{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T12:44:26Z","timestamp":1770813866191,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2020,11,5]],"date-time":"2020-11-05T00:00:00Z","timestamp":1604534400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020","doi-asserted-by":"publisher","award":["ONCORELIEF EU Project (ref: H2020-875392)"],"award-info":[{"award-number":["ONCORELIEF EU Project (ref: H2020-875392)"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Fitness sensors and health systems are paving the way toward improving the quality of medical care by exploiting the benefits of new technology. For example, the great amount of patient-generated health data available today gives new opportunities to measure life parameters in real time and create a revolution in communication for professionals and patients. In this work, we concentrated on the basic parameter typically measured by fitness applications and devices\u2014the number of steps taken daily. In particular, the main goal of this study was to compare the accuracy and precision of smartphone applications versus those of wearable devices to give users an idea about what can be expected regarding the relative difference in measurements achieved using different system typologies. In particular, the data obtained showed a difference of approximately 30%, proving that smartphone applications provide inaccurate measurements in long-term analysis, while wearable devices are precise and accurate. Accordingly, we challenge the reliability of previous studies reporting data collected with phone-based applications, and besides discussing the current limitations, we support the use of wearable devices for mHealth.<\/jats:p>","DOI":"10.3390\/s20216293","type":"journal-article","created":{"date-parts":[[2020,11,5]],"date-time":"2020-11-05T09:04:34Z","timestamp":1604567074000},"page":"6293","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Accuracy of Mobile Applications versus Wearable Devices in Long-Term Step Measurements"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0371-7782","authenticated-orcid":false,"given":"Filippo","family":"Piccinini","sequence":"first","affiliation":[{"name":"Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, 47014 Meldola (FC), Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1025-4210","authenticated-orcid":false,"given":"Giovanni","family":"Martinelli","sequence":"additional","affiliation":[{"name":"Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, 47014 Meldola (FC), Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3890-4852","authenticated-orcid":false,"given":"Antonella","family":"Carbonaro","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering (DISI), University of Bologna, 47521 Cesena, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.12965\/jer.1732928.464","article-title":"Review of researches on smartphone applications for physical activity promotion in healthy adults","volume":"13","author":"Jee","year":"2017","journal-title":"J. Exerc. Rehabil."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"101052","DOI":"10.1016\/j.pmcj.2019.101052","article-title":"User profiling from their use of smartphone applications: A survey","volume":"59","author":"Zhao","year":"2019","journal-title":"Pervasive Mob. Comput."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Kang, J.J., and Adibi, S. (2018). Systematic predictive analysis of personalized life expectancy using smart devices. Technologies, 6.","DOI":"10.3390\/technologies6030074"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Bayo-Monton, J.L., Martinez-Millana, A., Han, W., Fernandez-Llatas, C., Sun, Y., and Traver, V. (2018). Wearable sensors integrated with Internet of Things for advancing eHealth care. Sensors, 18.","DOI":"10.3390\/s18061851"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.pmcj.2012.06.002","article-title":"The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices","volume":"9","author":"Kranz","year":"2013","journal-title":"Pervasive Mob. Comput."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.compbiomed.2019.05.010","article-title":"Sleep quality prediction in caregivers using physiological signals","volume":"110","author":"Sadeghi","year":"2019","journal-title":"Comput. Biol. Med."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/j.semradonc.2019.05.008","article-title":"Big data from small devices: The future of smartphones in oncology","volume":"29","author":"Purswani","year":"2019","journal-title":"Semin. Radiat. Oncol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Dias, D., and Silva Cunha, J.P. (2018). Wearable health devices\u2014Vital sign monitoring, systems and technologies. Sensors, 18.","DOI":"10.3390\/s18082414"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1177\/1932296815622453","article-title":"A digital ecosystem of diabetes data and technology: Services, systems, and tools enabled by wearables, sensors, and apps","volume":"10","author":"Heintzman","year":"2016","journal-title":"J. Diabetes Sci. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Villarreal, V., Nielsen, M., and Samudio, M. (2018). Sensing and storing the blood pressure measure by patients through a platform and mobile devices. Sensors, 18.","DOI":"10.3390\/s18061805"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"956","DOI":"10.15288\/jsad.2013.74.956","article-title":"A wearable sensor system for monitoring cigarette smoking","volume":"74","author":"Sazonov","year":"2013","journal-title":"J. Stud. Alcohol Drugs"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Lee, J.W., Han, D.C., Shin, H.J., Yeom, S.H., Ju, B.K., and Lee, W. (2018). PEDOT: PSS-based temperature-detection thread for wearable devices. Sensors, 18.","DOI":"10.20944\/preprints201807.0450.v1"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e81","DOI":"10.2196\/mhealth.7689","article-title":"Mobile health in oncology: A patient survey about app-assisted cancer care","volume":"5","author":"Kessel","year":"2017","journal-title":"JMIR mHealth uHealth"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kang, X., Huang, B., and Qi, G. (2018). A novel walking detection and step counting algorithm using unconstrained smartphones. Sensors, 18.","DOI":"10.3390\/s18010297"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Rajan, K., Garofalo, E., and Chiolerio, A. (2018). Wearable intrinsically soft, stretchable, flexible devices for memories and computing. Sensors, 18.","DOI":"10.3390\/s18020367"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1249\/mss.0b013e31815a51b3","article-title":"Physical activity in the United States measured by accelerometer","volume":"40","author":"Troiano","year":"2008","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"451","DOI":"10.3949\/ccjm.84a.15173","article-title":"Apps and fitness trackers that measure sleep: Are they useful","volume":"84","author":"Mansukhani","year":"2017","journal-title":"Clevel. Clin. J. Med."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1080\/19325037.2019.1642265","article-title":"College students\u2019 use and perceptions of wearable fitness trackers","volume":"50","author":"Kinney","year":"2019","journal-title":"Am. J. Health Educ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s10865-018-9966-z","article-title":"The history and future of digital health in the field of behavioral medicine","volume":"42","author":"Arigo","year":"2019","journal-title":"J. Behav. Med."},{"key":"ref_20","first-page":"442","article-title":"Treatment of obesity","volume":"69","author":"Larsen","year":"1949","journal-title":"Tidsskr. Nor. laegeforen."},{"key":"ref_21","first-page":"455","article-title":"An objective measurement of hyperactivity","volume":"64","author":"Schulmann","year":"1959","journal-title":"Am. J. Ment. Defic."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.compbiomed.2018.09.025","article-title":"The mobile sleep lab app: An open-source framework for mobile sleep assessment based on consumer-grade wearable devices","volume":"103","author":"Burgdorf","year":"2018","journal-title":"Comput. Biol. Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1303","DOI":"10.1007\/s40279-016-0663-1","article-title":"Step counting: A review of measurement considerations and health-related applications","volume":"47","author":"Bassett","year":"2017","journal-title":"Sports Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2439","DOI":"10.2147\/CMAR.S148710","article-title":"Tracking steps in oncology: The time is now","volume":"10","author":"Purswani","year":"2018","journal-title":"Cancer Manag. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"315","DOI":"10.4258\/hir.2015.21.4.315","article-title":"Are currently available wearable devices for activity tracking and heart rate monitoring accurate, precise, and medically beneficial?","volume":"21","author":"Nounou","year":"2015","journal-title":"Health Inform. Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1186\/s12966-015-0314-1","article-title":"Systematic review of the validity and reliability of consumer-wearable activity trackers","volume":"12","author":"Evenson","year":"2015","journal-title":"Int. J. Behav. Nutr. Phys. Act."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"743","DOI":"10.3389\/fphys.2018.00743","article-title":"A critical review of consumer wearables, mobile applications and equipment for providing biofeedback, monitoring stress and sleep in physically active populations","volume":"9","author":"Peake","year":"2018","journal-title":"Front. Physiol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41597-019-0016-7","article-title":"Physical activity, sleep and cardiovascular health data for 50,000 individuals from the MyHeart Counts Study","volume":"6","author":"Hershman","year":"2019","journal-title":"Sci. Data"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1200\/CCI.17.00147","article-title":"Use of wearable, mobile, and sensor technology in cancer clinical trials","volume":"2","author":"Cox","year":"2018","journal-title":"JCO Clin. Cancer Inform."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.cct.2017.11.002","article-title":"Wearable activity monitors in oncology trials: Current use of an emerging technology","volume":"64","author":"Gresham","year":"2018","journal-title":"Contemp. Clin. Trials"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1058","DOI":"10.1200\/JCO.2012.48.2752","article-title":"Randomized, controlled trial of yoga in women with breast cancer undergoing radiotherapy","volume":"32","author":"Chandwani","year":"2014","journal-title":"J. Clin. Oncol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1007\/s10552-012-9896-y","article-title":"Physical activity, diabetes, and thyroid cancer risk: A pooled analysis of five prospective studies","volume":"23","author":"Kitahara","year":"2012","journal-title":"Cancer Causes Control."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2947","DOI":"10.1002\/ijc.24913","article-title":"Prospective study of body mass index, physical activity and thyroid cancer","volume":"126","author":"Leitzmann","year":"2010","journal-title":"Int. J. Cancer"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1023\/A:1013757030600","article-title":"Recreational physical activity and risk of papillary thyroid cancer (United States)","volume":"12","author":"Rossing","year":"2001","journal-title":"Cancer Causes Control."},{"key":"ref_35","first-page":"1","article-title":"Integrating heterogeneous data of healthcare devices to enable domain data management","volume":"14","author":"Carbonaro","year":"2018","journal-title":"J. e-Learn. Knowl. Soc."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Dijkhuis, T.B., Blaauw, F.J., Van Ittersum, M.W., Velthuijsen, H., and Aiello, M. (2018). Personalized physical activity coaching: A machine learning approach. Sensors, 18.","DOI":"10.3390\/s18020623"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"68","DOI":"10.23996\/fjhw.76673","article-title":"Validation of consumer wearable activity tracker as step measurement in free-living conditions","volume":"11","author":"Tam","year":"2019","journal-title":"Finn. J. eHealth eWelfare"},{"key":"ref_38","first-page":"764","article-title":"Wrist-worn physical activity trackers tend to underestimate steps during walking","volume":"10","author":"Sears","year":"2017","journal-title":"Int. J. Exerc. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1016\/j.jsams.2013.10.241","article-title":"Validation of the Fitbit One activity monitor device during treadmill walking","volume":"17","author":"Takacs","year":"2014","journal-title":"J. Sci. Med. Sport"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.gaitpost.2016.04.025","article-title":"Validity of FitBit, Jawbone UP, Nike+ and other wearable devices for level and stair walking","volume":"48","author":"Huang","year":"2016","journal-title":"Gait Posture"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Ngueleu, A.M., Blanchette, A.K., Bouyer, L., Maltais, D., McFadyen, B.J., Moffet, H., and Batcho, C.S. (2019). Design and accuracy of an instrumented insole using pressure sensors for step count. Sensors, 19.","DOI":"10.3390\/s19050984"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1001\/jama.2014.17841","article-title":"Accuracy of smartphone applications and wearable devices for tracking physical activity data","volume":"313","author":"Case","year":"2015","journal-title":"JAMA"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"e88","DOI":"10.2196\/mhealth.7870","article-title":"Mobile device accuracy for step counting across age groups","volume":"5","author":"Modave","year":"2017","journal-title":"JMIR mHealth uHealth"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1080\/02640414.2018.1491941","article-title":"Assessment of step accuracy using the Consumer Technology Association standard","volume":"37","author":"Bunn","year":"2019","journal-title":"J. Sports Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.jgo.2017.09.008","article-title":"A pilot study of an accelerometer-equipped smartphone to monitor older adults with cancer receiving chemotherapy in Mexico","volume":"9","author":"Kim","year":"2018","journal-title":"J. Geriatr. Oncol."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Jones, M., Morris, J., and Deruyter, F. (2018). Mobile healthcare and people with disabilities: Current state and future needs. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15030515"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"104017","DOI":"10.1016\/j.ijmedinf.2019.104017","article-title":"Wearable sensors with possibilities for data exchange: Analyzing status and needs of different actors in mobile health monitoring systems","volume":"133","author":"Muzny","year":"2020","journal-title":"Int. J. Med. Inform."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"D\u00edaz, S., Stephenson, J.B., and Labrador, M.A. (2020). Use of wearable sensor technology in gait, balance, and range of motion analysis. Appl. Sci., 10.","DOI":"10.3390\/app10010234"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1816","DOI":"10.1249\/MSS.0000000000000289","article-title":"Age group comparability of raw accelerometer output from wrist-and hip-worn monitors","volume":"46","author":"Hildebrand","year":"2014","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_50","first-page":"63","article-title":"Quality control and data reduction procedures for accelerometry-derived measures of physical activity","volume":"21","author":"Colley","year":"2010","journal-title":"Health Rep."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/21\/6293\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:29:33Z","timestamp":1760178573000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/21\/6293"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,5]]},"references-count":50,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2020,11]]}},"alternative-id":["s20216293"],"URL":"https:\/\/doi.org\/10.3390\/s20216293","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,5]]}}}