Development of tremor-suppression filter for meal-assist robot

Ohara, Eiichi; Yano, Ken'ichi; Horihata, Satoshi; Aoki, Takaaki; Nishimoto, Yuji

doi:10.1109/whc.2009.4810802

Cited by 8 publications

(1 citation statement)

References 8 publications

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“…[ [185][186][187] [ 161,188] [48, 100,112,140,166,183,185,[189][190][191][192] [48,50, 62, 140,[193][194][195][196] [39,40, 182,197] [198] [148,190,193,199] [117, 119,195] [ 21,56,176,178,[200][201][202][203] HCI-M [204] [ 205,206] [204, [207][208][209] [90, 208,210] [ 207,210] [ [211][212][213] HCI-TMI [183,214,…”

Section: Hci-hapmentioning

confidence: 99%

Two decades of assistive technologies to empower people with disability: a systematic mapping study

Enríquez,

Soria Morillo,

García-García

et al. 2023

Disability and Rehabilitation: Assistive Technology

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Section: Hci-hapmentioning

confidence: 99%

Two decades of assistive technologies to empower people with disability: a systematic mapping study

Enríquez,

Soria Morillo,

García-García

et al. 2023

Disability and Rehabilitation: Assistive Technology

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Tremor frequency based filter to extract voluntary movement of patients with essential tremor

Matsumoto

Seki

Ando

et al. 2012

2012 4th IEEE RAS &Amp; EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

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Analysis of EMG signals of patients with essential tremor focusing on the change of tremor frequency

Matsumoto

Seki

Ando

et al. 2012

2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Essential tremor is a disorder that causes involuntary oscillations in patients while engaging in actions or while maintaining a posture. ET patients have serious difficulties in performing activities of daily living such as eating food, drinking water, and writing. We have thus been developing an EMG-controlled exoskeletal robot to suppress tremors. The EMG signal of ET patients involves a mix of voluntary movement and tremor signals. To control the exoskeletal robot accurately, tremor signals must be removed from the patient's EMG signal. To date, we have been developing a filter to remove tremor signals from the patient's EMG. The design of this filter was based on the hypothesis that the rectified tremor signals are able to be approximated by a powered sine wave. This filter was found to have a large effect on removing tremor signals. However, tremor signals are generated both while performing voluntary movement and while maintaining a posture, and the filter was attenuating both signals. To control this robot accurately, the signal generated while performing voluntary movement is expected not to be attenuated. To accomplish this, we try to use a parameter that reflects a state of the patient's movement, performing a voluntary movement or maintaining a posture, as a switch to activate the powered sine filter. This paper provides an analysis of the favorable parameters. We focus on two parameters: the peak-to-peak interval of the rectified EMG signal, and the interval of the flat and low amplitude area of the rectified EMG signal. Through evaluation, it is affirmed that both parameters change with the state of the patient's movement. However, the latter parameter is superior to the former in terms of variability, which indicates that the interval of the flat and low amplitude area of the rectified EMG signal is a more favorable parameter to promote control of the exoskeletal robot. As a future work, we will mount the parameter to the algorithm and evaluate the robotic system.

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Development of tremor-suppression filter for meal-assist robot

Cited by 8 publications

References 8 publications

Two decades of assistive technologies to empower people with disability: a systematic mapping study

Two decades of assistive technologies to empower people with disability: a systematic mapping study

Tremor frequency based filter to extract voluntary movement of patients with essential tremor

Analysis of EMG signals of patients with essential tremor focusing on the change of tremor frequency

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