Enabling always-available input with muscle-computer interfaces

Saponas, T. Scott; Tan, Desney; Morris, Dan; Balakrishnan, Ravin; Turner, Jim; Landay, James A.

doi:10.1145/1622176.1622208

Cited by 279 publications

(137 citation statements)

References 18 publications

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“…Angle wrist = nfEMG extensor − nfEMG flexor (6) Finally, the estimated angle is changed x position required for controlling the horizontal motion of the paddle. And also the size of the paddle is determined by TCL.…”

Section: Transformation From Emg To Control Commandmentioning

confidence: 99%

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Control of a Brick-Breaking Game Using Electromyogram

Shin¹,

Kambara²,

Yoshimura³

et al. 2014

IJET

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Abstract-We aim to design a human-interface system to control a brick-breaking game using electromyographic (EMG) signals elicited by wrist movements. By measuring EMG signals, it is possible to predict the next stage of movement or force before motion. We filtered EMG signals through a finite impulse response filter with a cut-off frequency of 2.2 Hz. The resulting signal is very similar to the actual tension. We calculated subtraction between flexor and extensor muscles to obtain movement of the wrist. After simple calibration, the participant was able to control a paddle to break bricks in real time using wrist movements. Consequently, we succeeded in controlling the paddle of the game. The proposed system is expected to use as a rehabilitation tool or an entertainment system.

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Section: Transformation From Emg To Control Commandmentioning

confidence: 99%

“…al. (2009) have used EMG signals to classify gestures on free space [6]. They demonstrated the ability to discriminate finger gestures involved finger pinching, holding a mug, and carry a bag using only EMG signals from the forearm.…”

Section: Introductionmentioning

confidence: 99%

Control of a Brick-Breaking Game Using Electromyogram

Shin¹,

Kambara²,

Yoshimura³

et al. 2014

IJET

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“…Beside these classical input methods, last years have seen a growing interest in brain computer interfaces (BCIs) and more generally in biosignal based interfaces (e.g. muscle-computer interfaces [15]). …”

Section: Related Workmentioning

confidence: 99%

My-World-in-My-Tablet: An Architecture for People with Physical Impairment

Caruso

Cincotti

Leotta

et al. 2013

Human-Computer Interaction. Interaction Modalities and Techniques

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Mobile computing, coupled with advanced types of input interfaces, such as Brain Computer Interfaces (BCIs), can improve the quality of life of persons with different disabilities. In this paper we describe the architecture and the prototype of an assistive system, which allows users to express themselves and partially preserve their independence in controlling electrical devices at home. Even in absence of muscular functions, the proposed system would still allows the user some communication and control capabilities, by relaying on non-invasive BCIs. Experiments show how the fully-software realization of the system guarantees effective use with BCIs.

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“…Saponas [74] developed a muscle computer interaction system. The system used the forearm electromyograph (EMG) signals to classify the finger gesture using a support vector machine (SVM).…”

Section: • Inertial Sensorsmentioning

confidence: 99%

Sensor Fusion for Effective Hand Motion Detection

Abyarjoo¹

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Enabling always-available input with muscle-computer interfaces

Cited by 279 publications

References 18 publications

Control of a Brick-Breaking Game Using Electromyogram

Control of a Brick-Breaking Game Using Electromyogram

My-World-in-My-Tablet: An Architecture for People with Physical Impairment

Sensor Fusion for Effective Hand Motion Detection

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