Abstract
This systematic review classifies smartwatch-based healthcare applications in the literature according to their application and summarizes what has led to feasible systems. To this end, we conducted a systematic review of peer-reviewed smartwatch studies related to health care by searching PubMed, EBSCOHost, Springer, Elsevier, Pro-Quest, IEEE Xplore, and ACM Digital Library databases to find articles between 1998 and 2016. Inclusion criteria were as follows: (1) a smartwatch was used, (2) the study was related to a healthcare application, (3) the study was a randomized controlled trial or pilot study, and (4) the study included human participant testing. Each article was evaluated in terms of its application, population type, setting, study size, study type, and features relevant to the smartwatch technology. After screening 1119 articles, 27 articles were chosen that were directly related to health care. Classified applications included activity monitoring, chronic disease self-management, nursing or home-based care, and healthcare education. All studies were considered feasibility or usability studies, and had limited sample sizes. No randomized clinical trials were found. Also, most studies utilized Android-based smartwatches over Tizen, custom-built, or iOS-based smartwatches, and many relied on the use of the accelerometer and inertial sensors to elucidate physical activities. The results show that most research on smartwatches has been conducted only as feasibility studies for chronic disease self-management. Specifically, these applications targeted various disease conditions whose symptoms can easily be measured by inertial sensors, such as seizures or gait disturbances. In conclusion, although smartwatches show promise in health care, significant research on much larger populations is necessary to determine their acceptability and effectiveness in these applications.
Similar content being viewed by others
References
Lu TC, Fu CM, Ma MM, Fang CC, Turner AM (2016) Healthcare applications of smart watches. Appl Clin Inform 7(3):850–869
Glowacki EM, Zhu Y, Hunt E (2016) Magsamen-Conrad K, Bernhardt JM Facilitators and barriers to smartwatch use among individuals with chronic diseases: a qualitative study. University of Texas, Austin
Reeder B, David A (2016) Health at hand: a systematic review of smart watch uses for health and wellness. J Biomed Eng Inform 63:269–276
James DC, Harville C (2015) Barriers and motivators to participating in mHealth research among African American men. Am J Mens Health. https://doi.org/10.1177/1557988315620276
De Jongh T, Gurol-Urganci I, Vodopivec-Jamsek V, Car J, Atun R (2012) Mobile phone messaging for facilitating self-management of long-term illnesses. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.CD007459.pub2
Whittaker R, McRobbie H, Bullen C, Rodgers A, Gu Y (2009) Mobile phone-based interventions for smoking cessation. Cochrane Database Syst Rev 4(4):CD006611. https://doi.org/10.1002/14651858.CD006611.pub2
Smith C, Gold J, Ngo TD, Sumpter C, Free C (2015) Mobile phone-based interventions for improving contraception use. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.CD011159.pub2
Fisher E, Law E, Palermo TM, Eccleston C (2015) Psychological therapies (remotely delivered) for the management of chronic and recurrent pain in children and adolescents. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.CD011118.pub2
Marcano Belisario JS, Jamsek J, Huckvale K, O'Donoghue J, Morrison CP, Car J (2015) Comparison of self-administered survey questionnaire responses collected using mobile apps versus other methods. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.MR000042.pub2
Ozdalga E, Ozdalga A, Ahuja N (2012) The smartphone in medicine: a review of current and potential use among physicians and students. JMIR 14(5):e128. https://doi.org/10.2196/jmir.1994
Webb T, Joseph J, Yardley L, Michie S (2010) Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. JMIR. 12(1):e4. https://doi.org/10.2196/jmir.1376
Phillips G, Felix L, Galli L, Patel V, Edwards P (2010) The effectiveness of mhealth technologies for improving health and health services: a systematic review protocol. BMC Res Notes 3(1):250
Dunton GF, Liao Y, Intille SS, Spruijt-Metz D, Pentz M (2011) Investigating children’s physical activity and sedentary behavior using ecological momentary assessment with mobile phones. Obesity 19(6):1205–1212. https://doi.org/10.1038/oby.2010.302
Ehrler F, Lovis C (2014) Supporting elderly homecare with smartwatches: advantages and drawbacks. Stud Health Technol Inform 205:667–671
Mann S Wristwatch-based videoconferencing system. http://brevets-patents.ic.gc.ca/opic-cipo/cpd/eng/patent/2275784/summary.html?type=number_search&tabs1Index=tabs1_1. Accessed 11 January 2017
Kastrenakes J (2015) Apple Watch release date is April 24th, with pricing from $349 to over $10,000 (March 2015). https://www.theverge.com/2015/3/9/8162455/apple-watch-price-release-date-2015. Accessed 4 August 2017
Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, Schünemann HJ (2008) GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ, pp 336–924. http://www.ebcp.com.br/simple/upfiles/pdfs/2009BrozekPart1.pdf. Accessed 19 July 2016
Gutierrez MA, Fast ML, Ngu AH, Gao BJ (2015) Real-time prediction of blood alcohol content using smartwatch sensor data. In Proc ICSH, pp 175–186. https://link.springer.com/chapter/10.1007/978-3-319-29175-8_16. Accessed 19 July 2016
Iakovakis DE, Papadopoulou FA, Hadjileontiadis LJ (2016) Fuzzy logic-based risk of fall estimation using smartwatch data as a means to form an assistive feedback mechanism in everyday living activities. Healthc Technol Lett 3(4):263–268. https://doi.org/10.1049/htl.2016.0064
Kelling C, Pitaro D, Rantala J (2016) Good vibes: the impact of haptic patterns on stress levels. In Proc Academic Mindtrek Conference, pp 130–136. https://dl.acm.org/citation.cfm?id=2994368. Accessed 6 July 2016
Moder T, Wisiol K, Wieser M (2016 Walking aid identification using wearables. In Proc Comut Help People Spec Needs, pp 335–341. https://link.springer.com/chapter/10.1007/978-3-319-41264-1_46. Accessed 19 August 2016
Prange A, Sonntag D (2015) Easy deployment of spoken dialogue technology on smartwatches for mental healthcare. In Proc Pervasive Computing Paradigms for Mental Health, pp 150–156. https://link.springer.com/chapter/10.1007/978-3-319-32270-4_15. Accessed 19 July 2016
Berrocal J, Garcia-Alonso J, Murillo J, Canal C (2017) Rich contextual information for monitoring the elderly in an early stage of cognitive impairment. Pervasive Mob Comput 34:106–125. http://www.sciencedirect.com/science/article/pii/S1574119216300499. Accessed 19 August 2016
Blaauw F, Schenk H, Jeronimus B, van der Krieke L, de Jonge P, Aiello M (2016) Let’s get physiqual—an intuitive and generic method to combine sensor technology with ecological momentary assessments. J Bioed Eng Inform 63:141–149
Lockman J, Fisher RS, Olson DM (2011) Detection of seizure-like movements using a wrist accelerometer. Epilepsy Behav 20(4):638–641. https://doi.org/10.1016/j.yebeh.2011.01.019
Lopez WOC, Higuera CAE, Fonoff ET, de Oliveira Souza C, Albicker U, Martinez JAE (2014) Listenmee and listenmee smartphone application: synchronizing walking to rhythmic auditory cues to improve gait in Parkinson’s disease. Hum Mov Sci 37:147–156. https://doi.org/10.1016/j.humov.2014.08.001
Sharma V, Mankodiya K, De La Torre F, Zhang A, Ryan N, Ton TG, Gandhi R, Jain S (2014) SPARK: personalized Parkinson disease interventions through synergy between a smartphone and a smartwatch. In Proc The Design, User Experience, and Usability: User Experience Design for Everyday Life Applications and Services. 103–114, https://doi.org/10.1007/978-3-319-07635-5_11
Chippendale P, Tomaselli V, DAlto V, Urlini G, Modena CM, Messelodi S, Strano SM, Alce G, Hermodsson K, Razafimahazo M, Michel T (2014) Personal shopping assistance and navigator system for visually impaired people. In Proc Comput Vis ECCV, pp 375–390. https://hal.inria.fr/hal-01102707/. Accessed 19 July 2016
Årsand E, Muzny M, Bradway M, Muzik J, Hartvigsen G (2015) Performance of the first combined smartwatch and smartphone diabetes diary application study. J Diabetes Sci Technol 9(3):556–563. https://doi.org/10.1177/1932296814567708
Mortazavi B, Nemati E, VanderWall K, Flores-Rodriguez HG, Cai JYJ, Lucier J, Naeim A, Sarrafzadeh M (2015) Can smartwatches replace smartphones for posture tracking? Sensors 15(10):26783–26800. https://doi.org/10.3390/s151026783
Boletsis C, McCallum S, Landmark BF (2015) The use of smartwatches for health monitoring in home-based dementia care. In Proc Conf Hum Aspects IT Aged Pop, pp 15–26.https://link.springer.com/chapter/10.1007/978-3-319-20913-5_2. Accessed 19 July 2016
Faye S, Frank R, Engel T (2015) Adaptive activity and context recognition using multimodal sensors in smart devices. In Proc MobiCase, pp 33–50. https://link.springer.com/chapter/10.1007/978-3-319-29003-4_3. Accessed 6 July 2016
Haescher M, Trimpop J, Matthies DJ, Bieber G, Urban B, Kirste T (2015) aHead: considering the head position in a multi-sensory setup of wearables to recognize everyday activities with intelligent sensor fusions. In Proc Mobile HCI, pp 741–752. https://link.springer.com/chapter/10.1007/978-3-319-20916-6_68. Accessed 19 July 2016
Jeong Y, Chee Y, Song Y, Koo K (2015) Smartwatch app as the chest compression depth feedback device. In Proc World Congress on Medical Physics and Biomedical Engineering, pp 1465–1468. https://link.springer.com/chapter/10.1007/978-3-319-19387-8_357. Accessed 19 July 2016
Panagopoulos C, Kalatha E, Tsanakas P, Maglogiannis I (2015) Evaluation of a mobile home care platform. In Proc ECAI, pp 328–343. https://link.springer.com/chapter/10.1007/978-3-319-26005-1_22. Accessed 18 July 2016
Neto LdSB, Maike VRML, Koch FL, Baranauskas MCC, de Rezende Rocha A, Goldenstein SK (2015) A wearable face recognition system built into a smartwatch and the blind and low vision users. In Proc ICEIS, pp 515–528. https://link.springer.com/chapter/10.1007/978-3-319-29133-8_25. Accessed 19 August 2017
Kalantarian H, Sarrafzadeh M (2015) Audio-based detection and evaluation of eating behavior using the smartwatch platform. Comput Biol Med 65:1–9. https://doi.org/10.1016/j.compbiomed.2015.07.013
Vilarinho T, Farshchian B, Bajer DG, Dahl OH, Egge I, Hegdal SS, Lønes A, Slettevold JN, Weggersen SM (2015) A combined smartphone and smartwatch fall detection system. In Proc IEEE Int Conf CIT UCC DASC PICOM, pp 1443–1448. http://ieeexplore.ieee.org/abstract/document/7363260/?reload=true. Accessed 28 July 2016
Dubey H, Goldberg JC, Mankodiya K, Mahler L (2015) A multi-smartwatch system for assessing speech characteristics of people with dysarthria in group settings. In Proc Int Conf HealthCom, pp 528–533. http://ieeexplore.ieee.org/abstract/document/7454559/. Accessed 6 July 2016
Dubey H, Goldberg JC, Abtahi M, Mahler L, Mankodiya K (2015) EchoWear: smartwatch technology for voice and speech treatments of patients with Parkinson’s disease. Proc Wireless Health. 15:1–15 8
Thomaz E, Essa I, Abowd GD (2015) A practical approach for recognizing eating moments with wrist-mounted inertial sensing. In Proc 2015 ACM UbiComp, pp 1029–1040. https://dl.acm.org/citation.cfm?id=2807545. Accessed 6 July 2016
Ali H, Li H (2016) Designing a smart watch interface for a notification and communication system for nursing homes. In Proc Conf Hum Aspects IT Aged Pop, pp 401–411. https://link.springer.com/chapter/10.1007/978-3-319-39943-0_39. Accessed 19 July 2016
Banos O, Amin MB, Khan WA, Afzal M, Hussain M, Kang BH, Lee S (2016) The mining minds digital health and wellness framework. Biomed Eng Online 15(Suppl. 1):S76
Duclos M, Fleury G, Lacomme P, Phan R, Ren L, Rousset S (2016) An acceleration vector variance based method for energy expenditure estimation in real-life environment with a smartphone/smartwatch integration. Expert Syst Appl 63:435–449. https://doi.org/10.1016/j.eswa.2016.07.021
Velez M, Fisher RS, Bartlett V, Le S (2016) Tracking generalized tonic-clonic seizures with a wrist accelerometer linked to an online database. Seizure 39:13–18. https://doi.org/10.1016/j.seizure.2016.04.009
Hosseini A, Buonocore CM, Hashemzadeh S, Hojaiji H, Kalantarian H, Sideris C, Bui AA, King CE, Sarrafzadeh M (2016) Hipaa compliant wireless sensing smartwatch application for the self-management of pediatric asthma. In Proc 2016 I.E. Int Conf BSN, pp 49–54. http://ieeexplore.ieee.org/abstract/document/7516231/. Accessed 28 July 2016
Dobrican RA, Zampunieris D (2016) A proactive solution, using wearable and mobile applications, for closing the gap between the rehabilitation team and cardiac patients. In Proc 2016 I.E. Int Conf ICHI. 146–155
Thorpe JR, Rønn-Andersen KVH, Bień P, Özkil AG, Forchhammer BH, Maier AM (2016) Pervasive assistive technology for people with dementia: a UCD case. Healthc Technol Lett. 3(4):297–302. https://doi.org/10.1049/htl.2016.0057
Nair S, Kheirkhahan M, Davoudi A, Rashidi P, Wanigatunga AA, Corbett DB, Manini TM, Ranka S (2016) Roamm: a software infrastructure for real-time monitoring of personal health. In Proc Int Conf HealthCom, pp 1–6. http://ieeexplore.ieee.org/abstract/document/7749479/. . Accessed 28 July 2016
Micallef N, Baillie L, Uzor S (2016) Time to exercise!: an aide-memoire stroke app for post-stroke arm rehabilitation. In Proc Int Conf MobileHCI, pp 112–123. https://dl.acm.org/citation.cfm?id=2935338. Accessed 6 July 2016
Ye X, Chen G, Gao Y, Wang H, Cao Y (2016) Assisting food journaling with automatic eating detection. In Proc 2016 CHI, pp 3255–3262. https://dl.acm.org/citation.cfm?id=2892426. Accessed 19 August 2017
Portney LG, Watkins MP (2015) Foundations of clinical research: applications to practice. FA Davis. https://www.fadavis.com/product/physical-therapy-foundations-clinical-research-portney-3?&RequestId=1574275166. Accessed 1 January 2017
Singh AK, Farmer C, Van Den Berg ML, Killington M, Barr CJ (2016) Accuracy of the FitBit at walking speeds and cadences relevant to clinical rehabilitation populations. Disabil Health J 9(2):320–323. https://doi.org/10.1016/j.dhjo.2015.10.011
Bassett DR, Toth LP, LaMunion SR, Crouter SE (2016) Step counting: a review of measurement considerations and health-related applications. Sports Med:1–13
Egan M The 5 most exciting announcements from Google i/o 2014: Android l, android wear news, android auto, chromebooks, and android tv. http://www.pcadvisor.co.uk/feature/google-android/5-most-exciting-announcements-from-google-i-o-2014-3524194/. Accessed 11 January 2017
Dawson T Top 10 best smartwatches buyers guide: October 2014 edition. 2017-01-11. http://www.androidheadlines.com/2014/10/top-10-best-smartwatches-buyers-guide-october-2014-edition.html. Accessed 11 January 2017
Introduction to Clinical Trials (1998) In: Friedman LM, Furberg C, DeMets DL (eds.) Fundamentals of Clinical Trials. Springer, New York, pp 1–18 http://www.springer.com/us/book/9781441915863. Accessed 12 August 2017
Funding
This work was supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) Los Angeles Pediatric Research using Integrated Sensor Monitoring Systems (PRISMS) Center: The Biomedical REAl-Time Health Evaluation (BREATHE) Platform, NIH/NIBIB U54 award no. EB022002.
Author information
Authors and Affiliations
Contributions
MS had the idea to write a systematic review on smartwatches in health care, CEK and MS performed the review and analysis, CEK wrote the article, and MS is the guarantor of the review.
Corresponding author
Ethics declarations
Conflict of Interests
The authors declare that they have no conflict of interest.
Rights and permissions
About this article
Cite this article
King, C.E., Sarrafzadeh, M. A Survey of Smartwatches in Remote Health Monitoring. J Healthc Inform Res 2, 1–24 (2018). https://doi.org/10.1007/s41666-017-0012-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41666-017-0012-7