New control method for power-assisted wheelchair based on upper extremity movement using surface myoelectric signal

Oonishi, Yoshinori; Oh, Sehoon; Hon, Y.C.

doi:10.1109/amc.2008.4516117

Cited by 13 publications

(1 citation statement)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, several control techniques have been investigated and various types of bio-signals are used in each technique depending on its function. EMG is one of the commonly used bio-signals used in bio-robotics applications such as prosthetics [4,5], exoskeletons [6,7] and wheelchairs [8,9]. However, EMG based control methods are not preferred to use alone because of muscle fatigue problem which effects and disturbs the EMG signal amplitude [10,11].…”

Section: Introductionmentioning

confidence: 99%

Hybrid EEG-EMG based brain computer interface (BCI) system for real-time robotic arm control

Abdullah¹,

Khan²,

Serpelloni³

et al. 2019

Adv. Mater. Lett.

View full text Add to dashboard Cite

Nowadays, bio-signal based BCI systems are widely being used in healthcare systems and hence proven to be an effective tool in rehabilitation engineering to assist disabled people in improving their quality of life [1]. In this research work, handicapped people with above hand amputee have been targeted and hence non-invasive EEG and EMG biosensors are used to design wireless hybrid BCI system. The presented hybrid system is able to control real-time movement of robotic arm via combined effect of brain waves (attention and meditation mind states) and wrist muscles movements of healthy arm as command signal. The system operates the robotic arm within 3 degree of freedom (DOF) motion which corresponds to movement of shoulder (internal and external rotation), elbow (flexion and extension) and wrist (Gripper open and close) joint. It has been experimentally tested on 4 subjects with upper limb amputee (having one healthy arm) after training period of one day. On receiving the input signals from EEG and EMG sensors, subjects have successfully controlled the movements of the robotic arm with accuracy of 70% to 90%. In order to validate the obtained results, a potentiometer has been fixed on robotic arm and angular motion of shoulder and elbow joint is recorded (actual motion) and compared with results of the BCI system (required motion). The comparison shows high resemblance between actual and required motion which reflects the reliability of the system. In addition, apart from robotic prototype, its 2D modelled is also designed on visual studio. The presented preliminary experimental results show that the motorized prosthetic prototype movement due to mind and muscle control is in accordance with the 2D modelled virtual arm permitting to improve its real-time adoption for rehabilitation.

show abstract

Section: Introductionmentioning

confidence: 99%

Hybrid EEG-EMG based brain computer interface (BCI) system for real-time robotic arm control

Abdullah¹,

Khan²,

Serpelloni³

et al. 2019

Adv. Mater. Lett.

View full text Add to dashboard Cite

show abstract

Robotics and High-Throughput Techniques

Hasan

Safdar

Zahid

et al. 2018

Omics Technologies and Bio-Engineering

View full text Add to dashboard Cite

High-level hands-free control of wheelchair – a review

Sharmila

2016

Journal of Medical Engineering & Technology

View full text Add to dashboard Cite

A vital perception in designing human-machine interfaces for people with disabilities is hands-free control. It is important in setting up communication among a machine and the part of human body. Nowadays, hands-free control is extensively used to help disabled people to control the wheelchair. The hands-free control functions are not only helpful to elderly and disabled, but also useful for normal people who might require using their hands for other tasks at the same time. As a result, normal people are capable of manipulating multiple tasks at the same time. The wheelchair is manoeuvred using brainwaves, eyes and facial muscles movements, voice, tongue, gesture. The mobility using a powered wheelchair improves the quality of life of the aged people and the people with mobility impairments significantly. These powered wheelchairs can be actuated using various high-level control interfaces. In this review, the use of natural biological signals and non-biological signal to do the hands-free control of powered wheelchair is presented in this article.

show abstract

New control method for power-assisted wheelchair based on upper extremity movement using surface myoelectric signal

Cited by 13 publications

References 2 publications

Hybrid EEG-EMG based brain computer interface (BCI) system for real-time robotic arm control

Hybrid EEG-EMG based brain computer interface (BCI) system for real-time robotic arm control

Robotics and High-Throughput Techniques

High-level hands-free control of wheelchair – a review

Contact Info

Product

Resources

About