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

Portable and Mobile Technologies for Rehabilitation (142) Fitness Trackers and Smart Pedometers/Accelerometers (541) mHealth for Data Collection and Research (912) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1308) Wearable Devices and Sensors (816)

Published on in Vol 7, No 2 (2020): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17986, first published .
The Impact of Reducing the Number of Wearable Devices on Measuring Gait in Parkinson Disease: Noninterventional Exploratory Study

The Impact of Reducing the Number of Wearable Devices on Measuring Gait in Parkinson Disease: Noninterventional Exploratory Study

The Impact of Reducing the Number of Wearable Devices on Measuring Gait in Parkinson Disease: Noninterventional Exploratory Study

Authors of this article:

Matthew Czech1 Author Orcid Image ;   Charmaine Demanuele1 Author Orcid Image ;   Michael Kelley Erb1 Author Orcid Image ;   Vesper Ramos1 Author Orcid Image ;   Hao Zhang1 Author Orcid Image ;   Bryan Ho2 Author Orcid Image ;   Shyamal Patel1 Author Orcid Image
Article Authors Cited by (13) Tweetations (2) Metrics

Journals

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  8. Trabassi D, Serrao M, Varrecchia T, Ranavolo A, Coppola G, De Icco R, Tassorelli C, Castiglia S. Machine Learning Approach to Support the Detection of Parkinson’s Disease in IMU-Based Gait Analysis. Sensors 2022;22(10):3700 View
  9. Zhang T, Meng D, Lyu D, Fang B. The Efficacy of Wearable Cueing Devices on Gait and Motor Function in Parkinson Disease: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Archives of Physical Medicine and Rehabilitation 2024;105(2):369 View
  10. Ymeri G, Salvi D, Olsson C, Wassenburg M, Tsanas A, Svenningsson P. Quantifying Parkinson’s disease severity using mobile wearable devices and machine learning: the ParkApp pilot study protocol. BMJ Open 2023;13(12):e077766 View
  11. Zampogna A, Borzì L, Rinaldi D, Artusi C, Imbalzano G, Patera M, Lopiano L, Pontieri F, Olmo G, Suppa A. Unveiling the Unpredictable in Parkinson’s Disease: Sensor-Based Monitoring of Dyskinesias and Freezing of Gait in Daily Life. Bioengineering 2024;11(5):440 View
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Books/Policy Documents

  1. Seemann J, Loris T, Weber L, Synofzik M, Giese M, Ilg W. Artificial Neural Networks and Machine Learning – ICANN 2023. View