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A Systematic Review of Wearable Patient Monitoring Systems – Current Challenges and Opportunities for Clinical Adoption

  • Mobile & Wireless Health
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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.

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References

  1. Eaton, S., Roberts, S., and Turner, B., Delivering person centred care in long term conditions. BMJ. 350:h181, 2015.

    Article  PubMed  Google Scholar 

  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.

    Google Scholar 

  3. Sidhu, M. S., et al., Long-term conditions, self-management and systems of support: An exploration of health beliefs and practices within the Sikh community, Birmingham, UK. Ethn. Health :1–17, 2016.

  4. Sabesan, S., and Sankar, R., Improving long-term management of epilepsy using a wearable multimodal seizure detection system. Epilepsy Behav. 46:56–57, 2015.

    Article  Google Scholar 

  5. Paradiso, R., et al., WEALTHY-a wearable healthcare system: new frontier on e-textile. J. Telecommun. Inf. Technol. :105–113, 2005.

  6. Pantelopoulos, A., and Bourbakis, N.G., A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 40(1):1–12, 2010.

    Article  Google Scholar 

  7. Penders, J., et al., Human++: Emerging technology for body area networks. In: VLSI-SoC: Research Trends in VLSI and Systems on Chip. Springer, pp. 377–397, 2008.

  8. Malan, D., et al. Codeblue: An ad hoc sensor network infrastructure for emergency medical care. In International workshop on wearable and implantable body sensor networks. Boston, MA, 2004.

  9. Sung, M., Marci, C., and Pentland, A., Wearable feedback systems for rehabilitation. J. Neuroeng. Rehabil. 2(1):17, 2005.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Pandian, P., et al., Smart vest: Wearable multi-parameter remote physiological monitoring system. Med. Eng. Phys. 30(4):466–477, 2008.

    Article  CAS  PubMed  Google Scholar 

  11. Sardini, E., Serpelloni, M., and Pasqui, V., Wireless wearable T-shirt for posture monitoring during rehabilitation exercises. IEEE Trans. Instrum. Meas. 64(2):439–448, 2015.

    Article  Google Scholar 

  12. Soh, P.J., et al., Wearable wireless health monitoring: Current developments, challenges, and future trends. IEEE Microw. Mag. 16(4):55–70, 2015.

    Article  Google Scholar 

  13. Xu, J., et al., Personalized active learning for activity classification using wireless wearable sensors. IEEE J. Sel. Top. Sign. Proces. 10(5):865–876, 2016.

    Article  Google Scholar 

  14. Pantelopoulos, A., and Bourbakis, N., Design of the new prognosis wearable system-prototype for health monitoring of people at risk. In: Advances in Biomedical Sensing, Measurements, Instrumentation and Systems. Springer, pp. 29–42, 2010.

  15. Patel, S., et al., A review of wearable sensors and systems with application in rehabilitation. J. Neuroeng. Rehabil. 9(1):21, 2012.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Baig, M.M., Gholamhosseini, H., and Connolly, M.J., A comprehensive survey of wearable and wireless ECG monitoring systems for older adults. Med. Biol. Eng. Comput. 51(5):485–495, 2013.

    Article  PubMed  Google Scholar 

  17. Banaee, H., Ahmed, M.U., and Loutfi, A., Data mining for wearable sensors in health monitoring systems: A review of recent trends and challenges. Sensors. 13(12):17472–17500, 2013.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Baig, M.M., and Gholamhosseini, H., Smart health monitoring systems: An overview of design and modeling. J. Med. Syst. 37(2):9898, 2013.

    Article  PubMed  Google Scholar 

  19. Moher, D., et al., Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Ann. Intern. Med. 151(4):264–269, 2009.

    Article  PubMed  Google Scholar 

  20. Etemadi, M., et al., A wearable patch to enable long-term monitoring of environmental, activity and hemodynamics variables. IEEE Trans. Biomed. Circuits Syst. 10(2):280–288, 2016.

    Article  PubMed  Google Scholar 

  21. Thomas, S.S., et al., BioWatch: A noninvasive wrist-based blood pressure monitor that incorporates training techniques for posture and subject variability. IEEE J. Biomed. Health Inform. 20(5):1291–1300, 2016.

    Article  PubMed  Google Scholar 

  22. Wu, W., et al., Assessment of biofeedback training for emotion management through wearable textile physiological monitoring system. IEEE Sensors J. 15(12):7087–7095, 2015.

    Article  Google Scholar 

  23. Span, E., et al., Low-power wearable ECG monitoring system for multiple-patient remote monitoring. IEEE Sensors J. 16(13):5452–5462, 2016.

    Article  Google Scholar 

  24. Chia, A.R., et al., A vegetable, fruit, and white rice dietary pattern during pregnancy is associated with a lower risk of preterm birth and larger birth size in a multiethnic Asian cohort: The Growing Up in Singapore Towards Healthy Outcomes (GUSTO) cohort study. Am. J. Clin. Nutr. 104(5):1416–1423, 2016.

    Article  CAS  PubMed  Google Scholar 

  25. Melillo, P., et al., Cloud-based smart health monitoring system for automatic cardiovascular and fall risk assessment in hypertensive patients. J. Med. Syst. 39(10):1–7, 2015.

    Article  Google Scholar 

  26. Andreu-Perez, J., et al., From wearable sensors to smart implants-–toward pervasive and personalized healthcare. IEEE Trans. Biomed. Eng. 62(12):2750–2762, 2015.

    Article  PubMed  Google Scholar 

  27. Lanata, A., et al., Complexity index from a personalized wearable monitoring system for assessing remission in mental health. IEEE J. Biomed. Health. Inform. 19(1):132–139, 2015.

    Article  PubMed  Google Scholar 

  28. Doty, T. J., et al., The wearable multimodal monitoring system: A platform to study falls and near-falls in the real-world. In: International Conference on Human Aspects of IT for the Aged Population. Springer, 2015.

  29. Saleem, K., et al., Design and deployment challenges in immersive and wearable technologies. Behav. Inform. Technol. :1–12, 2017.

  30. Kakria, P., Tripathi, N., and Kitipawang, P., A real-time health monitoring system for remote cardiac patients using smartphone and wearable sensors. Int. J. Telemed. Appl. 2015, 2015.

  31. Sanfilippo, F., and Pettersen, K., A sensor fusion wearable health-monitoring system with haptic feedback. in 11th International Conference on Innovations in Information Technology (IIT). IEEE, 2015.

  32. Mukhopadhyay, S.C., Wearable sensors for human activity monitoring: A review. IEEE Sensors J. 15(3):1321–1330, 2015.

    Article  Google Scholar 

  33. Deshmukh, S. D., and Shilaskar, S. N., Wearable sensors and patient monitoring system: a review. in International Conference on Pervasive Computing (ICPC). IEEE, 2015.

  34. Kumari, P., Mathew, L., and Syal, P., Increasing trend of wearables and multimodal interface for human activity monitoring: A review. Biosens. Bioelectron. 90:298–307, 2017.

    Article  CAS  PubMed  Google Scholar 

  35. Raja, K., et al., Design of a low power ECG signal processor for wearable health system-review and implementation issues. In: Intelligent Systems and Control (ISCO), 2017 11th International Conference on. IEEE, 2017.

  36. Kaappa, E.S., et al., The electrical impedance measurements of dry electrode materials for the ECG measuring after repeated washing. Res. J. Text. Appar. 21(1):59–71, 2017.

    Article  Google Scholar 

  37. Martin, T., Jovanov, E., and Raskovic, D., Issues in wearable computing for medical monitoring applications: A case study of a wearable ECG monitoring device. In: Wearable Computers, The Fourth International Symposium on. IEEE, 2000.

  38. Milenković, A., Otto, C., and Jovanov, E., Wireless sensor networks for personal health monitoring: Issues and an implementation. Comput. Commun. 29(13):2521–2533, 2006.

    Article  Google Scholar 

  39. Rault, T., et al., A survey of energy-efficient context recognition systems using wearable sensors for healthcare applications. Pervasive Mob. Comput. 37:23–44, 2017.

    Article  Google Scholar 

  40. Wu, J., et al., The Promising Future of Healthcare Services: When big data analytics meets wearable technology. Inf. Manag. 2016.

  41. Ribeiro, J., Wearable Technology Spending: A Strategic Approach to Decision-Making. In: Wearable Technology and Mobile Innovations for Next-Generation Education, p. 37, 2016.

  42. Honggang, W., et al., Resource-aware secure ECG healthcare monitoring through body sensor networks. Wirel Commun, IEEE. 17(1):12–19, 2010.

    Article  Google Scholar 

  43. Michard, F., A sneak peek into digital innovations and wearable sensors for cardiac monitoring. J. Clin. Monit. Comput.:1–7, 2016.

  44. Lee, W., Yoon, H., and Park, K., Smart ECG Monitoring Patch with Built-in R-Peak Detection for Long-Term HRV Analysis. Ann. Biomed. Eng. :1–10, 2016.

  45. Iqbal, M.H., et al., A review of wearable technology in medicine. J. R. Soc. Med. 109(10):372–380, 2016.

    Article  PubMed  Google Scholar 

  46. Kyriazakos, S., et al., eWALL: An intelligent caring home environment offering personalized context-aware applications based on advanced sensing. Wirel. Pers. Commun. 87(3):1093–1111, 2016.

    Article  Google Scholar 

  47. Prakash, R., Ganesh, A.B., and Sivabalan, S., Network coded cooperative communication in a real-time wireless hospital sensor network. J. Med. Syst. 41(5):72, 2017.

    Article  CAS  PubMed  Google Scholar 

  48. Kyungtae, K., et al., A medical-grade wireless architecture for remote electrocardiography. IEEE Trans. Inf. Technol. Biomed. 15(2):260–267, 2011.

    Article  Google Scholar 

  49. Araújo, F.H., Santana, A.M., and Neto, P.d.A.S., Using machine learning to support healthcare professionals in making preauthorisation decisions. Int. J. Med. Inform. 94:1–7, 2016.

  50. Elsebakhi, E., et al., Large-scale machine learning based on functional networks for biomedical big data with high performance computing platforms. J. Comput. Sci. 11:69–81, 2015.

    Article  Google Scholar 

  51. Miller, R. A., Diagnostic decision support systems, In: Clinical decision support systems. Springer, pp. 181–208, 2016.

  52. Berner, E. S. and La Lande, T. J., Overview of clinical decision support systems, In: Clinical decision support systems, Springer, pp. 1–17, 2016.

  53. Wright, A., et al., Analysis of clinical decision support system malfunctions: a case series and survey. J. Am. Med. Inform. Assoc. :ocw005, 2016.

  54. Baig, M. M., Hosseini, H. G., and Lindén, M., Machine learning-based clinical decision support system for early diagnosis from real-time physiological data. In: Region 10 Conference (TENCON), 2016 IEEE. IEEE, 2016.

  55. Price-Haywood, E. G., et al., eHealth literacy: Patient engagement in identifying strategies to encourage use of patient portals among older adults. Popul. Health Manag., 2017.

  56. Davis, S., et al., Shared decision-making using personal health record technology: A scoping review at the crossroads. J. Am. Med. Inform. Assoc., 2017.

  57. Milani, R. V., and Franklin, N. C., The role of Technology in Healthy Living Medicine. Prog. Cardiovasc. Dis., 2017.

  58. Park, E., et al., Understanding the emergence of wearable devices as next-generation tools for health communication. Inf. Technol. People. 29(4):717–732, 2016.

    Article  Google Scholar 

  59. Wu, J., et al., The promising future of healthcare services: When big data analytics meets wearable technology. Inf. Manag. 53(8):1020–1033, 2016.

    Article  Google Scholar 

  60. Rupp, M. A., et al., The impact of technological trust and self-determined motivation on intentions to use wearable fitness technology. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. SAGE Publications, 2016.

  61. Jolicoeur, M., Novel Vitality Indices Derived From the Hexoskin in Patients Affected With Angina Undergoing Coronary Revascularization or Medical Therapy (NOVA-SKIN). [Cinical Trial] [cited 2016 15 October 2016], 2016. Available from: https://clinicaltrials.gov/ct2/show/NCT02591758?term=hexoskin&rank=1.

  62. (Hexoskin), C.T.i. Key Metrics delivered by Hexoskin, 2016, Available from: http://www.hexoskin.com/pages/key-metrics-delivered-by-hexoskin.

  63. Bergmann, J., and McGregor, A., Body-worn sensor design: What do patients and clinicians want? Ann. Biomed. Eng. 39(9):2299–2312, 2011.

    Article  CAS  PubMed  Google Scholar 

  64. Yang, Z., et al., An IoT-cloud based wearable ECG monitoring system for smart healthcare. J. Med. Syst. 40(12):286, 2016.

    Article  PubMed  Google Scholar 

  65. Kurien, M., Trott, N., and Sanders, D., Long-term care for patients with coeliac disease in the UK: A review of the literature and future directions. J. Hum. Nutr. Diet., 2016.

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Authors and Affiliations

  1. School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland, 1142, New Zealand

    Mirza Mansoor Baig, Hamid GholamHosseini, Aasia A. Moqeem & Farhaan Mirza

  2. School of Innovation Design and Engineering, Mälardalen University, Västerås, Sweden

    Maria Lindén

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  1. Mirza Mansoor Baig
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  2. Hamid GholamHosseini
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  3. Aasia A. Moqeem
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Correspondence to Mirza Mansoor Baig.

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Baig, M.M., GholamHosseini, H., Moqeem, A.A. et al. A Systematic Review of Wearable Patient Monitoring Systems – Current Challenges and Opportunities for Clinical Adoption. J Med Syst 41, 115 (2017). https://doi.org/10.1007/s10916-017-0760-1

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