2014.2370945 · Cited by 1,401
Wireless sensor networks for personal health monitoring: Issues and an implementation
Milenković, A., Otto, C., & Jovanov, E. (2006) · Computer Communications · doi:10.1016/j.comcom.2006.02.011 · Cited by 1,023
CodeBlue: An Ad Hoc Sensor Network Infrastructure for Emergency Medical Care
Malan, D. J., Fulford-Jones, T. R. F., Welsh, M., & Moulton, S. (2004) · Digital Access to Scholarship at Harvard (DASH) (Harvard University) · Cited by 798
An IoT-cloud Based Wearable ECG Monitoring System for Smart Healthcare
Yang, Z., Zhou, Q., Lei, L., Zheng, K., & Xiang, W. (2016) · Journal of Medical Systems · doi:10.1007/s10916-016-0644-9 · Cited by 490
Banaee, H., Ahmed, M., & Loutfi, A. (2013) · Sensors · doi:10.3390/s131217472 · Cited by 452
Research works printed but not linked: 2
- O’Shaughnessy, C., The Basics: National Spending for Long-Term Services and Supports. 2012. National Health Policy Forum, George Washington University, Washington DC, 2013.
- Wu, J., et al., The promising future of healthcare services: When big data analytics meets wearable technology. Inf. Manag. 53(8):1020–1033, 2016. · DOI
Cited by
Sorted by citations
Items 101–200 of 350
Taylor, P. J., Thompson, C. H., Luscombe‐Marsh, N. D., Wycherley, T. P., Wittert, G., Brinkworth, G. D., & Zajac, I. T. (2019) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2019.107814 · Cited by 21
Advances and New Therapies in Traumatic Spinal Cord Injury
Montoto-Marqués, A., Benito-Penalva, J., Ferreiro-Velasco, M. E., Wright, M. A., de la Barrera, S. S., Kumru, H., Gaitán-Pérez, N., Hernández-Navarro, A., Rodríguez-Sotillo, A., Braga, F. M., et al. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14072203 · Cited by 25
Stavropoulos, T. G., Μεδίτσκος, Γ., Lazarou, I., Mpaltadoros, L., Papagiannopoulos, S., Tsolaki, M., & Kompatsiaris, I. Y. (2021) · Sensors · doi:10.3390/s21186230 · Cited by 21
From Wearables to Implantables: Harnessing Sensor Technologies for Continuous Health Monitoring
Koruprolu, A., Hack, T., Ghadami, O., Jain, A., & Hall, D. A. (2025) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2025.3568754 · Cited by 20
Boateng, G., Motti, V. G., Mishra, V., Batsis, J. A., Hester, J. D., & Kotz, D. F. (2019) · ACM Annual International Conference on Mobile Computing and Networking (MobiCom) · doi:10.1145/3300061.3345432 · Cited by 20
Sensing Affect to Empower Students
Wang, Q., Jing, S., Joyner, D. A., Wilcox, L. G., Li, H., Plötz, T., & DiSalvo, B. J. (2020) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3386527.3405917 · Cited by 19
Identifying critical success factors for wearable medical devices: a comprehensive exploration
Değerli, M., & Özkan, S. (2020) · Universal Access in the Information Society · doi:10.1007/s10209-020-00763-2 · Cited by 21
Development and Initial Validation of an Acute Readiness Monitoring Scale in Military Personnel
Keegan, R. J., Flood, A. P., Niyonsenga, T., Welvaert, M., Rattray, B., Sarkar, M., Melberzs, L., & Crone, D. J. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.738609 · Cited by 23
Developments in healthcare information systems in Ireland and internationally
ESRI, Walsh, B., Domhnaill, C. M., ESRI, Mohan, G., & ESRI (2021) · doi:10.26504/sustat105 · Cited by 18
Kwon, K., Lee, Y. J., Chung, S., Lee, J., Na, Y., Kwon, Y., Shin, B., Bateman, A., Lee, J., Guess, M., et al. (2025) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.4c17369 · Cited by 18
Baluta, S., Suresh, V., Chmielowska, M., Smeesters, L., & Cabaj, J. (2026) · ACS Omega · doi:10.1021/acsomega.5c06072 · Cited by 20
Reliability Assessment of New and Updated Consumer-Grade Activity and Heart Rate Monitors
Oniani, S., Woolley, S. I., Pires, I. M., García, N. M., Collins, T., Ledger, S., & Pandyan, A. D. (2018) · Keele Research Repository (Keele University) · doi:10.13140/rg.2.2.35628.72328 · Cited by 18
Souza, J., Escadas, S., Baxevani, I., Rodrigues, D., & Freitas, A. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192215231 · Cited by 18
Recent advances of nanogenerator technology for cardiovascular sensing and monitoring
Liu, W., & Wang, X. (2023) · Nano Energy · doi:10.1016/j.nanoen.2023.108910 · Cited by 18
Wearable system for real-time monitoring of hemodynamic parameters: Implementation and evaluation
Girčys, R., Kazanavičius, E., Maskeliūnas, R., Damaševičius, R., & Woźniak, M. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.101873 · Cited by 18
Wu, S., Cao, W., Fu, S., Yao, B., Yang, Z., Yin, C., Mishra, V., Addison, D., Zhang, P., & Wang, D. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714272 · Cited by 22
Emerging Trends in AI-Driven Health Tech: A Comprehensive Review and Future Prospects
Mullankandy, S., Kazmi, I., Islam, T., & Phia, W. J. (2024) · European Journal of Technology · doi:10.47672/ejt.1888 · Cited by 17
Khorev, V. S., Kiselev, A. R., Badarin, A., Antipov, V. M., Drapkina, O. M., Kurkin, S., & Hramov, A. E. (2024) · The European Physical Journal Special Topics · doi:10.1140/epjs/s11734-024-01289-x · Cited by 17
Remote Health Monitoring in Clinical Trial using Machine Learning Techniques: A Conceptual Framework
Abiodun, T. N., Okunbor, D. I., & Osamor, V. C. (2022) · Health and Technology · doi:10.1007/s12553-022-00652-z · Cited by 17
Kumar, P. S., Ramasamy, M., Kallur, K. R., Rai, P., & Varadan, V. K. (2023) · Sensors · doi:10.3390/s23031389 · Cited by 16
Rehabilitation Technologies for Chronic Conditions: Will We Sink or Swim?
LaMarca, A., Tse, I., & Keysor, J. J. (2023) · Healthcare · doi:10.3390/healthcare11202751 · Cited by 16
Zhang, Z., Amegbor, P. M., & Sabel, C. E. (2021) · Sensors · doi:10.3390/s21227693 · Cited by 15
High-Sensitivity Electric Potential Sensors for Non-Contact Monitoring of Physiological Signals
Tang, X., Chen, W., Mandal, S., Bi, K., & Özdemir, T. (2022) · IEEE Access · doi:10.1109/access.2022.3150587 · Cited by 13
3D textile structures with integrated electroactive electrodes for wearable electrochemical sensors
Farajikhah, S., Choi, J., Esrafilzadeh, D., Underwood, J., Innis, P. C., Paull, B., & Wallace, G. G. (2020) · Journal of the Textile Institute · doi:10.1080/00405000.2020.1720968 · Cited by 14
Ferguson, C., Inglis, S. C., Breen, P. P., Gargiulo, G. D., Byiers, V., Macdonald, P. S., & Hickman, L. (2020) · JMIR Aging · doi:10.2196/17299 · Cited by 15
MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data
Ollenschläger, M., Küderle, A., Mehringer, W. A., Seifer, A.-K., Winkler, J., Gaßner, H., Kluge, F., & Eskofier, B. M. (2022) · Sensors · doi:10.3390/s22155849 · Cited by 14
Wearable Device Technology in Healthcare—Exploring Constraining and Enabling Factors
Krey, M. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-981-15-0637-6_1 · Cited by 15
Chakravorty, T., Jha, K., Barthwal, S., & Chakraborty, S. (2020) · Journal of international technology and information management · doi:10.58729/1941-6679.1438 · Cited by 14
Evolving dynamic self-adaptation policies of mHealth systems for long-term monitoring
Ballesteros, J., Ayala, I., Caro-Romero, J. R., Amor, M., & Fuentes, L. (2020) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2020.103494 · Cited by 13
Ocagli, H., Lorenzoni, G., Lanera, C., Schiavo, A., D’Angelo, L., Liberti, A. D., Besola, L., Cibin, G., Martinato, M., Azzolina, D., et al. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18137171 · Cited by 14
Kim, J., & Kim, J. (2023) · Sensors · doi:10.3390/s23125736 · Cited by 13
A Smart Solution for Proprioceptive Rehabilitation through M-IMU Sensors
Lapresa, M., Tamantini, C., di Luzio, F. S., Cordella, F., Bravi, M., Miccinilli, S., & Zollo, L. (2020) · IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) · doi:10.1109/metroind4.0iot48571.2020.9138193 · Cited by 12
Intelligent reliability assurance methodologies for engineering systems: advances and challenges
Liu, Z., Zhang, Q., Liu, Y., Lei, Y., & Zuo, M. J. (2025) · Journal of Reliability Science and Engineering · doi:10.1088/3050-2454/ae047e · Cited by 11
Exploring the Potential Use of Wearable Devices as a Prognostic Tool among Patients in Hospice Care
Huang, Y., Kabir, M. A., Upadhyay, U., Dhar, E., Uddin, M., & Syed-Abdul, S. (2022) · Medicina · doi:10.3390/medicina58121824 · Cited by 11
Remote monitoring for long-term physical health conditions: an evidence and gap map
de Bell, S., Zhelev, Z., Shaw, N., Bethel, A. C., Anderson, R., & Coon, J. T. (2023) · Health and Social Care Delivery Research · doi:10.3310/bvcf6192 · Cited by 12
Ravikumar, C. P., Sudheer, P., & Kumar, P. (2023) · International Journal of Education and Management Engineering · doi:10.5815/ijeme.2023.06.04 · Cited by 12
Scardulla, F., Cosoli, G., Gnoffo, C., Antognoli, L., Bongiorno, F., Diana, G., Scalise, L., D’Acquisto, L., & Arnesano, M. (2025) · Sensors · doi:10.3390/s25144477 · Cited by 13
Post marketing study of hemodynamic and hematological noninvasive readings in a blood bank
Segman, Y. J., & Sheiman, E. (2018) · SAGE Open Medicine · doi:10.1177/2050312118796065 · Cited by 25
Baig, M. M., Mirza, F., GholamHosseini, H., Gutiérrez, J., & Ullah, E. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8513343 · Cited by 11
Self-citationWireless monitoring and artificial intelligence: A bright future in cardiothoracic surgery
Kalfa, D. M., Agrawal, S. K., Goldshtrom, N., LaPar, D. J., & BACHA, E. A. (2019) · Journal of Thoracic and Cardiovascular Surgery · doi:10.1016/j.jtcvs.2019.08.141 · Cited by 11
Matni, N., Moraes, J., Pacheco, L., do Rosário, D. L., Oliveira, H. M. N. D. S., Cerqueira, E., & Neto, A. (2020) · International Wireless Communications and Mobile Computing Conference (IWCMC) · doi:10.1109/iwcmc48107.2020.9148524 · Cited by 11
Keogh, A., Johnston, W., Ashton, M., Sett, N., Mullan, R. H., Donnelly, S. C., Dorn, J. F., Calvo, F., Namee, B. M., & Caulfield, B. (2020) · Digital Biomarkers · doi:10.1159/000512044 · Cited by 12
Enablers for IoT Regarding Wearable Medical Devices to Support Healthy Living: The Five Facets
Değerli, M., & Özkan, S. (2021) · Studies in computational intelligence · doi:10.1007/978-981-15-9897-5_10 · Cited by 10
Wearable Devices for Patient Monitoring System using IoT
Arunkumar, J. R., Raman, R., Sivakumar, S., & Pavithra, R. (2023) · International Conference on Communication and Electronics Systems (ICCES) · doi:10.1109/icces57224.2023.10192741 · Cited by 10
Matti, C., Essig, S., Föhn, Z., & Balthasar, A. (2023) · Journal of Medical Systems · doi:10.1007/s10916-023-01998-1 · Cited by 10
Wong, A. K. C., Bayuo, J., Su, J. J., Wong, F. K. Y., Chow, K. K. S., Wong, B. P., Wong, S. M., & Hui, V. C. C. (2024) · Journal of Medical Internet Research · doi:10.2196/52435 · Cited by 12
Contribuições tecnológicas para saúde: olhar sobre a atividade física
Verzani, R. H., & Serapião, A. B. D. S. (2020) · Ciência & Saúde Coletiva · doi:10.1590/1413-81232020258.19742018 · Cited by 10
Grabowska, W. A., Burton, W. M., Kowalski, M., Vining, R. D., Long, C. R., Lisi, A. J., Hausdorff, J. M., Manor, B. D., Muñoz‐Vergara, D., & Wayne, P. M. (2022) · BMC Musculoskeletal Disorders · doi:10.1186/s12891-022-05783-y · Cited by 10
Multimode optical fiber specklegram smart bed sensor array
Warren-Smith, S. C., Kilpatrick, A. D., Wisal, K., & Nguyen, L. V. (2022) · Journal of Biomedical Optics · doi:10.1117/1.jbo.27.6.067002 · Cited by 10
Hindelang, M., Wecker, H., Biedermann, T., & Zink, A. (2024) · Health Informatics Journal · doi:10.1177/14604582241260607 · Cited by 9
Wireless Communication Security Breaches in Smart Healthcare Applications
Srivastava, S., & Singh, J. (2021) · International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) · doi:10.1109/icac3n53548.2021.9725738 · Cited by 9
Zhang, Y., Ma, Y., & Liang, C. (2024) · Behaviour and Information Technology · doi:10.1080/0144929x.2024.2350674 · Cited by 12
Manetti, S., Vainieri, M., Guidotti, E., Zuccarino, S., Ferré, F., Morelli, M. S., & Emdin, M. (2020) · BMJ Open · doi:10.1136/bmjopen-2020-040738 · Cited by 9
Wearable Ag-NyW textile electrode for continuous ECG monitoring
Srinivasulu, A., Sriraam, N., Prakash, V. S. R., & Sahoo, S. (2021) · Research on Biomedical Engineering · doi:10.1007/s42600-021-00147-2 · Cited by 9
A Network Architecture and Routing Protocol for the MEDIcal WARNing System
Leonardi, L., Bello, L. L., Patti, G., & Ragusa, O. (2021) · Journal of Sensor and Actuator Networks · doi:10.3390/jsan10030044 · Cited by 9
Pro-Con Debate: Universal Versus Selective Continuous Monitoring of Postoperative Patients
Blike, G. T., McGrath, S. P., Kinney, M. A. O., & Gali, B. (2024) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000006840 · Cited by 9
User Experience Study of the Patient Monitoring Systems Based on Usability Testing and Eye Tracking
Choi, H., & Jang, W. S. (2024) · Healthcare · doi:10.3390/healthcare12242573 · Cited by 8
3D-Printed Wearable Sensors for the Identification of Shoulder Movement Planes
Dimo, A., Longo, U. G., d’Hooghe, P. P. R. N., Alessandro de, S. I. R. E., Papalia, R., Schena, E., & Presti, D. L. (2025) · Sensors · doi:10.3390/s25185853 · Cited by 8
Health 4.0, Prevention, and Health Promotion in Companies: A Systematic Literature Review
Domínguez-Miranda, S. A., & Rodríguez-Aguilar, R. (2023) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-031-34750-4_13 · Cited by 9
Domínguez-Miranda, S. A., & Rodríguez-Aguilar, R. (2024) · Iberoamerican Journal of Science Measurement and Communication · doi:10.47909/ijsmc.85 · Cited by 8
Design Considerations in Wearable Technology for Patients with Bipolar Disorder
Tran, T., & Nathan-Roberts, D. (2018) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931218621273 · Cited by 8
Nova, F. F., Pfafman, R., Kardys, K., Kerrigan, C., Guha, S., & Pater, J. A. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555605 · Cited by 7
Pernice, R., Parisi, A., Guarino, S., Fallica, G., Vinciguerra, V., Ferla, G., Faes, L., & Busacca, A. (2020) · IEEE Mediterranean Electrotechnical Conference (MELECON) · doi:10.1109/melecon48756.2020.9140716 · Cited by 7
Amin, A. B., Wang, S., David, U., & Noh, Y. (2022) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc48229.2022.9871998 · Cited by 7
Applications of Artificial Intelligence for Health Informatics: A Systematic Review
Hasan, M. E., Islam, M. J., Islam, R., Chen, D., Sanín, C., & Xu, G. (2023) · Journal of Artificial Intelligence for Medical Sciences · doi:10.55578/joaims.230920.001 · Cited by 10
Characteristics of Future Models of Integrated Outpatient Care
Leviton, A., Oppenheimer, J. E., Chiujdea, M., Antonetty, A., Ojo, O. W., Garcia, S. M., Weas, S., Fleegler, E. W., Chan, E., & Loddenkemper, T. (2019) · Healthcare · doi:10.3390/healthcare7020065 · Cited by 9
The future of artificial intelligence in healthcare
Radakovich, N., & Nazha, A. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-820273-9.00016-6 · Cited by 7
Timinis, C., Opie, J., Watt, S., Rogers, Y., & Drobnjak, I. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714134 · Cited by 8
Patel, V., Moosa, S., Sundaram, S., Langer, L. K., MacMillan, T. E., Cavalcanti, R. B., Cram, P. M., Gunaratne, K., Bayley, M. T., & Wu, R. C. (2022) · Informatics for Health and Social Care · doi:10.1080/17538157.2022.2042304 · Cited by 6
Promoting Engagement in Remote Patient Monitoring Using Asynchronous Messaging
Liaqat, S., Liaqat, D., Son, T., Falk, T. H., Wu, R. C., Gershon, A. S., de Lara, E., & Mariakakis, A. T. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642630 · Cited by 7
Ejdys, J., Czerwińska, M., & Ginevičius, R. (2024) · Human Technology · doi:10.14254/1795-6889.2024.20-1.8 · Cited by 6
Jeyadevan, A., & Grigg, J. (2024) · Current Addiction Reports · doi:10.1007/s40429-024-00587-7 · Cited by 6
Curiello, S., Iannuzzi, E., Meissner, D., & Nigro, C. (2025) · European Journal of Innovation Management · doi:10.1108/ejim-01-2024-0078 · Cited by 7
Caring electronically for young outpatients who have epilepsy
Oppenheimer, J. E., Leviton, A., Chiujdea, M., Antonetty, A., Ojo, O. W., Garcia, S. M., Weas, S., Fleegler, E. W., Chan, E., & Loddenkemper, T. (2018) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2018.06.018 · Cited by 5
Wearable gait analysis systems: ready to be used by medical practitioners in geriatric wards?
Ollenschläger, M., Kluge, F., Müller-Schulz, M., Püllen, R., Möller, C., Klucken, J., & Eskofier, B. M. (2022) · European Geriatric Medicine · doi:10.1007/s41999-022-00629-1 · Cited by 6
Schultz, C. L., Bocarro, J. N., Hipp, J. A., Bennett, G. J., & Floyd, M. F. (2022) · Frontiers in Digital Health · doi:10.3389/fdgth.2022.932533 · Cited by 6
Liappas, N., Teriús-Padrón, J. G., Machado, E., Loghmani, M. R., García-Betances, R. I., Vincze, M., Quero, I. C., & Cabrera-Umpiérrez, M. F. (2019) · IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) · doi:10.1109/smartworld-uic-atc-scalcom-iop-sci.2019.00075 · Cited by 6
Integration of Internet of Things and Cloud Computing for Cardiac Health Recognition
Houssein, E. H., Ibrahim, I. E., Hassaballah, M., & Wazery, Y. M. (2021) · Studies in computational intelligence · doi:10.1007/978-3-030-70542-8_26 · Cited by 6
Cluster-Based Health Monitoring Scheme in Wireless Sensor Networks
Selvakanmani, S., Shanmathi, M., & Sandhya, N. S. (2018) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-030-02674-5_7 · Cited by 6
Jamil, S., Mohammadnezhad, M., Abdulrahim, A., Muhammad, F., & Khan, H. T. A. (2025) · Chronic Diseases and Translational Medicine · doi:10.1002/cdt3.70018 · Cited by 5
Fuhrmann, L. M., Lukas, C. A., Schindler‐Gmelch, L., & Berking, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-06588-4 · Cited by 4
Investigating the Role of Machine Learning in Detecting Psychological Tension
Panicker, S., & Gayathri, P. (2021) · Lecture notes in networks and systems · doi:10.1007/978-981-33-6546-9_32 · Cited by 5
The use of digital health in heart rhythm care
Tchapmi, D. P., Agyingi, C., Egbe, A., Marcus, G. M., & Noubiap, J. J. (2023) · Expert Review of Cardiovascular Therapy · doi:10.1080/14779072.2023.2226868 · Cited by 6
Disease Spread Control in Cruise Ships: Monitoring, Simulation, and Decision Making
Triantafyllou, G., Kalozoumis, P. G., Cholopoulou, E., & Iakovidis, D. K. (2024) · Springer eBooks · doi:10.1007/978-3-031-48831-3_8 · Cited by 5
Temporal variational autoencoder model for in-hospital clinical emergency prediction
Nguyen, T.-N., Kim, S.-H., Kho, B., Do, N.-T., Iyortsuun, N. K., Lee, G.-S., & Yang, H.-J. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106975 · Cited by 6
A digital twin enabled wearable device for customized healthcare
Zhu, Z., & Zhong, R. Y. (2025) · Digital Twin · doi:10.12688/digitaltwin.17717.2 · Cited by 5
Reconfigurable monitoring for telecommunication networks
Tianxing, M., Osipov, V. Y., Vodyaho, A. I., Kalmatskiy, A., Zhukova, N. A., Lebedev, S. V., & Shichkina, Y. A. (2020) · PeerJ Computer Science · doi:10.7717/peerj-cs.288 · Cited by 5
Alloghani, M. A., Subair, S., & Thron, C. (2022) · Studies in computational intelligence · doi:10.1007/978-3-030-92245-0_6 · Cited by 5
Challenges for Deploying IoT Wearable Medical Devices Among the Ageing Population
Xing, F., Peng, G., Liang, T., & Jiang, J. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-91125-0_25 · Cited by 5
Reflexión sobre la evaluación de impacto en eSalud. «No todo lo que brilla es oro»
Agudelo-Londoño, S. (2020) · trilogía Ciencia Tecnología Sociedad · doi:10.22430/21457778.1262 · Cited by 6
Implementing meta-session autoregulation strategies for exercise- a scoping review
Ibrahim, A. H., Beaumont, C. T., & Strohacker, K. A. (2024) · International journal of exercise science · doi:10.70252/dabq1369 · Cited by 4
A Wearable Chest Band Based on a 3-D-Printed FBG Sensor for Cardiorespiratory Monitoring
Presti, D. L., Massaroni, C., & Schena, E. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3612740 · Cited by 4
Xu, T., Liu, C., Li, L., Song, D., Rose, G. M., & Zhu, S. (2026) · Journal of Palliative Medicine · doi:10.1177/10966218261418542 · Cited by 7
Kim, H., Cho, B., Jung, J., & Kim, J. (2023) · Digital Health · doi:10.1177/20552076231218133 · Cited by 4
A digital twin enabled wearable device for customized healthcare
Zhu, Z., & Zhong, R. Y. (2022) · Digital Twin · doi:10.12688/digitaltwin.17717.1 · Cited by 4
Swist, T., Collin, P. J., Lewis, J., Medlow, S., Williams, I., Davies, C., & Steinbeck, K. S. (2023) · Digital Health · doi:10.1177/20552076231212286 · Cited by 5
How Artificial Intelligence Challenges Tailorable Technology Design
Fechner, P., König, F., Lockl, J., & Röglinger, M. (2024) · Business & Information Systems Engineering · doi:10.1007/s12599-024-00872-9 · Cited by 4
A Study of the Awareness of Wearable Medical Devices in India: A Potential Market Perspective
Nanda, S., & Som, B. K. (2018) · Journal of Business Theory and Practice · doi:10.22158/jbtp.v6n2p83 · Cited by 5
Haddad, P. A., Servati, A., Soltanian, S., Servati, P., & Ko, F. (2018) · Textile Research Journal · doi:10.1177/0040517518817060 · Cited by 4
Reliable Healthcare Monitoring System Using SPOC Framework
Ramya, P., Sravanthi, P. N., & Kumar, M. M. (2019) · Lecture notes in networks and systems · doi:10.1007/978-981-13-7082-3_45 · Cited by 4
Metadata
- Authors
- Baig, M. M., GholamHosseini, H., Moqeem, A. A., Mirza, F., & Lindén, M.
- Affiliations
- Auckland University of Technology (NZ)
- Corresponding author
- Baig, Mirza Mansoor
- Venue
- Journal of Medical Systems
- Published
- 2017-06-19
- Volume
- 41
- Issue
- 7
- Pages
- 115-115
- ISSN
- 0148-5598 (ISSN-L)
- 1573-689X
- OpenAlex
- W2625326488
- Cited by
- 351
- References
- 64
- Citations by year
- 2026: 30 · 2025: 52 · 2024: 37 · 2023: 36 · 2022: 38 · 2021: 54 · 2020: 50 · 2019: 27 · 2018: 22 · 2017: 5
- FWCI
- 2.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Medical Systems (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Keywords
- wearable sensors, clinical adoption, interoperability, clinical usability, chronic disease monitoring, rehabilitation, cardiovascular disease, fall detection, mental health monitoring, wireless data collection, communication platforms, machine learning in healthcare, artificial intelligence in healthcare
- MeSH terms
- Artificial Intelligence, Delivery of Health Care, Humans, Monitoring, Physiologic, Software
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