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Data management and visualization of wearable medical devices assisted by artificial intelligence

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Abstract

With the development of information technology and artificial intelligence technology, medical wearable devices are becoming more and more intelligent. At the same time, the continuous progress of information technology and artificial intelligence technology also makes intelligent medical wearable devices more and more complex, and the data generated by corresponding medical devices are also more and more huge. To further standardize the health data management of the corresponding wearable medical device monitoring management and improve the user stickiness and intelligence of wearable devices, this paper will study the scientific management and visualization technology of wearable medical device data based on artificial intelligence technology. This paper first analyzes the structure of the data ecosystem based on wearable devices, and constructs the corresponding system on this basis. At the same time, it innovatively proposes the data mining technology combined with the time series cycle mode, and manages and analyzes the corresponding device data based on this technology. At the same time, in the actual data processing process, we pay attention to the data preprocessing technology to realize the compressed storage and management of data size. In the aspect of visualization of wearable device data management, this paper will realize data collection, sending, and receiving display based on Android platform, and realize data cloud storage. In the experimental part, this paper designs a wearable medical device data management and visualization software based on a lung function monitoring tracker. Experimental results show that the corresponding algorithm has obvious advantages.

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References

  • Adeli K (2019) Electronic apps and medical diagnostics data management[J]. Clin Chim Acta 493(4):S742–S743

    Article  Google Scholar 

  • Brodie MA, Pliner EM, Ho A et al (2018) Big data vs accurate data in health research: large-scale physical activity monitoring, smartphones, wearable devices and risk of unconscious bias[J]. Med Hypotheses 119(3):32–36

    Article  Google Scholar 

  • Choi W, Kim SH, Lee W et al (2020) Comparison of continuous ECG monitoring by wearable patch device and conventional telemonitoring device[J]. J Korean Med Sci 35(44):112–130

    Article  Google Scholar 

  • Cook AJ, Lehmann T, Gargiulo GD et al (2015) Open platform, eight-channel, portable bio-potential and activity data logger for wearable medical device development[J]. Electron Lett 51(21):1641–1643

    Article  Google Scholar 

  • Deng W, Shen C, Wang P et al (2021) Continuous fabrication of polyethylene microfibrilar bundles for wearable personal thermal management fabric[J]. Appl Surf Sci 2021(7):149255

    Article  Google Scholar 

  • Ejupi A, Brodie M, Lord SR et al (2016) Wavelet-based sit-to-stand detection and assessment of fall risk in older people using a wearable pendant device[J]. IEEE Trans Biomed Eng 11(2):1602–1607

    Google Scholar 

  • Fearis K, Petrie A (2017) Best practices in early phase medical device development: engineering, prototyping, and the beginnings of a quality management system[J]. Surgery 161(3):571–575

    Article  Google Scholar 

  • Gu B, He M, Yang D et al (2020) Wearable Janus MnO2 hybrid membranes for thermal comfort management applications[J]. Appl Surf Sci 509(4):145170

    Article  Google Scholar 

  • Khan Y, Ostfeld AE, Lochner CM et al (2016) Monitoring of vital signs with flexible and wearable medical devices[J]. Adv Mater 28(22):11–19

    Google Scholar 

  • King Rachel C et al (2017) Application of data fusion techniques and technologies for wearable health monitoring[J]. Med Eng Physics 14(6):41–52

    Google Scholar 

  • Li YQ (2016) Multifunctional wearable device based on flexible and conductive carbon sponge/polydimethylsiloxane composite[J]. ACS Appl Mater Interfaces 05:33189–33196

    Article  Google Scholar 

  • Min SD, Wang CW, Lee HM et al (2018) A low cost wearable wireless sensing system for paretic hand management after stroke[J]. J Supercomput 74(10):5231–5240

    Article  Google Scholar 

  • Miyaji T, Kawaguchi T, Azuma K et al (2018) Feasibility trial of collecting patient-generated health data using a wearable device and electronic patient-reported outcomes in cancer patients[J]. J Clin Oncol 36(15):e18725–e18725

    Article  Google Scholar 

  • Miyaji T, Kawaguchi T, Azuma K et al (2020) Patient-generated health data collection using a wearable activity tracker in cancer patients—a feasibility study[J]. Support Care Cancer 28(10):31–42

    Google Scholar 

  • Moulaei K, Malek M, Sheikhtaheri A (2021) A smart wearable device for monitoring and self-management of diabetic foot: a proof of concept study[J]. Internat J Med Inform 146(5):104343

    Article  Google Scholar 

  • Muzny M, Henriksen A, Giordanengo A et al (2020) Wearable sensors with possibilities for data exchange: analyzing status and needs of different actors in mobile health monitoring systems[J]. Internat J Med Inform 133(11):1040171–1040178

    Google Scholar 

  • Odom NR, Lindmar JM, Hirt J et al (2019) Forensic inspection of sensitive user data and artifacts from smartwatch wearable devices[J]. J Forensic Sci 64(6):1673–1686

    Article  Google Scholar 

  • Pattinson SW, Huber ME, Kim S et al (2019) Additive manufacturing: additive manufacturing of biomechanically tailored meshes for compliant wearable and implantable devices (Adv Funct Mater 32/2019)[J]. Adv Funct Mater 29(32):21–32

    Google Scholar 

  • Sathyanarayana A, Srivastava J, Fernandez-Luque L (2017) The science of sweet dreams: predicting sleep efficiency from wearable device data[J]. Computer 50(3):30–38

    Article  Google Scholar 

  • Schumacher J, Vandecreek D (2015) Intellectual capital at risk: data management practices and data loss by faculty members at five American Universities[J]. J Anim Sci 10(2):601–610

    Google Scholar 

  • Wu J, Li H, Lin Z et al (2017) How big data and analytics reshape the wearable device market - the context of e-health[J]. Int J Prod Res 55(17–18):5168–5182

    Article  Google Scholar 

  • Yilmaz M (2019) Easy pre/post-processing of finite elements with custom symbolic-objects: a self-expressive Python interface[J]. Comput Struct 222(10):82–97

    Article  Google Scholar 

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Correspondence to Meizhi Zhao.

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Zhao, M., Wang, D. & Li, J. Data management and visualization of wearable medical devices assisted by artificial intelligence. Netw Model Anal Health Inform Bioinforma 10, 53 (2021). https://doi.org/10.1007/s13721-021-00328-0

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  • DOI: https://doi.org/10.1007/s13721-021-00328-0

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