Comparison between two control algorithms for EMG-based navigation

LaBarge, Erin; Fortunati, Jonathan; Sullivan, Meaghan; Bartels, Nathan; Zhang, Ronald; Sun, Yu

doi:10.1109/nebc.2010.5458223

Cited by 4 publications

(2 citation statements)

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“…There is a relevant background related to neuromuscular signals applied to Rehabilitation Technologies. Myoelectric signals (MES) have been proposed to command devices, such as robotic prostheses, or act as generic man-machine interfaces in many papers [ 1 – 5 ]. But prosthesis adaptation is a major drawback for the limb impaired [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals

Rosa

Alonso

Carrera

et al. 2010

Sensors

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This paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System), a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES) and, as a novelty, the myomechanic signals (MMS). In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals.

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Section: Introductionmentioning

confidence: 99%

Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals

Rosa

Alonso

Carrera

et al. 2010

Sensors

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show abstract

“…Centrando el análisis literario en las interfaces encargadas de la detección de señales EMG, aparecen trabajos con objetivos claramente similares. Así, [198] emplea señales EMG en sentido amplio, [187], [199] y [200] presentan interfaces que detectan guiños de los ojos, [201] y [189] detectan gestos faciales (movimientos de la boca y la frente), [202] utiliza señales de las manos y del cuello y, finalmente, [203] y [204] emplean señales del antebrazo. Nuevamente, estos sistemas se utilizan como interfaz para sistemas de movilidad, sillas de ruedas o sistemas robóticos, o para el control de ordenadores personales.…”

Section: Señales Emg/eog Durante El Movimiento Muscular Voluntariounclassified

Innovaciones en sistemas e interfaces humano-máquina: aplicación a las tecnologías de rehabilitación

González¹

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On detecting and adaptive timing for electromyogram based control signals

Lum

Pérez

Sun

2012

2012 38th Annual Northeast Bioengineering Conference (NEBEC)

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Comparison between two control algorithms for EMG-based navigation

Cited by 4 publications

References 1 publication

Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals

Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals

Innovaciones en sistemas e interfaces humano-máquina: aplicación a las tecnologías de rehabilitación

On detecting and adaptive timing for electromyogram based control signals

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