Published on in Vol 1, No 2 (2013): Jul-Dec

Differences in Trunk Accelerometry Between Frail and Nonfrail Elderly Persons in Sit-to-Stand and Stand-to-Sit Transitions Based on a Mobile Inertial Sensor

Differences in Trunk Accelerometry Between Frail and Nonfrail Elderly Persons in Sit-to-Stand and Stand-to-Sit Transitions Based on a Mobile Inertial Sensor

Differences in Trunk Accelerometry Between Frail and Nonfrail Elderly Persons in Sit-to-Stand and Stand-to-Sit Transitions Based on a Mobile Inertial Sensor

Journals

  1. Galán-Mercant A, Barón-López F, Labajos-Manzanares M, Cuesta-Vargas A. Reliability and criterion-related validity with a smartphone used in timed-up-and-go test. BioMedical Engineering OnLine 2014;13(1) View
  2. Galán-Mercant A, Cuesta-Vargas A. Detección precoz de la fragilidad, tecnología aplicada al movimiento humano para la prevención de la discapacidad. Fisioterapia 2017;39(3):135 View
  3. Mateos-Angulo A, Galán-Mercant A, Cuesta-Vargas A. Mobile Jump Assessment (mJump): A Descriptive and Inferential Study. JMIR Rehabilitation and Assistive Technologies 2015;2(2):e7 View
  4. LEMOYNE R, MASTROIANNI T. IMPLEMENTATION OF A SMARTPHONE AS A WIRELESS ACCELEROMETER PLATFORM FOR QUANTIFYING HEMIPLEGIC GAIT DISPARITY IN A FUNCTIONALLY AUTONOMOUS CONTEXT. Journal of Mechanics in Medicine and Biology 2018;18(02):1850005 View
  5. Mugueta-Aguinaga I, Garcia-Zapirain B. Is Technology Present in Frailty? Technology a Back-up Tool for Dealing with Frailty in the Elderly: A Systematic Review. Aging and disease 2017;8(2):2005 View
  6. Shah N, Aleong R, So I. Novel Use of a Smartphone to Measure Standing Balance. JMIR Rehabilitation and Assistive Technologies 2016;3(1):e4 View
  7. Galán-Mercant A, Cuesta-Vargas A. Clinical frailty syndrome assessment using inertial sensors embedded in smartphones. Physiological Measurement 2015;36(9):1929 View
  8. Rahemi H, Nguyen H, Lee H, Najafi B. Toward Smart Footwear to Track Frailty Phenotypes—Using Propulsion Performance to Determine Frailty. Sensors 2018;18(6):1763 View
  9. González-Sánchez M, Cuesta-Vargas A, del Mar Rodríguez González M, Caro E, Núñez G, Galán-Mercant A, Belmonte J. Effectiveness of a muticomponent workout program integrated in an evidence based multimodal program in hyperfrail elderly patients: POWERAGING randomized clinical trial protocol. BMC Geriatrics 2019;19(1) View
  10. Galán-Mercant A, Cuesta-Vargas A. Mobile Romberg test assessment (mRomberg). BMC Research Notes 2014;7(1) View
  11. Dasenbrock L, Heinks A, Schwenk M, Bauer J. Technology-based measurements for screening, monitoring and preventing frailty. Zeitschrift für Gerontologie und Geriatrie 2016;49(7):581 View
  12. Mateos-Angulo A, Galán-Mercant A, Cuesta-Vargas A. Kinematic Mobile Drop Jump Analysis at Different Heights Based on a Smartphone Inertial Sensor. Journal of Human Kinetics 2020;73(1):57 View
  13. Cattelani L, Palumbo P, Palmerini L, Bandinelli S, Becker C, Chesani F, Chiari L. FRAT-up, a Fall-Risk Assessment Tool for Elderly People Living in the Community. Journal of Medical Internet Research 2015;17(2):e41 View
  14. Tedesco S, Barton J, O’Flynn B. A Review of Activity Trackers for Senior Citizens: Research Perspectives, Commercial Landscape and the Role of the Insurance Industry. Sensors 2017;17(6):1277 View
  15. Almogren A. RETRACTED ARTICLE: An automated and intelligent Parkinson disease monitoring system using wearable computing and cloud technology. Cluster Computing 2019;22(S1):2309 View
  16. Cuesta-Vargas A, Pajares B, Trinidad-Fernandez M, Alba E, Roldan-Jiménez C. Inertial Sensors Embedded in Smartphones as a Tool for Fatigue Assessment Based on Acceleration in Survivors of Breast Cancer. Physical Therapy 2020;100(3):447 View
  17. Pan D, Dhall R, Lieberman A, Petitti D. A Mobile Cloud-Based Parkinson’s Disease Assessment System for Home-Based Monitoring. JMIR mHealth and uHealth 2015;3(1):e29 View
  18. Hellec J, Chorin F, Castagnetti A, Colson S. Sit-To-Stand Movement Evaluated Using an Inertial Measurement Unit Embedded in Smart Glasses—A Validation Study. Sensors 2020;20(18):5019 View
  19. Campillay Guzmán J, Guzmán Silva R, Guzmán-Venegas R. Reproducibilidad de los tiempos de ejecución de la prueba de Timed Up and Go , medidos con acelerómetros de smartphones en personas mayores residentes en la comunidad. Revista Española de Geriatría y Gerontología 2017;52(5):249 View
  20. Alvaro M, Alejandro G, Ignacio C. KINEMATIC ANALYSIS BY GENDER IN DIFFERENT JUMP TESTS BASED ON A SMARTPHONE INERTIAL SENSOR. Revista Brasileira de Medicina do Esporte 2018;24(4):263 View
  21. Cobo A, Villalba-Mora E, Hayn D, Ferre X, Pérez-Rodríguez R, Sánchez-Sánchez A, Bernabé-Espiga R, Sánchez-Sánchez J, López-Diez-Picazo A, Moral C, Rodriguez-Mañas L. Portable Ultrasound-Based Device for Detecting Older Adults’ Sit-to-Stand Transitions in Unsupervised 30-Second Chair–Stand Tests. Sensors 2020;20(7):1975 View
  22. Cobo A, Villalba-Mora E, Pérez-Rodríguez R, Ferre X, Rodríguez-Mañas L. Unobtrusive Sensors for the Assessment of Older Adult’s Frailty: A Scoping Review. Sensors 2021;21(9):2983 View
  23. Vavasour G, Giggins O, Doyle J, Kelly D. How wearable sensors have been utilised to evaluate frailty in older adults: a systematic review. Journal of NeuroEngineering and Rehabilitation 2021;18(1) View
  24. Hsu Y, Wang H, Zhao Y, Chen F, Tsui K. Automatic Recognition and Analysis of Balance Activity in Community-Dwelling Older Adults: Algorithm Validation. Journal of Medical Internet Research 2021;23(12):e30135 View
  25. Minici D, Cola G, Giordano A, Antoci S, Girardi E, Bari M, Avvenuti M. Towards Automated Assessment of Frailty Status Using a Wrist-Worn Device. IEEE Journal of Biomedical and Health Informatics 2022;26(3):1013 View
  26. Piche E, Chorin F, Gerus P, Jaafar A, Reneaud N, Guerin O, Zory R. Validity of a simple sit-to-stand method for assessing force-velocity profile in older adults. Experimental Gerontology 2021;156:111595 View
  27. Fastame M, Mulas I, Putzu V, Asoni G, Viale D, Mameli I, Pau M. Executive and Motor Functions in Older Individuals with Cognitive Impairment. Behavioral Sciences 2022;12(7):214 View
  28. Anzai E, Ren D, Cazenille L, Aubert-Kato N, Tripette J, Ohta Y. Random forest algorithms to classify frailty and falling history in seniors using plantar pressure measurement insoles: a large-scale feasibility study. BMC Geriatrics 2022;22(1) View
  29. Fu S, Duan T, Hou M, Yang F, Chai Y, Chen Y, Liu B, Ma Y, Liu A, Wang X, Chen L. Postural Balance in Individuals With Knee Osteoarthritis During Stand-to-Sit Task. Frontiers in Human Neuroscience 2021;15 View
  30. Pau M, Mulas I, Putzu V, Asoni G, Viale D, Mameli I, Allali G. Functional mobility in older women with and without motoric cognitive risk syndrome: a quantitative assessment using wearable inertial sensors. Journal of Gerontology and Geriatrics 2022;70(1):1 View
  31. Wang D, Gu X, Yu H. Sensors and algorithms for locomotion intention detection of lower limb exoskeletons. Medical Engineering & Physics 2023;113:103960 View
  32. Greene B, Doheny E, McManus K, Caulfield B. Estimating balance, cognitive function, and falls risk using wearable sensors and the sit-to-stand test. Wearable Technologies 2022;3 View
  33. Velazquez-Diaz D, Arco J, Ortiz A, Pérez-Cabezas V, Lucena-Anton D, Moral-Munoz J, Galán-Mercant A. Use of Artificial Intelligence in the Identification and Diagnosis of Frailty Syndrome in Older Adults: Scoping Review. Journal of Medical Internet Research 2023;25:e47346 View
  34. Pradeep Kumar D, Najafi B, Laksari K, Toosizadeh N. Sensor-Based Assessment of Variability in Daily Physical Activity and Frailty. Gerontology 2023;69(9):1147 View
  35. Pan J, Huang W, Huang Z, Luan J, Zhang X, Liao B. Biomechanical analysis of lower limbs during stand-to-sit tasks in patients with early-stage knee osteoarthritis. Frontiers in Bioengineering and Biotechnology 2023;11 View

Books/Policy Documents

  1. LeMoyne R, Mastroianni T. Wireless MEMS Networks and Applications. View
  2. LeMoyne R, Mastroianni T. Wearable and Wireless Systems for Healthcare I. View