Internet of Things for beyond-the-laboratory prosthetics research

Hancong Wu, Matthew Dyson, Kianoush Nazarpour

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Research on upper-limb prostheses is typically laboratory-based. Evidence indicates that research has not yet led to prostheses that meet user needs. Inefficient communication loops between users, clinicians and manufacturers limit the amount of quantitative and qualitative data that researchers can use in refining their innovations. This paper offers a first demonstration of an alternative paradigm by which remote, beyond-the-laboratory prosthesis research according to user needs is feasible. Specifically, the proposed Internet of Things setting allows remote data collection, real-time visualization and prosthesis reprogramming through Wi-Fi and a commercial cloud portal. Via a dashboard, the user can adjust the configuration of the device and append contextual information to the prosthetic data. We evaluated this demonstrator in real-time experiments with three able-bodied participants. Results promise the potential of contextual data collection and system update through the internet, which may provide real-life data for algorithm training and reduce the complexity of send-home trials. This article is part of the theme issue ‘Advanced Neurotechnologies: translating innovation for health and well-being’.
Original languageEnglish
Number of pages13
JournalPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Issue number2228
Early online date6 Jun 2022
Publication statusPublished - 25 Jul 2022

Keywords / Materials (for Non-textual outputs)

  • myoelectric control
  • internet of things
  • abstract decoder
  • Naive Bayes classifier


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