A Wearable Pointing Device Using EMG Signals

Ogino, Hirotaka; Arita, Jun; Tsuji, Toshio

doi:10.20965/jrm.2005.p0173

Cited by 14 publications

(2 citation statements)

References 7 publications

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“…Vision-based gesture recognition obtains gesture information in a non-contact manner and can be applied to a wider range of fields. However, wearable and vision-based gesture recognition methods have disadvantages, including poor user experience and vulnerability to environmental factors such as illumination [ 1 , 4 ]. Wearable electromyography (EMG) signal control systems require electrodes to be stuck onto the forearm or wrist, which requires skin cleanliness and electrode performance with certain use restrictions [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics

Tang

Wang

et al. 2018

Sensors

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Non-contact human-computer interactions (HCI) based on hand gestures have been widely investigated. Here, we present a novel method to locate the real-time position of the hand using the electrostatics of the human body. This method has many advantages, including a delay of less than one millisecond, low cost, and does not require a camera or wearable devices. A formula is first created to sense array signals with five spherical electrodes. Next, a solving algorithm for the real-time measured hand position is introduced and solving equations for three-dimensional coordinates of hand position are obtained. A non-contact real-time hand position sensing system was established to perform verification experiments, and the principle error of the algorithm and the systematic noise were also analyzed. The results show that this novel technology can determine the dynamic parameters of hand movements with good robustness to meet the requirements of complicated HCI.

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Section: Introductionmentioning

confidence: 99%

Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics

Tang

Wang

et al. 2018

Sensors

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“…(6) Recently, the EMG has opened up new possibilities for other human-computer interfaces in the fields of augmentative and alternative communication (7)(8)(9)(10) and environmental control. (11) The EMG contains information on muscle recruitment, timing pattern, and force. Therefore, the EMG is useful as an input signal for human adaptive mechatronics.…”

Section: Introductionmentioning

confidence: 99%

Feasibility of Capacitive Sensing of Surface Electromyographic Potential through Cloth

Ueno

Yamaguchi²,

Iida³

et al. 2012

Sensors and Materials

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A capacitive sensing method was developed for sensing surface electromyographic potential (sEMG) through a thin cloth. The method is based on capacitive coupling involving fabric electrodes, the cloth, and the skin of the subject. A proposed measuring device was assembled by modifying the previously developed instrument for electrocardiographic potential. Experimental results showed that sEMG obtained with the proposed system was clearly visible and showed firings synchronized with sEMG simultaneously measured with a commercial device and that the spectral powers of both sEMGs were almost identical. These results demonstrated the potential of the proposed method to measure sEMG through cloth. The method enables the discomfort due to conventional skin-to-electrode coupling to be eliminated, although the signal quality, such as the signal-to-noise ratio (S/N), is slightly decreased with the cloth barrier.

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