Research Library

Bioelectric potentials provide an intuitive source of control in human-machine interfaces. In this work an open source low-cost system for bioelectric signals acquisition and processing was developed. A single module can acquire up to 8 differential or single-ended channels, and several modules can be daisy-chained together. Opto-isolated USB communication was included in the design to interface safely with a personal computer. Embedded digital processing was used for float conversion and filtering. The high-level software was implemented as a complementary part of BioPatRec, an existing open source project. Source files for the PCB, firmware, and high-level software are available online (GitHub: ADS_BP). This integration provides a low-cost, open source and complete system for research on intuitive myoelectric control.

This chapter provides an overview on the use of Virtual Reality (VR) in rehabilitation with respect to recent neuroscience and physical therapy reviews of individuals with motor impairments. A wide range of technologies have been employed to provide rehabilitation supported by VR. Several studies have found evidence of the benefits of VR rehabilitation technologies. However, support for their efficacy is still limited due the lack of generalizable results and the uncoordinated effort of many individual, heterogeneous studies that have been conducted. Although VR has clear potential as a rehabilitation tool to improve treatment outcomes, future trials need to take into account the individual perspective of each patient group and consolidate research methodologies across trials to allow for stronger conclusions across the heterogeneous field of neurorehabilitation.

Electric signals from the muscles can be analysed using artificial intelligence to control artificial limbs, but researchers use different development platforms to develop these techniques which slows down progress and makes it harder to compare results. We developed a shared (open source) platform called BioPatRec to foster collaboration and demonstrated its capabilities by analysing signals from 17 able-bodied participants using various techniques. BioPatRec can be used to record signals, process them, analyse them with artificial intelligence and control virtual or mechanical limbs. BioPatrec is freely available and used in three different continents with the hope to accelerate the development of better algorithms to improve the lives of those with limb loss.