This paper is in the following e-collection/theme issue:

mHealth for Data Collection and Research (981) Wearable Devices and Sensors (903) Portable and Mobile Technologies for Rehabilitation (156)

Published on in Vol 3, No 1 (2015): Jan-Mar

Validation of a Portable Device for Mapping Motor and Gait Disturbances in Parkinson’s Disease

Validation of a Portable Device for Mapping Motor and Gait Disturbances in Parkinson’s Disease

Validation of a Portable Device for Mapping Motor and Gait Disturbances in Parkinson’s Disease

Authors of this article:

Alejandro Rodríguez-Molinero1, 2 Author Orcid Image ;   Albert Samà3 Author Orcid Image ;   David A Pérez-Martínez4 Author Orcid Image ;   Carlos Pérez López3 Author Orcid Image ;   Jaume Romagosa3 Author Orcid Image ;   Àngels Bayés5 Author Orcid Image ;   Pilar Sanz6 Author Orcid Image ;   Matilde Calopa7 Author Orcid Image ;   César Gálvez-Barrón8 Author Orcid Image ;   Eva de Mingo8 Author Orcid Image ;   Daniel Rodríguez Martín3 Author Orcid Image ;   Natalia Gonzalo8 Author Orcid Image ;   Francesc Formiga9 Author Orcid Image ;   Joan Cabestany3 Author Orcid Image ;   Andreu Català3 Author Orcid Image
Article Authors Cited by (48) Tweetations (7) Metrics

Journals

  1. Porciuncula F, Roto A, Kumar D, Davis I, Roy S, Walsh C, Awad L. Wearable Movement Sensors for Rehabilitation: A Focused Review of Technological and Clinical Advances. PM&R 2018;10(9S2) View
  2. Gurchiek R, Choquette R, Beynnon B, Slauterbeck J, Tourville T, Toth M, McGinnis R. Open-Source Remote Gait Analysis: A Post-Surgery Patient Monitoring Application. Scientific Reports 2019;9(1) View
  3. Kassavetis P, Saifee T, Roussos G, Drougkas L, Kojovic M, Rothwell J, Edwards M, Bhatia K. Developing a Tool for Remote Digital Assessment of Parkinson's Disease. Movement Disorders Clinical Practice 2016;3(1):59 View
  4. di Biase L, Di Santo A, Caminiti M, De Liso A, Shah S, Ricci L, Di Lazzaro V. Gait Analysis in Parkinson’s Disease: An Overview of the Most Accurate Markers for Diagnosis and Symptoms Monitoring. Sensors 2020;20(12):3529 View
  5. Morgan C, Rolinski M, McNaney R, Jones B, Rochester L, Maetzler W, Craddock I, Whone A. Systematic Review Looking at the Use of Technology to Measure Free-Living Symptom and Activity Outcomes in Parkinson’s Disease in the Home or a Home-like Environment. Journal of Parkinson's Disease 2020;10(2):429 View
  6. Almogren A. RETRACTED ARTICLE: An automated and intelligent Parkinson disease monitoring system using wearable computing and cloud technology.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
  7. Moridani M, Shahrestani N. Linear and Nonlinear Analysis of Gait Motor Signal to Diagnose Parkinson’s Disease. International Journal of Bioscience, Biochemistry and Bioinformatics 2018;8(4):202 View
  8. Rodríguez-Martín D, Pérez-López C, Samà A, Català A, Moreno Arostegui J, Cabestany J, Mestre B, Alcaine S, Prats A, Cruz Crespo M, Bayés À. A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients. Sensors 2017;17(4):827 View
  9. Silva de Lima A, Evers L, Hahn T, de Vries N, Daeschler M, Boroojerdi B, Terricabras D, Little M, Bloem B, Faber M. Impact of motor fluctuations on real-life gait in Parkinson’s patients. Gait & Posture 2018;62:388 View
  10. Johansson D, Malmgren K, Alt Murphy M. Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: a mixed-methods systematic review. Journal of Neurology 2018;265(8):1740 View
  11. Pérez-López C, Samà A, Rodríguez-Martín D, Català A, Cabestany J, Moreno-Arostegui J, De Mingo E, Rodríguez-Molinero A. Assessing Motor Fluctuations in Parkinson’s Disease Patients Based on a Single Inertial Sensor. Sensors 2016;16(12):2132 View
  12. Aich S, Youn J, Chakraborty S, Pradhan P, Park J, Park S, Park J. A Supervised Machine Learning Approach to Detect the On/Off State in Parkinson’s Disease Using Wearable Based Gait Signals. Diagnostics 2020;10(6):421 View
  13. Rodríguez-Molinero A, Samà A, Pérez-López C, Rodríguez-Martín D, Alcaine S, Mestre B, Quispe P, Giuliani B, Vainstein G, Browne P, Sweeney D, Quinlan L, Moreno Arostegui J, Bayes À, Lewy H, Costa A, Annicchiarico R, Counihan T, Laighin G, Cabestany J. Analysis of Correlation between an Accelerometer-Based Algorithm for Detecting Parkinsonian Gait and UPDRS Subscales. Frontiers in Neurology 2017;8 View
  14. Thorp J, Adamczyk P, Ploeg H, Pickett K. Monitoring Motor Symptoms During Activities of Daily Living in Individuals With Parkinson's Disease. Frontiers in Neurology 2018;9 View
  15. Rodríguez-Molinero A, Pérez-Martínez D, Gálvez-Barrón C, Hernández-Vara J, Martínez-Castrillo J, Álvarez R, de Fabregues O, Samà A, Pérez-López C, Romagosa J, Bregman J. Remote control of apomorphine infusion rate in Parkinson's disease: Real-time dose variations according to the patients' motor state. A proof of concept. Parkinsonism & Related Disorders 2015;21(8):996 View
  16. Belić M, Bobić V, Badža M, Šolaja N, Đurić-Jovičić M, Kostić V. Artificial intelligence for assisting diagnostics and assessment of Parkinson’s disease—A review. Clinical Neurology and Neurosurgery 2019;184:105442 View
  17. Hssayeni M, Burack M, Jimenez-Shahed J, Ghoraani B. Assessment of response to medication in individuals with Parkinson’s disease. Medical Engineering & Physics 2019;67:33 View
  18. Rodríguez-Molinero A, Pérez-López C, Samà A, Rodríguez-Martín D, Alcaine S, Mestre B, Quispe P, Giuliani B, Vainstein G, Browne P, Sweeney D, Quinlan L, Arostegui J, Bayes À, Lewy H, Costa A, Annicchiarico R, Counihan T, Laighin G, Cabestany J. Estimating dyskinesia severity in Parkinson’s disease by using a waist-worn sensor: concurrent validity study. Scientific Reports 2019;9(1) View
  19. 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
  20. Bayés À, Samá A, Prats A, Pérez-López C, Crespo-Maraver M, Moreno J, Alcaine S, Rodriguez-Molinero A, Mestre B, Quispe P, de Barros A, Castro R, Costa A, Annicchiarico R, Browne P, Counihan T, Lewy H, Vainstein G, Quinlan L, Sweeney D, ÓLaighin G, Rovira J, Rodrigue z-Martin D, Cabestany J. A “HOLTER” for Parkinson’s disease: Validation of the ability to detect on-off states using the REMPARK system. Gait & Posture 2018;59:1 View
  21. Punin C, Barzallo B, Clotet R, Bermeo A, Bravo M, Bermeo J, Llumiguano C. A Non-Invasive Medical Device for Parkinson’s Patients with Episodes of Freezing of Gait. Sensors 2019;19(3):737 View
  22. Ghoraani B, Hssayeni M, Bruack M, Jimenez-Shahed J. Multilevel Features for Sensor-Based Assessment of Motor Fluctuation in Parkinson's Disease Subjects. IEEE Journal of Biomedical and Health Informatics 2020;24(5):1284 View
  23. 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
  24. Lieber B, Taylor B, Appelboom G, McKhann G, Connolly E. Motion Sensors to Assess and Monitor Medical and Surgical Management of Parkinson Disease. World Neurosurgery 2015;84(2):561 View
  25. Samà A, Pérez-López C, Rodríguez-Martín D, Català A, Moreno-Aróstegui J, Cabestany J, de Mingo E, Rodríguez-Molinero A. Estimating bradykinesia severity in Parkinson's disease by analysing gait through a waist-worn sensor. Computers in Biology and Medicine 2017;84:114 View
  26. Santos García D, López Ariztegui N, Cubo E, Vinagre Aragón A, García-Ramos R, Borrué C, Fernández-Pajarín G, Caballol N, Cabo I, Barrios-López J, Hernández Vara J, Ávila Rivera M, Gasca-Salas C, Escalante S, Manrique de Lara P, Pérez Noguera R, Álvarez Sauco M, Sierra M, Monje M, Sánchez Ferro A, Novo Ponte S, Alonso-Frech F, Macías-García D, Legarda I, Rojo A, Álvarez Fernández I, Buongiorno M, Pastor P, García Ruíz P. Clinical utility of a personalized and long-term monitoring device for Parkinson's disease in a real clinical practice setting: An expert opinion survey on STAT-ON™. Neurología 2023;38(5):326 View
  27. Barrachina-Fernández M, Maitín A, Sánchez-Ávila C, Romero J. Wearable Technology to Detect Motor Fluctuations in Parkinson’s Disease Patients: Current State and Challenges. Sensors 2021;21(12):4188 View
  28. Perrote F, Zeppa G, Coca H, Figueroa S, de Battista J. Evaluación de un sistema de sensores inerciales externos tipo Holter en pacientes con enfermedad de Parkinson en Argentina. Neurología Argentina 2021;13(3):153 View
  29. Alvarez F, Popa M, Solachidis V, Hernandez-Penaloza G, Belmonte-Hernandez A, Asteriadis S, Vretos N, Quintana M, Theodoridis T, Dotti D, Daras P. Behavior Analysis through Multimodal Sensing for Care of Parkinson’s and Alzheimer’s Patients. IEEE MultiMedia 2018;25(1):14 View
  30. Rodríguez-Molinero A, Hernández-Vara J, Miñarro A, Pérez-López C, Bayes-Rusiñol À, Martínez-Castrillo J, Pérez-Martínez D. Multicentre, randomised, single-blind, parallel group trial to compare the effectiveness of a Holter for Parkinson’s symptoms against other clinical monitoring methods: study protocol. BMJ Open 2021;11(7):e045272 View
  31. De Venuto D, Annese V, Mezzina G, Defazio G. FPGA-Based Embedded Cyber-Physical Platform to Assess Gait and Postural Stability in Parkinson’s Disease. IEEE Transactions on Components, Packaging and Manufacturing Technology 2018;8(7):1167 View
  32. Morita M. Biomarkers with digital technology and digital biomarkers for medication management. Drug Delivery System 2022;37(1):17 View
  33. Sun Y, Li L, Chen Y, Wang L, Zhai L, Sheng J, Liu T, Jin X. Feasibility and positive effects of scalp acupuncture for modulating motor and cerebral activity in Parkinson’s disease: A pilot study. NeuroRehabilitation 2022;51(3):467 View
  34. Habets J, Herff C, Kubben P, Kuijf M, Temel Y, Evers L, Bloem B, Starr P, Gilron R, Little S. Rapid Dynamic Naturalistic Monitoring of Bradykinesia in Parkinson’s Disease Using a Wrist-Worn Accelerometer. Sensors 2021;21(23):7876 View
  35. Rodríguez-Martín D, Cabestany J, Pérez-López C, Pie M, Calvet J, Samà A, Capra C, Català A, Rodríguez-Molinero A. A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ONTM. Frontiers in Neurology 2022;13 View
  36. Kenny L, Moore K, O' Riordan C, Fox S, Barton J, Tedesco S, Sica M, Crowe C, Alamäki A, Condell J, Nordström A, Timmons S. The Views and Needs of People With Parkinson Disease Regarding Wearable Devices for Disease Monitoring: Mixed Methods Exploration. JMIR Formative Research 2022;6(1):e27418 View
  37. Levin O, Iakovleva O, Coloman I, Kuzmina A. Could New Generations of Sensors Reshape the Management of Parkinson’s Disease?. Clinical and Translational Neuroscience 2021;5(2):18 View
  38. Guo C, Chiesa P, de Moor C, Fazeli M, Schofield T, Hofer K, Belachew S, Scotland A. Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review. Journal of Medical Internet Research 2022;24(11):e37683 View
  39. ZhuParris A, de Goede A, Yocarini I, Kraaij W, Groeneveld G, Doll R. Machine Learning Techniques for Developing Remotely Monitored Central Nervous System Biomarkers Using Wearable Sensors: A Narrative Literature Review. Sensors 2023;23(11):5243 View
  40. Moreau C, Rouaud T, Grabli D, Benatru I, Remy P, Marques A, Drapier S, Mariani L, Roze E, Devos D, Dupont G, Bereau M, Fabbri M. Overview on wearable sensors for the management of Parkinson’s disease. npj Parkinson's Disease 2023;9(1) View
  41. Santos García D, López Ariztegui N, Cubo E, Vinagre Aragón A, García-Ramos R, Borrué C, Fernández-Pajarín G, Caballol N, Cabo I, Barrios-López J, Hernández Vara J, Ávila Rivera M, Gasca-Salas C, Escalante S, Manrique de Lara P, Pérez Noguera R, Álvarez Sauco M, Sierra M, Monje M, Sánchez Ferro A, Novo Ponte S, Alonso-Frech F, Macías-García D, Legarda I, Rojo A, Álvarez Fernández I, Buongiorno M, Pastor P, García Ruíz P. Clinical utility of a personalized and long-term monitoring device for Parkinson's disease in a real clinical practice setting: An expert opinion survey on STAT-ON™. Neurología (English Edition) 2023;38(5):326 View
  42. Cox E, Wade R, Hodgson R, Fulbright H, Phung T, Meader N, Walker S, Rothery C, Simmonds M. Devices for remote continuous monitoring of people with Parkinson’s disease: a systematic review and cost-effectiveness analysis. Health Technology Assessment 2024:1 View
  43. Crowe C, Sica M, Kenny L, O’Flynn B, Scott Mueller D, Timmons S, Barton J, Tedesco S. Wearable-Enabled Algorithms for the Estimation of Parkinson’s Symptoms Evaluated in a Continuous Home Monitoring Setting Using Inertial Sensors. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2024;32:3828 View
  44. Bremer A. Der Einsatz von Wearables bei Menschen mit idiopathischem Parkinson-Syndrom. neuroreha 2024;16(04):187 View

Books/Policy Documents

  1. Pérez-López C, Samà A, Rodríguez-Martín D, Català A, Cabestany J, de Mingo E, Rodríguez-Molinero A. Advances in Computational Intelligence. View