Edinburgh Neuroprosthetics Laboratory, School of Informatics, The University of Edinburgh, Edinburgh EH8 9AB, UK.
Intelligent Sensing Laboratory, School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
Philos Trans A Math Phys Eng Sci. 2022 Jul 25;380(2228):20210005. doi: 10.1098/rsta.2021.0005. Epub 2022 Jun 6.
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'.
上肢假肢的研究通常以实验室为基础。有证据表明,研究尚未导致满足用户需求的假肢。用户、临床医生和制造商之间低效的沟通循环限制了研究人员在改进创新时可以使用的定量和定性数据的数量。本文首次展示了一种替代范式,根据用户需求进行远程、超越实验室的假肢研究是可行的。具体来说,所提出的物联网设置允许通过 Wi-Fi 和商业云门户进行远程数据收集、实时可视化和假肢重新编程。通过仪表板,用户可以调整设备的配置并向假肢数据添加上下文信息。我们通过三个健全参与者的实时实验评估了该演示器。结果承诺通过互联网进行上下文数据收集和系统更新的潜力,这可能为算法训练提供实际数据,并降低送回家试验的复杂性。本文是主题为“高级神经技术:为健康和福祉转化创新”的一部分。