Advertisement

Human-centered approaches that integrate sensor technology across the lifespan: Opportunities and challenges

      ABSTRACT

      Children, parents, older adults, and caregivers routinely use sensor technology as a source of health information and health monitoring. The purpose of this paper is to describe three exemplars of research that used a human-centered approach to engage participants in the development, design, and usability of interventions that integrate technology to promote health. The exemplars are based on current research studies that integrate sensor technology into pediatric, adult, and older adult populations living with a chronic health condition. Lessons learned and considerations for future studies are discussed. Nurses have successfully implemented interventions that use technology to improve health and detect, prevent, and manage diseases in children, families, individuals and communities. Nurses are key stakeholders to inform clinically relevant health monitoring that can support timely and personalized intervention and recommendations.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Nursing Outlook
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Alexander G
        • Rantz M
        • Skubic M
        • Aud MA
        • Wakefield B
        • Florea E
        • Paul A
        Sensor systems for monitoring functional status in assisted living facility residents.
        Research in Gerontological Nursing. 2008; 1: 238
        • American Diabetes Association
        Facilitating behavior change and well-being to improve health outcomes: Standards of Medical Care in Diabetes-2020.
        Diabetes Care. 2020; 43: S48-S65https://doi.org/10.2337/dc20-S005
        • Arsand E
        • Demiris G.
        User-centered methods for designing patient-centric self-help tools.
        Inform Health Social Care. 2008; 33: 158-169
        • Aviel Y
        • Stremler R
        • Benseler SM
        • Cameron B
        • Laxer RM
        • Ota S
        • Feldman BM
        • et al.
        Sleep and fatigue and the relationship to pain, disease activity and quality of life in juvenile idiopathic arthritis and juvenile dermatomyositis.
        Rheumatology. 2011; 50: 2051-2206
        • Backonja U
        • Kneale L
        • Demiris G
        • Thompson HJ
        Senior tech: The next generation: Health informatics solutions for older adults living in the community.
        Journal of Gerontological Nursing. 2016; 42: 2-3
        • Banerjee T
        • Keller J
        • Skubic M
        • Stone E
        Day or night activity recognition from video using fuzzy clustering techniques.
        IEEE Transactions on Fuzzy Systems. 2014; 22: 483-493
        • Banerjee T
        • Keller JM
        • Popescu M
        • Skubic M
        Recognizing complex instrumental activities of daily living using scene information and fuzzy logic.
        Computer Vision and Image Understanding. 2015; 140: 68-82
        • Banerjee T
        • Skubic M
        • Keller JM
        • Abbott CC
        Sit-to-stand measurement for in home monitoring using voxel analysis.
        IEEE Journal of Biomedical and Health Informatics. 2014; 18: 1502-1509
        • Banerjee T
        • Yefimova M
        • Keller J
        • Skubic M
        • Woods DL
        • Rantz M
        Exploratory analysis of older adults’ sedentary behavior in the primary living area using Kinect depth data.
        Journal of Ambient Intelligence and Smart Environments. 2017; 9: 163-179
        • Bekemeier B
        • Park S
        • Backonja U
        • Ornelas I
        • Turner AM
        Data, capacity-building, and training needs to address rural health inequities in the Northwest United States: a qualitative study.
        Journal of American Medical Informatics Association. 2019; 26: 825
        • Bock C
        • Demiris G
        • Choi Y
        • Le T
        • Thompson HJ
        • Samuel A
        • Huang D
        Engaging older adults in the visualization of sensor data facilitated by an open platform for connected devices.
        Technology and Health Care. 2016; 24: 541-550
        • Breitenstein SM
        • Shane J
        • Julion W
        • Gross D
        Developing the eCPP: adapting an evidence-based parent training program for digital delivery in primary care settings.
        Worldviews Evidence Based Nursing. 2015; 12: 31-40
        • Caldwell BA
        • Ordway MR
        • Sadler LS
        • Redeker NS
        Parent perspective on sleep and sleep habits among young children living with economic adversity.
        Journal of Pediatric Health Care. 2019; 34: 10-22
        • Choi YK
        • Demiris G
        • Lin SY
        • Iribarren SJ
        • Landis CA
        • Thompson HJ
        • Ward TM
        Smartphone applications to support sleep self-management: Review and evaluation.
        Journal of Clinical Sleep Medicine. 2018; 14: 1783-1790
        • Demiris G
        • Skubic M
        • Keller J
        • Rantz M
        • Parker Oliver D
        • Aud M
        • Green N
        Nurse Participation in the Design of User Interfaces for a Smart Home System.
        in: Proceedings, International Conference on Smart Homes and Health Telematics, Belfast, N Ireland2006: 66-73
        • DeVito Dabbs A
        • Song MK
        • Myers B
        • Hawkins RP
        • Aubrecht J
        • Begey A
        • Dew MA
        Clinical trials of health information technology interventions intended for patient use: unique issues and considerations.
        Clinical Trials. 2013; 10: 896-906
        • Diaz KM
        • Krupka DJ
        • Chang MJ
        • et al.
        Validation of the Fitbit One® for physical activity measurement at an upper torso attachment site.
        BMC Research Notes. 2016; 9: 213https://doi.org/10.1186/s13104-016-2020-8
        • Dorsey SG
        • Renn CL
        • Griffioen M
        • Lassiter CB
        • Zhu S
        • Huot-Creasy H
        • Starkweather AR
        Whole blood transcriptomic profiles can differentiate vulnerability to chronic low back pain.
        Plos One. 2019; 14 (16)e0216539
        • Eikey EV
        • Reddy MC
        • Kuziemsky CE
        Examining the role of collaboration in studies of health information technologies in biomedical informatics: A systematic review of 25 years of research.
        Journal of Biomedical Informatics. 2015; 57: 263-277
        • Evenson KR
        • Goto MM
        • Furberg RD
        Systematic review of the validity and reliability of consumer-wearable activity trackers.
        International Journal of Behavioural Nutitonalr and Physical Activity. 2015; 12: 159
        • Figueiredo M
        • Caldeira C
        • Chen Y
        • Zheng K
        Routine self-tracking of health: reasons, facilitating factors, and the potential impact on health management practices.
        Amia ... Annual Symposium Proceedings [Electronic Resource]. 2018; 2017 (Published 2018 Apr 16): 706-714
        • Fu MR
        • Kurnat-Thoma E
        • Starkweather A
        • Henderson WA
        • Cashion AK
        • Williams JK
        • Coleman B
        Precision health: A nursing perspective.
        International Journal of Nursing Sciences. 2020; 7: 5-12https://doi.org/10.1016/j.ijnss.2019.12.008
        • Fu MR
        • Wang Y
        • Li C
        • Qiu Z
        • Axelrod D
        • Guth AA
        • Cheung YK
        Machine learning for detection of lymphedema among breast cancer survivors.
        Mhealth. 2018; 4 (29): 17
        • Harvey A.G.
        • Buysse D.J.
        Treating sleep problems: A transdiagnostic approach.
        The Guilford Press, 2018
        • Hickey KT
        • Bakken S
        • Byrne MW
        • Bailey DCE
        • Demiris G
        • Docherty SL
        • Grady PA
        Precision health: Advancing symptom and self-management science.
        Nursing Outlook. 2019; 67: 462-475
        • Jain A
        • Popescu M
        • Keller J
        • Rantz M
        • Markway B
        Linguistic summarization of in-home sensor data.
        Journal of biomedical informatics. 2019; 103240
        • Jiao C
        • Su BY
        • Lyons P
        • Zare A
        • Ho KH
        • Skubic M
        Multiple instance dictionary learning for beat-to-beat heart rate monitoring from Ballistocardiograms.
        IEEE Trans. on Biomedical Engineering. 2018; 65: 2634-2648https://doi.org/10.1109/TBME.2018.2812602
      1. Kearns, W.R., Kaura, N., Divina, M., Vo, C., Si, D., Ward, T.M., & Yuwen, W.A Wizard- of-Oz interface and persona-based methodology for collecting health counseling dialog. Proceedings of the ACM CHI 2020 Conference on Human Factors in Computing Systems. doi: 10.1145/3334480.3382902.

        • Kearns W.R.
        • Kaura N.
        • Divina M.
        • Vo C.
        • Si D.
        • Ward T.M.
        • Yuwen. W
        A Wizard-of-Oz interface and persona-based methodology for collecting health counseling dialog.
        in: Proceedings of the ACM CHI 2020 Conference on Human Factors in Computing Systems. 2020
        • Knisely MR
        • Maserati M
        • Heinsberg LW
        • Shah LL
        • Li H
        • Zhu Y
        • Conley YP
        Symptom Science: Advocating for Inclusion of Functional Genetic Polymorphisms.
        Biological Research for Nursing. 2019; 21: 349-354
      2. Koleck TA, Dreisbach C, Bourne PE, Bakken S Natural language processing of symptoms documented in free-text narratives of electronic health records: A systematic reviewJournal of the American Medical Informatics Association. 2019;26(4):364-379.

        • Law EF
        • Beals-Erickson SE
        • Noel M
        • Claar R
        • Palermo TM
        Pilot randomized controlled trial of internet-delivered cognitive-behavioral treatment for pediatric headache.
        Headache. 2015; 55: 1410-1425
        • Li S
        • Dunlop AL
        • Jones DP
        • Corwin EJ
        High-resolution metabolomics: Review of the field and implications for nursing science and the study of preterm birth.
        Biological Research for Nursing. 2016; 18: 12-22
        • Lorig KR
        • Holman HR
        Self-management education: history, definition, outcomes, and mechanisms.
        Annals of behavioral medicine. 2003; 26: 1-7
        • Maguire R
        • Fox PA
        • McCann L
        • et al.
        The eSMART study protocol: a randomised controlled trial to evaluate electronic symptom management using the advanced symptom management system (ASyMS) remote technology for patients with cancer.
        BMJ Open. 2017; 7 (Published Jun 6, 2017)e015016https://doi.org/10.1136/bmjopen-2016-015016
        • Miller WR
        • Lasiter S
        • Bartlett Ellis R
        • Buelow JM
        Chronic disease self-management: a hybrid concept analysis.
        Nursing Outlook. 2015; 63: 154-161
        • Nastasi BK
        • Varjas K
        • Schensul SL
        • Silva KT
        • Schensul JJ
        • Ratnayake P
        The participatory intervention model: A framework for conceptualizing and promoting intervention acceptability.
        School Psychology Quarterly. 2000; 15: 207-232
        • NCSDR
        The National Center on Sleep Disorders Research (NCSDR) of the National Institutes of Health (NIH).
        1993 (June 10Retrieved from:) (Accessed December 29, 2019)
      3. Omics Nursing Science and education network (n.d). ONSEN. Accessed March 16, 2020 Retrieved from: https://omicsnursingnetwork.net/

        • Owens JA
        • Mindell JA
        Pediatric Insomnia.
        Pediatric Clinics of North America. 2011; 58: 555-569
        • Palermo TM
        • Law EF
        • Fales J
        • Bromberg MH
        • Jessen-Fiddick T
        • Tai G
        Internet-delivered cognitive-behavioral treatment for adolescents with chronic pain and their parents: a randomized controlled multicenter trial.
        Pain. 2016; 157: 174-185
        • Phan K
        • Mobbs RJ.
        Long-term objective physical activity measurements using a wireless accelerometer following minimally invasive transforaminal interbody fusion surgery.
        Asian Spine Journal. 2016; 10: 366-369https://doi.org/10.4184/asj.2016.10.2.366
        • Phillips LJ
        • Deroche C
        • Rantz M
        • Alexander GL
        • Skubic M
        • Despins L.
        • Koopman R
        Using embedded sensors in independent living to predict gait changes and falls.
        Western Journal of Nursing Research. 2016; (published online 7/27/16)
        • Pina LR
        • Sien SW
        • Song C
        • Ward TM
        • Fogarty J
        • Munson SM
        • Kientz J
        DreamCatcher: Exploring how parents and school-age children can track and review sleep information together.
        In Proceedings of the ACM on Human-Computer Interaction. 2020; 4 (CSCW1, Article 46 (May 2020))https://doi.org/10.1145/3392882
        • Popescu M
        • Mahnot A
        Early illness recognition in older adults using in-home monitoring sensors and multiple instance learning.
        Methods of Informatics in Medicine. 2012; 51: 359-367
        • Rantz M
        • Lane K
        • Phillips LJ
        • Despins LA
        • Galambos C
        • Alexander GL
        • Koopman RJ
        • Hicks L
        • Skubic M
        • Miller SJ
        Enhanced RN care coordination with sensor technology: Impact on length of stay and cost in aging in place housing.
        Nursing Outlook. 2015; 63
        • Rantz M.
        Aging in place.
        Nurseweek, Midwest/Heartland Edition. 2003; 4
        • Rantz MJ
        • Phillips LJ
        • Galambos C
        • Lane K
        • Alexander GL
        • Despins L
        • Koopman RJ
        • Skubic M
        • Hicks L
        • Miller S
        • Harris BH
        • Deroche CB
        Randomized trial of intelligent sensor system for early illness alerts in senior housing.
        Journal of American Medical Directors Association. 2017; 18: 860-870
        • Rantz MJ
        • Marek KD
        • Aud M
        • Tyrer HW
        • Skubic M
        • Demiris G
        • Hussam A
        A technology and nursing collaboration to help older adults age in place.
        Nursing Outlook. 2005; 53: 40-45
        • Rantz MJ
        • Phillips L
        • Aud M
        • Popejoy L
        • Marek KD
        • Hicks LL
        • Zaniletti I
        • Miller SJ
        Evaluation of aging in place model with home care services and registered nurse care coordination in senior housing.
        Nursing Outlook. 2011; 59: 37-46
        • Rantz MJ
        • Porter RT
        • Cheshier D
        • Otto D
        • Servey 3rd, CH
        • Johnson RA
        • Taylor G
        TigerPlace, A state- Academic-private project to revolutionize traditional long-term care.
        Journal of Housing For the Elderly. 2008; 22 (Retrieved from): 66-85
        • Rantz MJ
        • Skubic M
        • Alexander G
        • Popescu M
        • Aud M
        • Koopman R
        • Miller S
        "Developing a comprehensive electronic health record to enhance nursing care coordination, use of technology, and research.
        Journal of Gerontological Nursing. 2010; 36: 13-17
        • Rantz MJ
        • Skubic M
        • Alexander GL
        • Aud MA
        • Wakefield BJ
        • Galambos C
        • Miller SJ
        Improving nurse care coordination with technology.
        Computers, Informatics, Nursing. 2010; 28: 325-332
        • Rantz MJ
        • Skubic M
        • Koopman R
        • Phillips L
        • Alexander GL
        • Miller SJ
        Using sensor networks to detect urinary tract infections in older adults.
        in: Proceedings, 13th IEEE International Conference on e-Health Networking, Application, & Services, Columbia, MO2011: 142-149
        • Rantz MJ
        • Skubic M
        • Koopman RJ
        • Alexander G
        • Phillips L
        • Musterman KI
        • Miller SJ
        Automated technology to speed recognition of signs of illness in older adults.
        Journal Gerontological Nursing. 2012; 38: 18-23
        • Rantz MJ
        • Skubic M
        • Miller SJ
        • Krampe J
        Using technology to enhance aging in place.
        in: Proc. of the 6th International Conference on Smart Homes and Health Telematics, Ames, IA2008: 169-176 (July)
        • Rosales L
        • Su Bo-Yu
        • Skubic M
        • Ho KC
        Heart rate estimation from hydraulic bed sensor Ballistocardiogram.
        Journal of Ambient Intelligence and Smart Environments. 2017; 9: 193-207
        • Schnall R.
        • Bakken S.
        • Rojas M
        • Travers J
        • Carballo-Dieguez A
        mHealth Technology as a Persuasive Tool for Treatment, Care and Management of Persons Living with HIV.
        Aids and Behavior. 2015; 19: 81-89https://doi.org/10.1007/s10461-014-0984-8
        • Schuler and Namioka
        2009.
        in: Schuler D. Namioka A. Participatory design principles and practices. CRC Press, Boca Raton, FL2009
        • Shulman RJ
        • Öhman L
        • Stridsberg M
        • Cain K
        • Simrén M
        • Heitkemper M
        Evidence of increased fecal granins in children with irritable bowel syndrome and correlates with symptoms.
        Neurogastroenterology and Motility. 2019; 31: e13486
        • Shyen S
        • Amine B
        • Rostom S
        • E L Badri D
        • Ezzahri M
        • Mawani N
        • Hajjaj-Hassouni N
        Sleep and its relationship to pain, dysfunction, and disease activity in juvenile idiopathic arthritis.
        Clinical Rheumatology. 2014; 33: 1425-1431
        • Siek K
        • Veinot T
        • Mynatt B
        Research opportunities in sociotechnical interventions for health disparity reduction. A computing community consortium.
        2019 (June 2019. Accessed January 14, 2020Retrieved from)
        • Skubic M
        • Alexander G
        • Popescu M
        • Rantz M
        • Keller J
        A smart home application to eldercare: Current status and lessons learned.
        Technology and Health Care. 2009; 17: 183-201
        • Skubic M
        • Guevara RD
        • Rantz M
        Automated health alerts using in-home sensor data for embedded health assessment.
        IEEE Journal of Translational Engineering in Health and Medicine. 2015; 3: 1-11
        • Sorscher AJ.
        How is your sleep: A neglected topic for health care screening.
        Journal of American Board of Family Medicine. 2008; 21: 141-148
        • Starkweather A
        • Jacelon CS
        • Bakken S
        • Barton DL
        • DeVito Dabbs A
        • Dorsey SG
        • Miller JL
        The use of technology to support precision health in nursing science.
        Journal of Nursing Scholarship. 2019; 51: 614-623
        • Stone E
        • Skubic M
        Unobtrusive, continuous, in-home gait measurement using the Microsoft Kinect.
        IEEE Transactions on Biomedical Engineering. 2013; 60: 2925-2932https://doi.org/10.1109/TBME.2013.2266341
        • Stone E
        • Skubic M
        Fall detection in homes of older adults using the Microsoft Kinect.
        IEEE Journal of Biomedical and Health Informatics. 2015; 19: 290-301
        • Stone E
        • Skubic M
        • Rantz M
        • Abbott C
        • Miller S
        Average in-home gait speed: Investigation of a new metric for mobility and fall risk assessment of elders.
        Gait and Posture. 2015; 41: 57-62
        • Stremler R
        • McMurray J
        • Brennenstuhl S
        Self-reported sleep quality and actigraphic measures of sleep in new mothers and the relationship to postpartum depressive symptoms.
        Behavioral Sleep Medicine. 2019; : 1-10
        • Su B-Y
        • Enayati M
        • Ho K-C
        • Skubic M
        • Despins D
        • Keller J
        • Rantz M
        Monitoring the relative blood pressure using a hydraulic bed sensor system.
        IEEE Trans. on Biomedical Engineering. 2019; 66: 740-748https://doi.org/10.1109/TBME.2018.2855639
        • Unertl KM
        • Schaefbauer CL
        • Campbell TR
        • Senteio C
        • Siek KA
        • Bakken S
        • Veinot TC
        Integrating community-based participatory research and informatics approaches to improve the engagement and health of underserved populations.
        Journal of the American Medical Informatics Association. 2016; 23: 60-73
        • Van Blarigan EL
        • Kenfield SA
        • Chan JM
        • Van Loon K
        • Paciorek A
        • Zhang L
        • Venook AP
        Feasibility and acceptability of a web-based dietary intervention with text messages for colorectal cancer: A randomized pilot trial.
        Cancer Epidemiology, Biomarkers & Prevention. 2020; 29: 752-760
        • Veinot TC
        • Ancker JS
        • Cole-Lewis H
        • Mynatt ED
        • Parker AG
        • Siek KA
        • Mamykina L
        Leveling up: On the potential of upstream health informatics interventions to enhance health equity.
        Medical Care. 2019; 57 (Suppl 6 Suppl 2): S108-S114https://doi.org/10.1097/MLR.0000000000001032
        • Veinot TC
        • Mitchell H
        • Ancker JS
        Good intentions are not enough: How informatics interventions can worsen inequality.
        Journal of the American Medical Informatics Association. 2018; 25 (1): 1080-1088https://doi.org/10.1093/jamia/ocy052
        • Vorderstrasse AA
        • Melkus GD
        • Pan W
        • Lewinski AA
        • Johnson CM
        Diabetes learning in virtual environments: Testing the efficacy of self-management training and support in virtual environments (randomized controlled trial protocol).
        Nursing Research. 2015; 64: 485-493
        • Wallace R
        • Abbott C
        • Gibson-Horn C
        • Rantz M
        • Skubic M
        “Metrics from in-home sensor data to assess gait change due to weighted vest therapy.
        Smart Health. 2017; 3-4: 1-19
        • Wang S
        • Skubic M
        • Zhu Y
        Activity density map visualization and dis-similarity comparison for eldercare monitoring.
        IEEE Journal of Biomedical and Health Informatics. 2012; 16: 607-614
        • Ward TM
        • Sonney J
        • Ringold S
        • Stockfish S
        • Wallace CA
        • Landis CA
        Sleep disturbances and behavior problems in children with and without arthritis.
        Journal of Pediatric Nursing. 2014; 29: 321-328
        • Ward TM
        • Yuwen W
        • Voss J
        • Ringold S
        Sleep fragmentation and protein biomarkers in pain in children with juvenile idiopathic arthritis.
        Biological Research for Nursing. 2016; 18: 299-306
        • Ward TM.
        • Rankin S.
        • Lee KA.
        Caring for children with sleep problems.
        Journal of Pediatric Nursing. 2007; 22: 283-296
        • Webel A
        • Prince-Paul M
        • Ganocy S
        • DiFranco E
        • Wellman C
        • Avery A
        • Slomka J
        Randomized clinical trial of a community navigation intervention to improve well-being in persons living with HIV and other co-morbidities.
        Aids Care. 2019; 31: 529-535
        • Whittemore R
        • Jeon S
        • Grey M
        An internet obesity prevention program for adolescents.
        Journal of Adolescent Health. 2013; 52: 439-447https://doi.org/10.1016/j.jadohealth.2012.07.014
        • Yuwen W
        • Backonja B
        • Bromberg MH
        • Garrison MM
        • Ringold S
        • Ward TM
        Usability testing of a web-based intervention for parents to improve sleep in young children with arthritis.
        in: Poster presentation, Pediatric Sleep Medicine Tenth Bi-Annual Conference, Naples, FL2019