Published on 15.04.15 in Vol 3, No 2 (2015): Apr-Jun
Works citing "Validation of Physical Activity Tracking via Android Smartphones Compared to ActiGraph Accelerometer: Laboratory-Based and Free-Living Validation Studies"
According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.3505):
(note that this is only a small subset of citations)
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Bort-Roig J, Chirveches-Pérez E, Garcia-Cuyàs F, Dowd KP, Puig-Ribera A. Monitoring Occupational Sitting, Standing, and Stepping in Office Employees With the W@W-App and the MetaWearC Sensor: Validation Study. JMIR mHealth and uHealth 2020;8(8):e15338
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Althoff T, Sosič R, Hicks JL, King AC, Delp SL, Leskovec J. Large-scale physical activity data reveal worldwide activity inequality. Nature 2017;547(7663):336
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Yamamoto K, Matsuda F, Matsukawa T, Yamamoto N, Ishii K, Kurihara T, Yamada S, Matsuki T, Kamijima M, Ebara T. Identifying characteristics of indicators of sedentary behavior using objective measurements. Journal of Occupational Health 2020;62(1)
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Åkerberg A, Söderlund A, Lindén M. Investigation of the validity and reliability of a smartphone pedometer application. European Journal of Physiotherapy 2016;18(3):185
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Amagasa S, Kamada M, Sasai H, Fukushima N, Kikuchi H, Lee I, Inoue S. How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study. JMIR mHealth and uHealth 2019;7(1):e10418
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Kramer J, Künzler F, Mishra V, Smith SN, Kotz D, Scholz U, Fleisch E, Kowatsch T. Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results From an Optimization Trial. Annals of Behavioral Medicine 2020;54(7):518
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Smith MP, Standl M, Heinrich J, Schulz H, Buchowski M. Accelerometric estimates of physical activity vary unstably with data handling. PLOS ONE 2017;12(11):e0187706
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Spruijt-Metz D, Wen CKF, O’Reilly G, Li M, Lee S, Emken BA, Mitra U, Annavaram M, Ragusa G, Narayanan S. Innovations in the Use of Interactive Technology to Support Weight Management. Current Obesity Reports 2015;4(4):510
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Pope L, Garnett B, Dibble M. Lessons Learned Through the Implementation of an eHealth Physical Activity Gaming Intervention with High School Youth. Games for Health Journal 2018;7(2):136
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Dadlani V, Levine JA, McCrady-Spitzer SK, Dassau E, Kudva YC. Physical Activity Capture Technology With Potential for Incorporation Into Closed-Loop Control for Type 1 Diabetes. Journal of Diabetes Science and Technology 2015;9(6):1208
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Mitchell M, White L, Lau E, Leahey T, Adams MA, Faulkner G. Evaluating the Carrot Rewards App, a Population-Level Incentive-Based Intervention Promoting Step Counts Across Two Canadian Provinces: Quasi-Experimental Study. JMIR mHealth and uHealth 2018;6(9):e178
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Thorpe JR, Forchhammer BH, Maier AM. Development of a Sensor-Based Behavioral Monitoring Solution to Support Dementia Care. JMIR mHealth and uHealth 2019;7(6):e12013
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Bort-Roig J, Puig-Ribera A, Contreras RS, Chirveches-Pérez E, Martori JC, Gilson ND, McKenna J. Monitoring sedentary patterns in office employees: validity of an m-health tool (Walk@Work-App) for occupational health. Gaceta Sanitaria 2018;32(6):563
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Smith MP, Horsch A, Standl M, Heinrich J, Schulz H. Uni- and triaxial accelerometric signals agree during daily routine, but show differences between sports. Scientific Reports 2018;8(1)
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Zhai Y, Nasseri N, Pöttgen J, Gezhelbash E, Heesen C, Stellmann J. Smartphone Accelerometry: A Smart and Reliable Measurement of Real-Life Physical Activity in Multiple Sclerosis and Healthy Individuals. Frontiers in Neurology 2020;11
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Höchsmann C, Knaier R, Infanger D, Schmidt-Trucksäss A. Validity of smartphones and activity trackers to measure steps in a free-living setting over three consecutive days. Physiological Measurement 2020;41(1):015001
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Silsupadol P, Prupetkaew P, Kamnardsiri T, Lugade V. Smartphone-Based Assessment of Gait During Straight Walking, Turning, and Walking Speed Modulation in Laboratory and Free-Living Environments. IEEE Journal of Biomedical and Health Informatics 2020;24(4):1188
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Olson E, Badder C, Sullivan S, Smith C, Propert K, Margulies SS. Alterations in Daytime and Nighttime Activity in Piglets after Focal and Diffuse Brain Injury. Journal of Neurotrauma 2016;33(8):734
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Floegel TA, Florez-Pregonero A, Hekler EB, Buman MP. Validation of Consumer-Based Hip and Wrist Activity Monitors in Older Adults With Varied Ambulatory Abilities. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 2017;72(2):229
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Funk MD, Salazar CL, Martinez M, Gonzalez J, Leyva P, Bassett D, Karabulut M. Validity of Smartphone Applications at Measuring Steps: Does Wear Location Matter?. Journal for the Measurement of Physical Behaviour 2019;2(1):22
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Urrea B, Misra S, Plante TB, Kelli HM, Misra S, Blaha MJ, Martin SS. Mobile Health Initiatives to Improve Outcomes in Primary Prevention of Cardiovascular Disease. Current Treatment Options in Cardiovascular Medicine 2015;17(12)
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Rodriguez V, Medrano C, Plaza I, Corella C, Abarca A, Julian J. Comparison of Several Algorithms to Estimate Activity Counts with Smartphones as an Indication of Physical Activity Level. IRBM 2019;40(2):95
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. Using Fitness Trackers in Clinical Research: What Nurse Practitioners Need to Know. The Journal for Nurse Practitioners 2017;13(1):34
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Maddison R, Gemming L, Monedero J, Bolger L, Belton S, Issartel J, Marsh S, Direito A, Solenhill M, Zhao J, Exeter DJ, Vathsangam H, Rawstorn JC. Quantifying Human Movement Using the Movn Smartphone App: Validation and Field Study. JMIR mHealth and uHealth 2017;5(8):e122
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Brodie M, Pliner E, Ho A, Li K, Chen Z, Gandevia S, Lord S. Big data vs accurate data in health research: Large-scale physical activity monitoring, smartphones, wearable devices and risk of unconscious bias. Medical Hypotheses 2018;119:32
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Kong N, Choi J, Seo WS. Evaluation of Sleep Problems or Disorders Using Sleep Questionnaires. Chronobiology in Medicine 2019;1(4):144
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Mitchell M, Lau E, White L, Faulkner G. Commercial app use linked with sustained physical activity in two Canadian provinces: a 12-month quasi-experimental study. International Journal of Behavioral Nutrition and Physical Activity 2020;17(1)
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Martin CA, Rivera DE, Hekler EB, Riley WT, Buman MP, Adams MA, Magann AB. Development of a Control-Oriented Model of Social Cognitive Theory for Optimized mHealth Behavioral Interventions. IEEE Transactions on Control Systems Technology 2020;28(2):331
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Yamamoto K, Ebara T, Matsuda F, Matsukawa T, Yamamoto N, Ishii K, Kurihara T, Yamada S, Matsuki T, Tani N, Kamijima M. Can self-monitoring mobile health apps reduce sedentary behavior? A randomized controlled trial. Journal of Occupational Health 2020;62(1)
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Direito A, Walsh D, Hinbarji M, Albatal R, Tooley M, Whittaker R, Maddison R. Using the Intervention Mapping and Behavioral Intervention Technology Frameworks: Development of an mHealth Intervention for Physical Activity and Sedentary Behavior Change. Health Education & Behavior 2018;45(3):331
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Hekler EB, Rivera DE, Martin CA, Phatak SS, Freigoun MT, Korinek E, Klasnja P, Adams MA, Buman MP. Tutorial for Using Control Systems Engineering to Optimize Adaptive Mobile Health Interventions. Journal of Medical Internet Research 2018;20(6):e214
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Katapally TR, Chu LM. Digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a SMART Platform study. BMJ Open 2020;10(6):e036787
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Perazzo JD, Webel AR, Fichtenbaum CJ, McComsey GA. Bone Health in People Living With HIV: The Role of Exercise and Directions for Future Research. Journal of the Association of Nurses in AIDS Care 2018;29(2):330
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Consolvo S, Bentley FR, Hekler EB, Phatak SS. Mobile User Research: A Practical Guide. Synthesis Lectures on Mobile and Pervasive Computing 2017;9(1):i
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Höchsmann C, Knaier R, Eymann J, Hintermann J, Infanger D, Schmidt‐Trucksäss A. Validity of activity trackers, smartphones, and phone applications to measure steps in various walking conditions. Scandinavian Journal of Medicine & Science in Sports 2018;28(7):1818
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Ding D, Ramirez Varela A, Bauman AE, Ekelund U, Lee I, Heath G, Katzmarzyk PT, Reis R, Pratt M. Towards better evidence-informed global action: lessons learnt from the Lancet series and recent developments in physical activity and public health. British Journal of Sports Medicine 2020;54(8):462
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Czmil A, Czmil S, Mazur D. A Method to Detect Type 1 Diabetes Based on Physical Activity Measurements Using a Mobile Device. Applied Sciences 2019;9(12):2555
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Heininga VE, van Roekel E, Wichers M, Oldehinkel AJ, Brañas-Garza P. Reward and punishment learning in daily life: A replication study. PLOS ONE 2017;12(10):e0180753
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Dabove P, Ghinamo G, Lingua AM. Inertial sensors for smartphones navigation. SpringerPlus 2015;4(1)
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Tavares BF, Pires IM, Marques G, Garcia NM, Zdravevski E, Lameski P, Trajkovik V, Jevremovic A. Mobile Applications for Training Plan Using Android Devices: A Systematic Review and a Taxonomy Proposal. Information 2020;11(7):343
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손윤선 , Kim Jong Kwang , Daetaek Lee , 황봉연 , 이종도 , 김기언 . Validity Evaluation of the T-REX Triaxial Accelerometer To Measure Physical Activity by Exercise Types and T-REX Attachment Locations in Men and Women. The Korean Journal of Measurement and Evaluation in Physical Education and Sports Science 2016;18(2):1
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Li X, Wang Y, Zhang B, Ma J. PSDRNN: An Efficient and Effective HAR Scheme Based on Feature Extraction and Deep Learning. IEEE Transactions on Industrial Informatics 2020;16(10):6703
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Younsun Son , Jong Kwang Kim , Yoon Jung Bae , Bong Yeon Hwang , Dae Taek Lee , Mi Young Lee , Chong-Do Lee , Keyeon KIM . Concurrent Validation of T-REX Accelerometer. IJASS(International Journal of Applied Sports Sciences) 2016;28(2):79
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Lee W, Lin K, Seto E, Migliaccio GC. Wearable sensors for monitoring on-duty and off-duty worker physiological status and activities in construction. Automation in Construction 2017;83:341
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Park CL, Cho D, Moore PJ. How does education lead to healthier behaviours? Testing the mediational roles of perceived control, health literacy and social support. Psychology & Health 2018;33(11):1416
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Zhou M, Fukuoka Y, Goldberg K, Vittinghoff E, Aswani A. Applying machine learning to predict future adherence to physical activity programs. BMC Medical Informatics and Decision Making 2019;19(1)
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Sullivan AN, Lachman ME. Behavior Change with Fitness Technology in Sedentary Adults: A Review of the Evidence for Increasing Physical Activity. Frontiers in Public Health 2017;4
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Wu R, Liaqat D, de Lara E, Son T, Rudzicz F, Alshaer H, Abed-Esfahani P, Gershon AS. Feasibility of Using a Smartwatch to Intensively Monitor Patients With Chronic Obstructive Pulmonary Disease: Prospective Cohort Study. JMIR mHealth and uHealth 2018;6(6):e10046
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Pearson E, Prapavessis H, Higgins C, Petrella R, White L, Mitchell M. Adding team-based financial incentives to the Carrot Rewards physical activity app increases daily step count on a population scale: a 24-week matched case control study. International Journal of Behavioral Nutrition and Physical Activity 2020;17(1)
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Kumar DS, Galloway JC. Feasibility of a home-based environmental enrichment paradigm to enhance purposeful activities in adults with traumatic brain injury: a case series. Disability and Rehabilitation 2022;44(14):3559
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Muntaner-Mas A, Martinez-Nicolas A, Quesada A, Cadenas-Sanchez C, Ortega FB. Smartphone App (2kmFIT-App) for Measuring Cardiorespiratory Fitness: Validity and Reliability Study. JMIR mHealth and uHealth 2021;9(1):e14864
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Stålesen J, Westergren T, Herman Hansen B, Berntsen S. A Mapping Review of Physical Activity Recordings Derived From Smartphone Accelerometers. Journal of Physical Activity and Health 2020;17(11):1184
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Mitchell MS, Orstad SL, Biswas A, Oh PI, Jay M, Pakosh MT, Faulkner G. Financial incentives for physical activity in adults: systematic review and meta-analysis. British Journal of Sports Medicine 2020;54(21):1259
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Savi D, Graziano L, Giordani B, Schiavetto S, Vito CD, Migliara G, Simmonds NJ, Palange P, Elborn JS. New strategies of physical activity assessment in cystic fibrosis: a pilot study. BMC Pulmonary Medicine 2020;20(1)
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Wang Y, Zhang Y, Bennell K, White DK, Wei J, Wu Z, He H, Liu S, Luo X, Hu S, Zeng C, Lei G. Physical Distancing Measures and Walking Activity in Middle-aged and Older Residents in Changsha, China, During the COVID-19 Epidemic Period: Longitudinal Observational Study. Journal of Medical Internet Research 2020;22(10):e21632
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Wang Y, König LM, Reiterer H. A Smartphone App to Support Sedentary Behavior Change by Visualizing Personal Mobility Patterns and Action Planning (SedVis): Development and Pilot Study. JMIR Formative Research 2021;5(1):e15369
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McCarthy H, Potts HWW, Fisher A. Physical Activity Behavior Before, During, and After COVID-19 Restrictions: Longitudinal Smartphone-Tracking Study of Adults in the United Kingdom. Journal of Medical Internet Research 2021;23(2):e23701
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Ho JY, Zijlema WL, Triguero-Mas M, Donaire-Gonzalez D, Valentín A, Ballester J, Chan EY, Goggins WB, Mo PK, Kruize H, van den Berg M, Gražuleviciene R, Gidlow CJ, Jerrett M, Seto EY, Barrera-Gómez J, Nieuwenhuijsen MJ. Does surrounding greenness moderate the relationship between apparent temperature and physical activity? Findings from the PHENOTYPE project. Environmental Research 2021;197:110992
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Mohammed MHH, Al‐Qahtani MHH, Takken T. Effects of 12 weeks of recreational football (soccer) with caloric control on glycemia and cardiovascular health of adolescent boys with type 1 diabetes. Pediatric Diabetes 2021;22(4):625
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Park J, Yoo E, Kim Y, Lee J. What Happened Pre- and during COVID-19 in South Korea? Comparing Physical Activity, Sleep Time, and Body Weight Status. International Journal of Environmental Research and Public Health 2021;18(11):5863
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de Carvalho Lana R, Ribeiro de Paula A, Souza Silva AF, Vieira Costa PH, Polese JC. Validity of mHealth devices for counting steps in individuals with Parkinson's disease. Journal of Bodywork and Movement Therapies 2021;28:496
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Pontin F, Lomax N, Clarke G, Morris MA. Socio-demographic determinants of physical activity and app usage from smartphone data. Social Science & Medicine 2021;284:114235
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Lugade V, Kuntapun J, Prupetkaew P, Boripuntakul S, Verner E, Silsupadol P. Three-Day Remote Monitoring of Gait Among Young and Older Adults Using Participants’ Personal Smartphones. Journal of Aging and Physical Activity 2021;29(6):1026
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Arumugam A, Samara SS, Shalash RJ, Qadah RM, Farhani AM, Alnajim HM, Alkalih HY. Does Google Fit provide valid energy expenditure measurements of functional tasks compared to those of Fibion accelerometer in healthy individuals? A cross-sectional study. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 2021;15(6):102301
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Prado RCR, Knebel MTG, Ribeiro EHC, Teixeira IP, Sasaki JE, Araújo LVD, Guerra PH, Florindo AA. Smartphone apps for tracking physical activity and sedentary behavior: A criterion validity review. Revista Brasileira de Atividade Física & Saúde 2022;27:1
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Li D, Lee C, Park AH, Lee H, Ding Y. Contextual and environmental factors that influence health: A within-subjects field experiment protocol. Frontiers in Public Health 2023;11
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Ho JY, Goggins WB, Mo PKH, Chan EYY. The effect of temperature on physical activity: an aggregated timeseries analysis of smartphone users in five major Chinese cities. International Journal of Behavioral Nutrition and Physical Activity 2022;19(1)
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Ráthonyi G, Takács V, Szilágyi R, Bácsné Bába , Müller A, Bács Z, Harangi-Rákos M, Balogh L, Ráthonyi-Odor K. Your Physical Activity Is in Your Hand—Objective Activity Tracking Among University Students in Hungary, One of the Most Obese Countries in Europe. Frontiers in Public Health 2021;9
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Yao Q, Wang J, Sun Y, Zhang L, Sun S, Cheng M, Yang Q, Wang S, Huang L, Lin T, Jia Y. Accuracy of steps measured by smartphones-based WeRun compared with ActiGraph-GT3X accelerometer in free-living conditions. Frontiers in Public Health 2022;10
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Vos AL, de Bruijn G, Klein MCA, Lakerveld J, Boerman SC, Smit EG. SNapp, a Tailored Smartphone App Intervention to Promote Walking in Adults of Low Socioeconomic Position: Development and Qualitative Pilot Study. JMIR Formative Research 2023;7:e40851
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Goh CMJL, Wang NX, Müller AM, Yap R, Edney S, Müller-Riemenschneider F. Validation of Smartphones and Different Low-Cost Activity Trackers for Step Counting Under Free-Living Conditions. Journal for the Measurement of Physical Behaviour 2023;:1
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Abdullah S, Arshad J, Khan MM, Alazab M, Salah K. PRISED tangle: a privacy-aware framework for smart healthcare data sharing using IOTA tangle. Complex & Intelligent Systems 2023;9(3):3023
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Atef H, Gaber M. Would the Actigraph Always be Sufficient for Sleep Analysis in Exercise-Based Studies? A Case Report of Negative Response of Sleep to Exercise. Sleep Science 2023;16(02):265
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Kumar A, Singh RR, Chatterjee I, Sharma N, Rana V. Neuroadaptive Incentivization in Healthcare using Blockchain and IoT. SN Computer Science 2023;5(1)
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Di Cesare MG, Perpetuini D, Cardone D, Merla A. Assessment of Voice Disorders Using Machine Learning and Vocal Analysis of Voice Samples Recorded through Smartphones. BioMedInformatics 2024;4(1):549
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According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.3505):
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Porszasz J, Stringer W, Casaburi R. Clinical Exercise Testing. 2018. 3:59
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Dorsch AK, King CE, Dobkin BH. Neurorehabilitation Technology. 2016. Chapter 29:605
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Zahran L, El-Beltagy M, Saleh M. Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019. 2020. Chapter 62:673
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Sariyska R, Montag C. Digital Phenotyping and Mobile Sensing. 2019. Chapter 4:45
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Rodriguez VH, Medrano C, Plaza I, Corella C, Abarca A, Julian JA. Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016). 2016. Chapter 6:49
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Saito T, Ono R. Physical Therapy and Research in Patients with Cancer. 2022. Chapter 13:293
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Sariyska R, Montag C. Digital Phenotyping and Mobile Sensing. 2023. Chapter 5:57
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