Development of an EMG-Controlled Mobile Robot

Bisi, Stefano; Luca, Luca De; Shrestha, Bikash; Yang, Zhijun; Gandhi, Vaibhav

doi:10.3390/robotics7030036

Cited by 27 publications

(10 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Being the hand extremely important in one's life, an entire field of HMI is dedicated to hand gesture recognition applications (Arapi et al, 2018;Shukla et al, 2018). Generally, visual, electromyographic, or inertial sensors are the most used technologies for detecting hand gestures (Cho et al, 2017;Ghafoor et al, 2017;Bisi et al, 2018;Polfreman, 2018). Visual-based hand gesture recognition systems do not need any device to wear, allowing for extreme freedom of use.…”

Section: Introductionmentioning

confidence: 99%

“…They also require real-time processing of the raw sEMG signals to extrapolate useful features (e.g., sEMG envelope/RMS) (Parajuli et al, 2019). As example, Myo Armband by Thalmic Labs 1 , a commercial device based on eight sEMG sensors and an inertial platform, allows the user to interface via Bluetooth with PCs or mobile devices to control supported applications (Nymoen et al, 2015;Sathiyanarayanan and Rajan, 2016;Myoband, 2019) including robot motion (Bisi et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Piezoresistive Array Armband With Reduced Number of Sensors for Hand Gesture Recognition

et al. 2020

View full text Add to dashboard Cite

Human machine interfaces (HMIs) are employed in a broad range of applications, spanning from assistive devices for disability to remote manipulation and gaming controllers. In this study, a new piezoresistive sensors array armband is proposed for hand gesture recognition. The armband encloses only three sensors targeting specific forearm muscles, with the aim to discriminate eight hand movements. Each sensor is made by a force-sensitive resistor (FSR) with a dedicated mechanical coupler and is designed to sense muscle swelling during contraction. The armband is designed to be easily wearable and adjustable for any user and was tested on 10 volunteers. Hand gestures are classified by means of different machine learning algorithms, and classification performances are assessed applying both, the 10-fold and leave-one-out cross-validations. A linear support vector machine provided 96% mean accuracy across all participants. Ultimately, this classifier was implemented on an Arduino platform and allowed successful control for videogames in real-time. The low power consumption together with the high level of accuracy suggests the potential of this device for exergames commonly employed for neuromotor rehabilitation. The reduced number of sensors makes this HMI also suitable for hand-prosthesis control.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Piezoresistive Array Armband With Reduced Number of Sensors for Hand Gesture Recognition

et al. 2020

View full text Add to dashboard Cite

show abstract

“…A brain-computer interface utilizing the EEG signals is proposed in [14] to control a mobile robot remotely and in corridor environments [15]. A mobile robot control method using EMG signals as robot command is proposed in [16]. EMG not only can be utilized to control command but also has the ability to detect the intention of the person as feedback control.…”

Section: Introductionmentioning

confidence: 99%

A Muscle Teleoperation System of a Robotic Rollator Based on Bilateral Shared Control

Chen

Zhou

et al. 2020

IEEE Access

View full text Add to dashboard Cite

The approach that achieves the teleoperation between human muscle signals and the mobile robot is increasingly applied to transfer human muscle stiffness to enhance robotic performance. In this paper, we develop a mobile rollator control system applying a muscle teleoperation interface and a shared control method to enhance the obstacle avoidance in an effective way. In order to control intuitively, haptic feedback is utilized in the teleoperation interface and is integrated with EMG stiffness to provide a large composition force. Then the composition force is implemented with an artificial potential field method to keep the robotic rollator away from the obstacle in advance. This algorithm is superior to the traditional APF algorithm regardless of the required time and trajectory length. The experimental results demonstrate the effectiveness of the proposed muscle teleoperation system.

show abstract

“…In recent year, developments of mobile robot have been popular in research field. The authors in [1][2][3] have been developed mobile robot for various applications. Measuring of distance between one point to another point still using conventional measuring method which still using of measuring tape.…”

Section: Introductionmentioning

confidence: 99%

Development of mobile robot for measuring distance using optical quadrature encoder

Zahari

Mutalib

Affendi

et al. 2020

IJEECS

View full text Add to dashboard Cite

<span>This paper describes the design and development of a measuring tool using a mobile robot. At present, contractors are measuring distances using measuring tape which has few limitations. This includes using of another manpower or a marking flag. The Robot Measuring System is designed to measure distances at multiple conditions such as smooth and rough surface. An optical quadrature encoder is used as a sensor to measure the distances while a program is installed in Arduino Uno for reading and data collection. Graphical User Interface (GUI) was created using Android software so that the movement of the robot can be controlled using a smartphone within a Bluetooth range. An experiment was conducted to test the reliability in terms of accuracy and precision. The best accuracy and precision were obtained when the robot speed is at 90 cm/s on the plain tiles, 80 cm/s on the tar road and 90 cm/s on the grass surface. The robot speed needs to be adjusted accordingly based on the surfaces in order to get an accurate result. <br /> This paper proved that the robot measuring system was successfully designed, implemented and analyzed.</span>

show abstract

Development of an EMG-Controlled Mobile Robot

Cited by 27 publications

References 20 publications

A Piezoresistive Array Armband With Reduced Number of Sensors for Hand Gesture Recognition

A Piezoresistive Array Armband With Reduced Number of Sensors for Hand Gesture Recognition

A Muscle Teleoperation System of a Robotic Rollator Based on Bilateral Shared Control

Development of mobile robot for measuring distance using optical quadrature encoder

Contact Info

Product

Resources

About