Erratum: Fall detection in individuals with lower limb amputations using mobile phones: Machine learning enhances robustness for real-world applications (JMIR mHealth and uHealth (2017) 5:10 (e151) DOI: 10.2196/mhealth.8201)

Nicholas Shawen, Luca Lonini*, Chaithanya Krishna Mummidisetty, Ilona Shparii, Mark V. Albert, Konrad Kording, Arun Jayaraman

*Corresponding author for this work

Research output: Contribution to journalComment/debatepeer-review

Abstract

The authors are thankful to Mark Begale and Christopher J Karr from CBITs for their technical assistance with the Purple Robot phone app. The authors would also like to thank Dr Saninder Kaur, Kelsey Greenoe, Ashley Adamczyk, and Ryan Griesenauer for their assistance during participant recruitment and data collection. This study was funded by the National Institute of Health - NIBIB grant 5 R01 EB019406-04 and by the Max Näder Rehabilitation Technologies and Outcomes Research Center of the Shirley Ryan Ability Lab (formerly Rehabilitation Institute of Chicago). The corrected article will appear in the online version of the paper on the JMIR website on December 20, 2017, together with the publication of this correction notice. Because this was made after submission to PubMed Central, the corrected article will also be re-submitted to PubMed Central.

Original languageEnglish (US)
Article numbere167
JournalJMIR mHealth and uHealth
Volume5
Issue number12
DOIs
StatePublished - Dec 2017

ASJC Scopus subject areas

  • Health Informatics

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