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Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to Multi-Grasp Prosthetic Hands.

Gonzalez-Vargas J, Dosen S, Amsuess S, Yu W, Farina D - PLoS ONE (2015)

Bottom Line: 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.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.The results showed that the performance of the novel HMI concept was comparable or, for some outcome measures, better than the classic myoelectric interfaces.

View Article: PubMed Central - PubMed

Affiliation: Center for Frontier Medical Engineering, Chiba University, Chiba, Japan.

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.

No MeSH data available.


Related in: MedlinePlus

Menu interface modes.a. Mode 1, the grasp types and sizes were simultaneously presented to the user by sequentially activating the electrodes (grasp type), first at high (large size) and then at low intensity (small size). b. In Mode 2, only the grasp types were presented first, by activating the electrodes sequentially (low intensity), and when the grasp type was selected (elbow flexion), grasp sizes were presented by activating a single electrode cyclically at high and low intensity.
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pone.0127528.g004: Menu interface modes.a. Mode 1, the grasp types and sizes were simultaneously presented to the user by sequentially activating the electrodes (grasp type), first at high (large size) and then at low intensity (small size). b. In Mode 2, only the grasp types were presented first, by activating the electrodes sequentially (low intensity), and when the grasp type was selected (elbow flexion), grasp sizes were presented by activating a single electrode cyclically at high and low intensity.

Mentions: System activation phase (ACTIVATION). The system was turned off by default (state = OFF), and therefore, the first step was the system activation (state = GRASP_DISPLAY). For this, the user had to perform a brief and small-amplitude supination and pronation motion of the forearm while the arm was placed in the starting position (time 0 in Fig 4). Repeating the same motion deactivated the control system (state = OFF). The assumption was that the user would turn on the system and start the electrotactile menu only when he/she actually intends to use the prosthesis.


Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to Multi-Grasp Prosthetic Hands.

Gonzalez-Vargas J, Dosen S, Amsuess S, Yu W, Farina D - PLoS ONE (2015)

Menu interface modes.a. Mode 1, the grasp types and sizes were simultaneously presented to the user by sequentially activating the electrodes (grasp type), first at high (large size) and then at low intensity (small size). b. In Mode 2, only the grasp types were presented first, by activating the electrodes sequentially (low intensity), and when the grasp type was selected (elbow flexion), grasp sizes were presented by activating a single electrode cyclically at high and low intensity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4466571&req=5

pone.0127528.g004: Menu interface modes.a. Mode 1, the grasp types and sizes were simultaneously presented to the user by sequentially activating the electrodes (grasp type), first at high (large size) and then at low intensity (small size). b. In Mode 2, only the grasp types were presented first, by activating the electrodes sequentially (low intensity), and when the grasp type was selected (elbow flexion), grasp sizes were presented by activating a single electrode cyclically at high and low intensity.
Mentions: System activation phase (ACTIVATION). The system was turned off by default (state = OFF), and therefore, the first step was the system activation (state = GRASP_DISPLAY). For this, the user had to perform a brief and small-amplitude supination and pronation motion of the forearm while the arm was placed in the starting position (time 0 in Fig 4). Repeating the same motion deactivated the control system (state = OFF). The assumption was that the user would turn on the system and start the electrotactile menu only when he/she actually intends to use the prosthesis.

Bottom Line: 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.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.The results showed that the performance of the novel HMI concept was comparable or, for some outcome measures, better than the classic myoelectric interfaces.

View Article: PubMed Central - PubMed

Affiliation: Center for Frontier Medical Engineering, Chiba University, Chiba, Japan.

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.

No MeSH data available.


Related in: MedlinePlus