title: Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to Multi-Grasp Prosthetic Hands.
abstract: Modern assistive devices are very sophisticated systems with multiple degrees of freedom. However, an effective and user-friendly control of these systems is still an open problem since conventional human-machine interfaces (HMI) cannot easily accommodate the system's complexity. In HMIs, the user is responsible for generating unique patterns of command signals directly triggering the device functions. This approach can be difficult to implement when there are many functions (necessitating many command patterns) and/or the user has a considerable impairment (limited number of available signal sources). In this study, we propose a novel concept for a general-purpose HMI where the controller and the user communicate bidirectionally to select the desired function. The system first presents possible choices to the user via electro-tactile stimulation; the user then acknowledges the desired choice by generating a single command signal. Therefore, the proposed approach simplifies the user communication interface (one signal to generate), decoding (one signal to recognize), and allows selecting from a number of options. To demonstrate the new concept the method was used in one particular application, namely, to implement the control of all the relevant functions in a state of the art commercial prosthetic hand without using any myoelectric channels. We performed experiments in healthy subjects and with one amputee to test the feasibility of the novel approach. The results showed that the performance of the novel HMI concept was comparable or, for some outcome measures, better than the classic myoelectric interfaces. The presented approach has a general applicability and the obtained results point out that it could be used to operate various assistive systems (e.g., prosthesis vs. wheelchair), or it could be integrated into other control schemes (e.g., myoelectric control, brain-machine interfaces) in order to improve the usability of existing low-bandwidth HMIs.
authors.affiliation: Center for Frontier Medical Engineering, Chiba University, Chiba, Japan.
authors.forename: Jose
authors.initials: J
authors.lastname: Gonzalez-Vargas
authors.affiliation: Department of Neurorehabilitation, University Medical Göttingen, Göttingen, Germany.
authors.forename: Strahinja
authors.initials: S
authors.lastname: Dosen
authors.affiliation: Department of Neurorehabilitation, University Medical Göttingen, Göttingen, Germany.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Amsuess
authors.affiliation: Center for Frontier Medical Engineering, Chiba University, Chiba, Japan.
authors.forename: Wenwei
authors.initials: W
authors.lastname: Yu
authors.affiliation: Department of Neurorehabilitation, University Medical Göttingen, Göttingen, Germany.
authors.forename: Dario
authors.initials: D
authors.lastname: Farina
mesh_terms: D000328:Adult; D001186:Artificial Limbs; D062207:Brain-Computer Interfaces; D004576:Electromyography; D005260:Female; D006225:Hand / Q000502:physiology*; D018737:Hand Strength; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D008875:Middle Aged; D014584:User-Computer Interface