IMPACT OF AI IN INTERNET OF MEDICAL THINGS FOR HEALTH CARE DELIVERY

  • Neeta Nathani Associate Professor, Gyan Ganga Institute of Technology and Sciences, Jabalpur (M.P.)
  • Zohaib Hasan Assistant Professor, Gyan Ganga Institute of Technology and Sciences, Jabalpur (M.P.)
Keywords: Artificial Intelligence, Internet Of Things, Internet Of Medical Things

Abstract

The Internet of Things (IoT) is a network of wireless, interconnected, and networked digital devices that can gather, send, and store data without the need for human or computer interaction. The Internet of Things has a lot of promise for expediting and improving health care delivery by proactively predicting health issues and diagnosing, treating, and monitoring patients both in and out of the hospital. Understanding how established and emerging IoT technologies may help health systems deliver safe and effective treatment is becoming increasingly critical. The purpose of this viewpoint paper is to present an overview of existing IoT technology in health care, as well as to describe how IoT devices are improving health service delivery and how IoT technology can alter and disrupt global healthcare in the next decade. The promise of IoT-based health care is explored further to theorize how IoT can increase access to preventative public health services and help us migrate from our existing secondary and tertiary health care systems to a more proactive, continuous, and integrated approach. The intersection of the Internet of Medical Things (IoMT) for patient monitoring and chronic care management and the use of Artificial Intelligence (AI) is becoming more promising than ever as the adoption of telemedicine continues to grow dramatically. Connected devices generate huge volumes of data based on real-time measurements of patient vitals, which is delivered to cloud-based applications that are monitored by medical specialists in virtual contact centres. The policy is applied per-patient, and healthcare providers receive warnings and messages when a patient's heart rate, oxygen level, glucose level, blood pressure, or other measurement reaches a set threshold. Depending on the sort of telemedicine and telehealth platforms in use, this data is tracked and acted upon by specialists who monitor many patients for many different practices, and in other circumstances, this data is sent directly to the provider. AI in healthcare, as well as other crucial technologies are essential for resolving the issue and producing future prosperity.

Downloads

Download data is not yet available.

References

Ashique K, Kaliyadan F, Aurangabadkar SJ. (2015) Clinical photography in dermatology using smartphones: an overview. Indian Dermatol Online J ;6(3):158-163. Retrieved from https://dx.doi.org/10.4103%2F2229-5178.156381 DOI: https://doi.org/10.4103/2229-5178.156381

Baur K, Schättin A, de Bruin ED, Riener R, Duarte JE, Wolf P. (2018) Trends in robot-assisted and virtual reality-assisted neuromuscular therapy: a systematic review of health-related multiplayer games. J Neuroeng Rehabil Nov 19;15(1):107. Retrieved from https://doi.org/10.1186/s12984-018-0449-9 DOI: https://doi.org/10.1186/s12984-018-0449-9

Bhelonde A, Didolkar N, Jangale S, Kulkarni N. (2015) Flexible Wound Assessment System for Diabetic Patient Using Android Smartphone. In: International Conference on Green Computing and Internet of Things. 2015 Presented at: ICGCIoT'15; October 8-10,; Noida, India. Retrieved from https://doi.org/10.1109/ICGCIoT.2015.7380509 DOI: https://doi.org/10.1109/ICGCIoT.2015.7380509

Birckhead B, Khalil C, Liu X, Conovitz S, Rizzo A, (2019) Danovitch I, et al. Recommendations for methodology of virtual reality clinical trials in health care by an international working group: iterative study. JMIR Ment Health Jan 31;6(1):e11973. DOI: https://doi.org/10.2196/11973

Chen HS, Jarrell JT, Carpenter KA, Cohen DS, Huang X. (2019) Blockchain in healthcare: a patient-centered model. Biomed J Sci Tech Res Aug 8;20(3):15017-15022. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6764776/ DOI: https://doi.org/10.26717/BJSTR.2019.20.003448

Chen S, Jones C, Moyle W. (2018) Social robots for depression in older adults: a systematic review. J Nurs Scholarsh Nov;50(6):612-622. Retrieved from https://doi.org/10.1111/jnu.12423 DOI: https://doi.org/10.1111/jnu.12423

Chirico A, Lucidi F, De Laurentiis M, Milanese C, Napoli A, Giordano A. (2016) Virtual reality in health system: beyond entertainment. A mini-review on the efficacy of VR during cancer treatment. J Cell Physiol Feb;231(2):275-287. Retrieved from https://doi.org/10.1002/jcp.25117

Dang LM, Piran MJ, Han D, Min K, Moon H. (2019) A survey on internet of things and cloud computing for healthcare. Electronics Jul 9 ;8(7) :768. Retrieved from https://doi.org/10.3390/electronics8070768 DOI: https://doi.org/10.3390/electronics8070768

Darwish A, Hassanien AE, Elhoseny M, Sangaiah AK, Muhammad K. (2017) The impact of the hybrid platform of internet of things and cloud computing on healthcare systems: opportunities, challenges, and open problems. J Ambient Intell Human Comput Dec 29;10(10):4151-4166. Retrieved from https://doi.org/10.1007/s12652-017-0659-1 DOI: https://doi.org/10.1007/s12652-017-0659-1

De Carvalho M, Dias T, Duchesne M, Nardi A, Appolinario J. (2017) Virtual reality in health system: beyond entertainment. A mini-review on the efficacy of VR during cancer treatment. Behav Sci (Basel) Jul 9;7(3). Retrieved from https://doi.org/10.1002/jcp.25117 DOI: https://doi.org/10.1002/jcp.25117

Dojchinovski D, Ilievski A, Gusev M. (2019) editors. Interactive home healthcare system with integrated voice assistant 2019;. Retrieved from https://doi.org/10.23919/MIPRO.2019.8756983 DOI: https://doi.org/10.23919/MIPRO.2019.8756983

Doryab A, Villalba DK, Chikersal P, Dutcher JM, Tumminia M, Liu X, et al. (2019) Identifying behavioral phenotypes of loneliness and social isolation with passive sensing: statistical analysis, data mining and machine learning of smartphone and FitBit data. JMIR Mhealth Uhealth Jul 24;7(7):e13209. DOI: https://doi.org/10.2196/13209

Eckert M, Volmerg JS, Friedrich CM. (2019) Augmented reality in medicine: systematic and bibliographic review. JMIR Mhealth Uhealth Apr 26;7(4):e10967. DOI: https://doi.org/10.2196/10967

Fisk M, Livingstone A, Pit SW. (2020) Telehealth in the context of covid-19: changing perspectives in Australia, the United Kingdom, and the United States. J Med Internet Res Jun 9;22(6):e19264. DOI: https://doi.org/10.2196/19264

GBD (2017) Disease Injury Incidence Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018 Nov 10; 392(10159):1789-1858. Retrieved from https://doi.org/10.1016/S0140-6736(18)32279-7 DOI: https://doi.org/10.1016/S0140-6736(18)32279-7

Gerup J, Soerensen CB, Dieckmann P. (2020) Augmented reality and mixed reality for healthcare education beyond surgery: an integrative review. Int J Med Educ Jan 18;11:1-18. Retrieved from https://dx.doi.org/10.5116%2Fijme.5e01.eb1a DOI: https://doi.org/10.5116/ijme.5e01.eb1a

Ilievski A, Dojchinovski D, Gusev M. (2019) Interactive Voice Assisted Home Healthcare Systems. In: Proceedings of the 9th Balkan Conference on Informatics. 2019 Presented at: BCI'19; September 26-28,; University of Sofia, Bulgaria. Retrieved from https://doi.org/10.1145/3351556.3351572 DOI: https://doi.org/10.1145/3351556.3351572

Internet of Things (IoT) (2019) in Healthcare. Research Markets.. URL: https://www.medicaldevice-network.com/comment/bringing-internet-things-healthcare/ [accessed 2020-10-02].

Jadczyk T, Kiwic O, Khandwalla RM, Grabowski K, Rudawski S, Magaczewski P, et al. (2019) Feasibility of a voice-enabled automated platform for medical data collection: CardioCube. Int J Med Inform Sep;129:388-393. [CrossRef] [Medline] Retrieved from https://doi.org/10.1016/j.ijmedinf.2019.07.001 DOI: https://doi.org/10.1016/j.ijmedinf.2019.07.001

Kakria P, Tripathi NK, Kitipawang P. (2015) A real-time health monitoring system for remote cardiac patients using smartphone and wearable sensors. Int J Telemed Appl;2015:373474. Retrieved from https://doi.org/10.1155/2015/373474 DOI: https://doi.org/10.1155/2015/373474

Laranjo L, Dunn A, Tong H, Kocaballi A, Chen J, Bashir R, et al. (2018) Conversational agents in healthcare: a systematic review. J Am Med Inform Assoc Sep 1;25(9):1248-1258. Retrieved from https://doi.org/10.1093/jamia/ocy072 DOI: https://doi.org/10.1093/jamia/ocy072

Levine DM, Ouchi K, Blanchfield B, Diamond K, Licurse A, Pu CT, et al. (2018) Hospital-level care at home for acutely ill adults: a pilot randomized controlled trial. J Gen Intern Med May;33(5):729-736. Retrieved from https://doi.org/10.7326/M19-0600 DOI: https://doi.org/10.1007/s11606-018-4307-z

Li S, Xu LD, Zhao S. (2018) 5G internet of things: a survey. J Ind Inf Integration Jun;10:1-9. Retrieved from https://doi.org/10.1016/j.jii.2018.01.005 DOI: https://doi.org/10.1016/j.jii.2018.01.005

Lohse KR, Hilderman CG, Cheung KL, Tatla S, van der Loos HF (2014). Virtual reality therapy for adults post-stroke: a systematic review and meta-analysis exploring virtual environments and commercial games in therapy. PLoS One;9(3):e93318. Retrieved from https://doi.org/10.1371/journal.pone.0093318 DOI: https://doi.org/10.1371/journal.pone.0093318

Majumder S, Chen L, Marinov O, Chen C, Mondal T, Deen MJ. (2018) Noncontact wearable wireless ECG systems for long-term monitoring. IEEE Rev Biomed Eng;11:306-321. Retrieved from https://doi.org/10.1109/RBME.2018.2840336 DOI: https://doi.org/10.1109/RBME.2018.2840336

Merchant R, Szefler SJ, Bender BG, Tuffli M, Barrett MA, Gondalia R, et al. (2018) Impact of a digital health intervention on asthma resource utilization. World Allergy Organ J;11(1):28 [FREE Full text] Retrieved from https://doi.org/10.1186/s40413-018-0209-0 DOI: https://doi.org/10.1186/s40413-018-0209-0

Merchant RK, Inamdar R, Quade RC. (2016) Effectiveness of population health management using the propeller health asthma platform: a randomized clinical trial. J Allergy Clin Immunol Pract;4(3):455-463. https://doi.org/10.1016/j.jaip.2015.11.022 DOI: https://doi.org/10.1016/j.jaip.2015.11.022

Mitchell M, Kan L. (2019) Digital technology and the future of health systems. Health Syst Reform;5(2):113-120. Retrieved from https://doi.org/10.1080/23288604.2019.1583040 DOI: https://doi.org/10.1080/23288604.2019.1583040

Mitchell-Box K, Braun KL. (2012) Fathers' thoughts on breastfeeding and implications for a theory-based intervention. J Obstet Gynecol Neonatal Nurs;41(6):E41-E50. Retrieved from https://doi.org/10.1111/j.1552-6909.2012.01399.x DOI: https://doi.org/10.1111/j.1552-6909.2012.01399.x

Moyle W, Jones C, Cooke M, O'Dwyer S, Sung B, Drummond S. (2013) Social Robots Helping People With Dementia: Assessing Efficacy of Social Robots in the Nursing Home Environment. In: 6th International Conference on Human System Interactions (HSI). Presented at: HSI'13; June 6-8, 2013; Sopot, Poland. Retrieved from https://doi.org/10.1109/HSI.2013.6577887 DOI: https://doi.org/10.1109/HSI.2013.6577887

Naik R, Macey N, West RJ, Godbehere P, Thurston SC, Fox R, et al. (2017) First use of an ingestible sensor to manage uncontrolled blood pressure in primary practice: the UK hypertension registry. J Community Med Health Educ;07(01). DOI: https://doi.org/10.4172/2161-0711.1000506

Nazir S, Ali Y, Ullah N, García-Magariño I. (2019) Internet of things for healthcare using effects of mobile computing: a systematic literature review. Wireless Commun Mobile Comput 2019 Nov 14 ; :1-20. Retrieved from https://doi.org/10.1155/2019/5931315 DOI: https://doi.org/10.1155/2019/5931315

Pan J, McElhannon J. (2018) Future Edge Cloud and Edge Computing for Internet of Things Applications. IEEE Internet Things J Feb;5(1):439-449. Retrieved from https://doi.org/10.1109/JIOT.2017.2767608 DOI: https://doi.org/10.1109/JIOT.2017.2767608

Park YR, Lee E, Na W, Park S, Lee Y, Lee J. (2019) Is blockchain technology suitable for managing personal health records? Mixed-methods study to test feasibility. J Med Internet Res Feb 8;21(2):e12533. DOI: https://doi.org/10.2196/12533

Persky S. (2011) Application of virtual reality methods to obesity prevention and management research. J Diabetes Sci Technol Mar 1;5(2):333-339. Retrieved from https://doi.org/10.1177%2F193229681100500220 DOI: https://doi.org/10.1177/193229681100500220

Plowman R, Peters-Strickland T, Savage G. (2018) Digital medicines clinical review on the safety of tablets with sensors.;17(9):849-852. Retrieved from https://doi.org/10.1080/14740338.2018.1508447 DOI: https://doi.org/10.1080/14740338.2018.1508447

Połap D, Winnicka A, Serwata K, Kęsik K, Woźniak M. (2018) An intelligent system for monitoring skin diseases. Sensors (Basel) Aug 4;18(8). Retrieved from https://doi.org/10.3390/s18082552 DOI: https://doi.org/10.3390/s18082552

Ritschel H, Seiderer A, Janowski K, Aslan I, André E. Drink-O-Mender (2018): An Adaptive Robotic Drink Adviser. In: Proceedings of the 3rd International Workshop on Multisensory Approaches to Human-Food Interaction. Presented at: MHFI'18; October 16, 2018; Boulder, Colorado. Retrieved from https://doi.org/10.1145/3279954.3279957 DOI: https://doi.org/10.1145/3279954.3279957

Saarikko T, Westergren UH, Blomquist T. (2017) The internet of things: are you ready for what’s coming? Bus Horiz Sep ;60(5) :667-676. Retrieved from https://doi.org/10.1016/j.bushor.2017.05.010 DOI: https://doi.org/10.1016/j.bushor.2017.05.010

Sangave NA, Aungst TD, Patel DK. (2019) Smart connected insulin pens, caps, and attachments: a review of the future of diabetes technology. Diabetes Spectr Nov;32(4):378-384. Retrieved from https://doi.org/10.2337/ds18-0069 DOI: https://doi.org/10.2337/ds18-0069

Sethi P, Sarangi S. (2017) Internet of things: architectures, protocols, and applications. J Electric Comput Eng. Retrieved from https://doi.org/10.1155/2017/9324035 DOI: https://doi.org/10.1155/2017/9324035

Shimizu E, Ogawa Y, Yazu H, Aketa N, Yang F, Yamane M, et al. (2019) 'Smart Eye Camera': an innovative technique to evaluate tear film breakup time in a murine dry eye disease model. PLoS One;14(5):e0215130. Retrieved from https://doi.org/10.1371/journal.pone.0215130 DOI: https://doi.org/10.1371/journal.pone.0215130

Sposaro F, Tyson G. (2020:a) iFall: an Android application for fall monitoring and response. (1557-170X (Print)). Retrieved from https://doi.org/10.1109/IEMBS.2009.5334912 DOI: https://doi.org/10.1109/IEMBS.2009.5334912

Tao V, Moy K, Amirfar VA (2016). A little robot with big promise may be future of personalized health care. Pharmacy Today Sep;22(9):38. Retrieved from https://doi.org/10.1016/j.ptdy.2016.08.022 DOI: https://doi.org/10.1016/j.ptdy.2016.08.022

Tashjian VC, Mosadeghi S, Howard AR, Lopez M, Dupuy T, Reid M, et al. (2017) Virtual reality for management of pain in hospitalized patients: results of a controlled trial. JMIR Ment Health Mar 29;4(1):e9. Retrieved from https://doi.org/10.1371/journal.pone.0219115 DOI: https://doi.org/10.2196/mental.7387

Torous J, Jän Myrick K, Rauseo-Ricupero N, Firth J. (2020) Digital mental health and covid-19: using technology today to accelerate the curve on access and quality tomorrow. JMIR Ment Health Mar 26;7(3):e18848. DOI: https://doi.org/10.2196/18848

Van der Putte D, Boumans R, Neerincx M, Rikkert M, de MM (2019). A Social Robot for Autonomous Health Data Acquisition Among Hospitalized Patients: An Exploratory Field Study. In: 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). Presented at: HRI'19; March 11-14, 2019; Daegu, Korea (South), Korea (South). Retrieved from https://doi.org/10.1109/HRI.2019.8673280 DOI: https://doi.org/10.1109/HRI.2019.8673280

Valmaggia LR, Latif L, Kempton MJ, Rus-Calafell M (2016). Virtual reality in the psychological treatment for mental health problems: an systematic review of recent evidence. Psychiatry Res Feb 28;236:189-195. Retrieved from https://doi.org/10.1016/j.psychres.2016.01.015 DOI: https://doi.org/10.1016/j.psychres.2016.01.015

Wan S, Gu Z, Ni Q. (2020) Cognitive computing and wireless communications on the edge for healthcare service robots. Comput Comm Jan;149:99-106. Retrieved from https://doi.org/10.1016/j.comcom.2019.10.012 DOI: https://doi.org/10.1016/j.comcom.2019.10.012

Wu M, Lu T, Ling F, Sun J (2010). Research on the Architecture of Internet of Things. In: 3rd International Conference on Advanced Computer Theory and Engineering. Presented at: ICACTE'10; August 20-22, 2010; Chengdu, China. https://doi.org/10.1109/ICACTE.2010.5579493 DOI: https://doi.org/10.1109/ICACTE.2010.5579493

Ye Q, Zhou J, Wu H. (2020) Using information technology to manage the covid-19 pandemic: development of a technical framework based on practical experience in China. JMIR Med Inform Jun 8;8(6):e19515. DOI: https://doi.org/10.2196/19515

Yin Y, Zeng Y, Chen X, Fan Y. (2016) The internet of things in healthcare : an overview. J Ind Inf Integration Mar;1:3-13. Retrieved from https://doi.org/10.1016/j.jii.2016.03.004 DOI: https://doi.org/10.1016/j.jii.2016.03.004

Published
2021-08-20
How to Cite
NATHANI, N., & Hasan, Z. (2021). IMPACT OF AI IN INTERNET OF MEDICAL THINGS FOR HEALTH CARE DELIVERY. International Journal of Engineering Technologies and Management Research, 8(8), 18-26. https://doi.org/10.29121/ijetmr.v8.i8.2021.1012