Published on in Vol 6 , No 1 (2018) :January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/8815, first published .
Smartphone App–Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability

Smartphone App–Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability

Smartphone App–Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability

Journals

  1. Zafonte R, Pascual‐Leone A, Baggish A, Weisskopf M, Taylor H, Connor A, Baker J, Cohan S, Valdivia C, Courtney T, Cohen I, Speizer F, Nadler L. The Football Players’ Health Study at Harvard University: Design and objectives. American Journal of Industrial Medicine 2019;62(8):643 View
  2. Kobsar D, Charlton J, Tse C, Esculier J, Graffos A, Krowchuk N, Thatcher D, Hunt M. Validity and reliability of wearable inertial sensors in healthy adult walking: a systematic review and meta-analysis. Journal of NeuroEngineering and Rehabilitation 2020;17(1) View
  3. Guillén-Rogel P, Franco-Escudero C, Marín P. Test-retest reliability of a smartphone app for measuring core stability for two dynamic exercises. PeerJ 2019;7:e7485 View
  4. Tang Y, Li Z, Tian H, Ding J, Lin B. Detecting Toe-Off Events Utilizing a Vision-Based Method. Entropy 2019;21(4):329 View
  5. Steinert A, Sattler I, Otte K, Röhling H, Mansow-Model S, Müller-Werdan U. Using New Camera-Based Technologies for Gait Analysis in Older Adults in Comparison to the Established GAITRite System. Sensors 2019;20(1):125 View
  6. Martin E, Kim S, Unfried A, Delcambre S, Sanders N, Bischoff B, Saavedra R. 6th vital sign app: Testing validity and reliability for measuring gait speed. Gait & Posture 2019;68:264 View
  7. Zhong R, Rau P. Are cost-effective technologies feasible to measure gait in older adults? A systematic review of evidence-based literature. Archives of Gerontology and Geriatrics 2020;87:103970 View
  8. Fujiwara S, Sato S, Sugawara A, Nishikawa Y, Koji T, Nishimura Y, Ogasawara K. The Coefficient of Variation of Step Time Can Overestimate Gait Abnormality: Test-Retest Reliability of Gait-Related Parameters Obtained with a Tri-Axial Accelerometer in Healthy Subjects. Sensors 2020;20(3):577 View
  9. Manor B, Zhou J, Lo O, Zhu H, Gouskova N, Yu W, Zafonte R, Lipsitz L, Travison T, Pascual‐Leone A. Self‐Reported Head Trauma Predicts Poor Dual Task Gait in Retired National Football League Players. Annals of Neurology 2020;87(1):75 View
  10. Erickson K, Grove G, Burns J, Hillman C, Kramer A, McAuley E, Vidoni E, Becker J, Butters M, Gray K, Huang H, Jakicic J, Kamboh M, Kang C, Klunk W, Lee P, Marsland A, Mettenburg J, Rogers R, Stillman C, Sutton B, Szabo-Reed A, Verstynen T, Watt J, Weinstein A, Wollam M. Investigating Gains in Neurocognition in an Intervention Trial of Exercise (IGNITE): Protocol. Contemporary Clinical Trials 2019;85:105832 View
  11. Zhong R, Rau P. A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation. JMIR mHealth and uHealth 2020;8(5):e14453 View
  12. Park J, Kim T. Reliability and Validity of a Smartphone-based Assessment of Gait Parameters in Patients with Chronic Stroke. Journal of The Korean Society of Physical Medicine 2018;13(3):19 View
  13. Cattaneo G, Bartrés-Faz D, Morris T, Sánchez J, Macià D, Tarrero C, Tormos J, Pascual-Leone A. The Barcelona Brain Health Initiative: A Cohort Study to Define and Promote Determinants of Brain Health. Frontiers in Aging Neuroscience 2018;10 View
  14. Jim H, Hoogland A, Brownstein N, Barata A, Dicker A, Knoop H, Gonzalez B, Perkins R, Rollison D, Gilbert S, Nanda R, Berglund A, Mitchell R, Johnstone P. Innovations in research and clinical care using patient‐generated health data. CA: A Cancer Journal for Clinicians 2020;70(3):182 View
  15. Takayanagi N, Sudo M, Yamashiro Y, Lee S, Kobayashi Y, Niki Y, Shimada H. Relationship between Daily and In-laboratory Gait Speed among Healthy Community-dwelling Older Adults. Scientific Reports 2019;9(1) View
  16. Chien J, Torres-Russotto D, Wang Z, Gui C, Whitney D, Siu K, Barbieri F. The use of smartphone in measuring stance and gait patterns in patients with orthostatic tremor. PLOS ONE 2019;14(7):e0220012 View
  17. Sato S, Fujiwara S, Miyoshi K, Chida K, Kobayashi M, Kubo Y, Yoshida K, Terasaki K, Ogasawara K. Improvement in gait function after carotid endarterectomy is associated with postoperative recovery in perfusion and neurotransmitter receptor function in the motor-related cerebral cortex: a 123I-iomazenil SPECT study. Nuclear Medicine Communications 2020;41(11):1161 View
  18. Montero-Odasso M, Sarquis-Adamson Y, Kamkar N, Pieruccini-Faria F, Bray N, Cullen S, Mahon J, Titus J, Camicioli R, Borrie M, Bherer L, Speechley M. Dual-task gait speed assessments with an electronic walkway and a stopwatch in older adults. A reliability study. Experimental Gerontology 2020;142:111102 View
  19. Takahashi T, Fujiwara S, Igarashi S, Ando T, Chida K, Kobayashi M, Yoshida K, Koji T, Kubo Y, Ogasawara K. Comparison of Subjective and Objective Assessments on Improvement in Gait Function after Carotid Endarterectomy. Sensors 2020;20(22):6590 View
  20. Su D, Liu Z, Jiang X, Zhang F, Yu W, Ma H, Wang C, Wang Z, Wang X, Hu W, Manor B, Feng T, Zhou J. Simple Smartphone-Based Assessment of Gait Characteristics in Parkinson Disease: Validation Study. JMIR mHealth and uHealth 2021;9(2):e25451 View
  21. Krichen M. Anomalies Detection Through Smartphone Sensors: A Review. IEEE Sensors Journal 2021;21(6):7207 View
  22. Pfau T, Reilly P. How low can we go? Influence of sample rate on equine pelvic displacement calculated from inertial sensor data. Equine Veterinary Journal 2021;53(5):1075 View
  23. Bahl N, Magnavita E, Hshieh T, Testa M, Kim D, Manor B, Driver J, Abel G, DuMontier C. Objective performance tests of cognition and physical function as part of a virtual geriatric assessment. Journal of Geriatric Oncology 2021;12(8):1256 View
  24. Bouça-Machado R, Pona-Ferreira F, Leitão M, Clemente A, Vila-Viçosa D, Kauppila L, Costa R, Matias R, Ferreira J. Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease. Sensors 2021;21(15):4972 View
  25. Juneau P, Baddour N, Burger H, Bavec A, Lemaire E. Comparison of Decision Tree and Long Short-Term Memory Approaches for Automated Foot Strike Detection in Lower Extremity Amputee Populations. Sensors 2021;21(21):6974 View
  26. Zhong R, Gao T. Impact of walking states, self-reported daily walking amount and age on the gait of older adults measured with a smart-phone app: a pilot study. BMC Geriatrics 2022;22(1) View
  27. Meigal A, Gerasimova-Meigal L, Reginya S, Soloviev A, Moschevikin A. Gait Characteristics Analyzed with Smartphone IMU Sensors in Subjects with Parkinsonism under the Conditions of “Dry” Immersion. Sensors 2022;22(20):7915 View
  28. PARATI M, AMBROSINI E, DE MARIA B, GALLOTTA M, DALLA VECCHIA L, FERRIERO G, FERRANTE S. The reliability of gait parameters captured via instrumented walkways: a systematic review and meta-analysis. European Journal of Physical and Rehabilitation Medicine 2022;58(3) View
  29. Kahlon A, Sansare A, Behboodi A. Remote Gait Analysis as a Proxy for Traditional Gait Laboratories: Utilizing Smartphones for Subject-Driven Gait Assessment across Differing Terrains. Biomechanics 2022;2(2):235 View
  30. Zhou J, Jiang X, Yu W, Zhu H, Lo O, Gouskova N, Travison T, Lipsitz L, Pascual-Leone A, Manor B. A Smartphone App-Based Application Enabling Remote Assessments of Standing Balance During the COVID-19 Pandemic and Beyond. IEEE Internet of Things Journal 2021;8(21):15818 View
  31. Telfeian A. Editorial. Neurosurgical healthcare delivery quality and “where we go from here” after the pandemic. Neurosurgical Focus 2021;51(5):E3 View
  32. Hamilton R, Williams J, Holt C. Biomechanics beyond the lab: Remote technology for osteoarthritis patient data—A scoping review. Frontiers in Rehabilitation Sciences 2022;3 View
  33. Shema-Shiratzky S, Beer Y, Mor A, Elbaz A. Smartphone-based inertial sensors technology – Validation of a new application to measure spatiotemporal gait metrics. Gait & Posture 2022;93:102 View
  34. Homan K, Yamamoto K, Kadoya K, Ishida N, Iwasaki N. Comprehensive validation of a wearable foot sensor system for estimating spatiotemporal gait parameters by simultaneous three-dimensional optical motion analysis. BMC Sports Science, Medicine and Rehabilitation 2022;14(1) View
  35. Salchow-Hömmen C, Skrobot M, Jochner M, Schauer T, Kühn A, Wenger N. Review—Emerging Portable Technologies for Gait Analysis in Neurological Disorders. Frontiers in Human Neuroscience 2022;16 View
  36. Rentz C, Far M, Boltes M, Schnitzler A, Amunts K, Dukart J, Minnerop M. System Comparison for Gait and Balance Monitoring Used for the Evaluation of a Home-Based Training. Sensors 2022;22(13):4975 View
  37. Alberto S, Cabral S, Proença J, Pona-Ferreira F, Leitão M, Bouça-Machado R, Kauppila L, Veloso A, Costa R, Ferreira J, Matias R. Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments. BMC Neurology 2021;21(1) View
  38. Arpan I, Shah V, McNames J, Harker G, Carlson-Kuhta P, Spain R, El-Gohary M, Mancini M, Horak F. Fall Prediction Based on Instrumented Measures of Gait and Turning in Daily Life in People with Multiple Sclerosis. Sensors 2022;22(16):5940 View
  39. Christensen J, Stanley E, Oro E, Carlson H, Naveh Y, Shalita R, Teitz L. The validity and reliability of the OneStep smartphone application under various gait conditions in healthy adults with feasibility in clinical practice. Journal of Orthopaedic Surgery and Research 2022;17(1) View
  40. Zhou J, Cattaneo G, Yu W, Lo O, Gouskova N, Delgado-Gallén S, Redondo-Camós M, España-Irla G, Solana-Sánchez J, Tormos J, Lipsitz L, Bartrés-Faz D, Pascual-Leone A, Manor B. The age-related contribution of cognitive function to dual-task gait in middle-aged adults in Spain: observations from a population-based study. The Lancet Healthy Longevity 2023;4(3):e98 View
  41. Sher A, Bunker M, Akanyeti O. Towards personalized environment‐aware outdoor gait analysis using a smartphone. Expert Systems 2022 View
  42. Kim M, Hall C. Application of EMGB to Study Impacts of Public Green Space on Active Transport Behavior: Evidence from South Korea. International Journal of Environmental Research and Public Health 2022;19(12):7459 View
  43. Shahar R, Agmon M. Gait Analysis Using Accelerometry Data from a Single Smartphone: Agreement and Consistency between a Smartphone Application and Gold-Standard Gait Analysis System. Sensors 2021;21(22):7497 View
  44. Rashid U, Barbado D, Olsen S, Alder G, Elvira J, Lord S, Niazi I, Taylor D. Validity and Reliability of a Smartphone App for Gait and Balance Assessment. Sensors 2021;22(1):124 View
  45. Zeinab M A, Nahed A S, Hossam M E, Mahmoud Y E. Comparison between the efficacy of underwater treadmill and over-ground treadmill training program on knee joint during gait cycle of stroke patients. Annals of Musculoskeletal Medicine 2021:005 View
  46. DuMontier C, Jaung T, Bahl N, Manor B, Testa M, Dieli-Conwright C, Kim D, Hshieh T, Driver J, Abel G. Virtual frailty assessment for older adults with hematologic malignancies. Blood Advances 2022;6(18):5360 View
  47. Di Bacco V, Gage W. Evaluation of a smartphone accelerometer system for measuring nonlinear dynamics during treadmill walking: concurrent validity and test-retest reliability. Journal of Biomechanics 2023:111527 View

Books/Policy Documents

  1. Kloek C. De dokter en digitalisering. View
  2. Bunker M, Sher A, Akpokodje V, Villagra F, Parthaláin N, Akanyeti O. Advances in Computational Intelligence Systems. View