scholarly journals Noninvasive Electroencephalogram Based Control of a Robotic Arm for Reach and Grasp Tasks

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Jianjun Meng ◽  
Shuying Zhang ◽  
Angeliki Bekyo ◽  
Jaron Olsoe ◽  
Bryan Baxter ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Human Subjects ◽  
Brain Activity ◽  
Computer Interface ◽  
Robotic Arm ◽  
Multiple Degrees Of Freedom ◽  
Non Invasive ◽  
Prosthetic Limbs ◽  
Reach And Grasp ◽  
Low Dimensional

Abstract Brain-computer interface (BCI) technologies aim to provide a bridge between the human brain and external devices. Prior research using non-invasive BCI to control virtual objects, such as computer cursors and virtual helicopters, and real-world objects, such as wheelchairs and quadcopters, has demonstrated the promise of BCI technologies. However, controlling a robotic arm to complete reach-and-grasp tasks efficiently using non-invasive BCI has yet to be shown. In this study, we found that a group of 13 human subjects could willingly modulate brain activity to control a robotic arm with high accuracy for performing tasks requiring multiple degrees of freedom by combination of two sequential low dimensional controls. Subjects were able to effectively control reaching of the robotic arm through modulation of their brain rhythms within the span of only a few training sessions and maintained the ability to control the robotic arm over multiple months. Our results demonstrate the viability of human operation of prosthetic limbs using non-invasive BCI technology.

scholarly journals BIOMIMETIC DESIGN OF LOW STIFFNESS ACTUATOR SYSTEMS FOR PROSTHETIC LIMBS

2011 ◽  
Author(s):  
D. L. Russell ◽  
M. McTavish
Keyword(s):  
Mechanical Properties ◽  
Degrees Of Freedom ◽  
Analytical Techniques ◽  
Energetic Costs ◽  
Multiple Degrees Of Freedom ◽  
Prosthetic Limbs ◽  
Limb Stiffness ◽  
Human Arm ◽  
Biomimetic Approach ◽  
Low Stiffness

The various relationships that are possible between the mechanical properties of single actuators and the overall mechanism (in this case a human arm with or without a prosthetic elbow) are discussed. Graphical and analytical techniques for describing the range of overall limb stiffnesses that are achievable and for characterizing the overall limb stiffness have been developed. Using a biomimetic approach and, considering energetic costs, stability and complexity, the implications of choosing passive or active implementations of stiffness are discussed. These techniques and approaches are particularly applicable with redundant (agonist - antagonist) actuators and multiple degrees of freedom. Finally, a novel biomimetic approach for control is proposed.

scholarly journals Progress in the brain–computer interface: an interview with Bin He

2019 ◽  
Vol 7 (2) ◽  
pp. 480-483
Author(s):  
Chengyu Li ◽  
Weijie Zhao
Keyword(s):  
Science Fiction ◽  
Brain Computer Interface ◽  
Department Head ◽  
Computer Interface ◽  
Robotic Arm ◽  
The Public ◽  
Non Invasive ◽  
History Of ◽  
Human Brains ◽  
The Brain

Abstract What can the brain–computer interface (BCI) do? Wearing an electroencephalogram (EEG) headcap, you can control the flight of a drone in the laboratory by your thought; with electrodes inserted inside the brain, paralytic patients can drink by controlling a robotic arm with thinking. Both invasive and non-invasive BCI try to connect human brains to machines. In the past several decades, BCI technology has continued to develop, making science fiction into reality and laboratory inventions into indispensable gadgets. In July 2019, Neuralink, a company founded by Elon Musk, proposed a sewing machine-like device that can dig holes in the skull and implant 3072 electrodes onto the cortex, promising more accurate reading of what you are thinking, although many serious scientists consider the claim misleading to the public. Recently, National Science Review (NSR) interviewed Professor Bin He, the department head of Biomedical Engineering at Carnegie Mellon University, and a leading scientist in the non-invasive-BCI field. His team developed new methods for non-invasive BCI to control drones by thoughts. In 2019, Bin’s team demonstrated the control of a robotic arm to follow a continuously randomly moving target on the screen. In this interview, Bin He recounted the history of BCI, as well as the opportunities and challenges of non-invasive BCI.

scholarly journals Introduction to the identification of brain waves based on their frequency

2018 ◽  
Vol 210 ◽  
pp. 05012 ◽  
Author(s):  
Zuzana Koudelková ◽  
Martin Strmiska
Keyword(s):  
Brain Activity ◽  
Computer Interface ◽  
Brain Wave ◽  
Non Invasive ◽  
Brain Waves ◽  
Analytical Reasoning ◽  
Brain Signals ◽  
Electroencephalogram Eeg ◽  
The Brain ◽  
Research Type

A Brain Computer Interface (BCI) enables to get electrical signals from the brain. In this paper, the research type of BCI was non-invasive, which capture the brain signals using electroencephalogram (EEG). EEG senses the signals from the surface of the head, where one of the important criteria is the brain wave frequency. This paper provides the measurement of EEG using the Emotiv EPOC headset and applications developed by Emotiv System. Two types of the measurements were taken to describe brain waves by their frequency. The first type of the measurements was based on logical and analytical reasoning, which was captured during solving mathematical exercise. The second type was based on relax mind during listening three types of relaxing music. The results of the measurements were displayed as a visualization of a brain activity.

scholarly journals Decoding a New Neural–Machine Interface for Control of Artificial Limbs

2007 ◽  
Vol 98 (5) ◽  
pp. 2974-2982 ◽  
Author(s):  
Ping Zhou ◽  
Madeleine M. Lowery ◽  
Kevin B. Englehart ◽  
He Huang ◽  
Guanglin Li ◽  
...  
Keyword(s):  
Motor Control ◽  
Degrees Of Freedom ◽  
Clinical Success ◽  
Surface Emg ◽  
Robotic Arm ◽  
Electrode Arrays ◽  
Control Information ◽  
Targeted Muscle Reinnervation ◽  
Prosthetic Limbs ◽  
Machine Interface

An analysis of the motor control information content made available with a neural–machine interface (NMI) in four subjects is presented in this study. We have developed a novel NMI–called targeted muscle reinnervation (TMR)—to improve the function of artificial arms for amputees. TMR involves transferring the residual amputated nerves to nonfunctional muscles in amputees. The reinnervated muscles act as biological amplifiers of motor commands in the amputated nerves and the surface electromyogram (EMG) can be used to enhance control of a robotic arm. Although initial clinical success with TMR has been promising, the number of degrees of freedom of the robotic arm that can be controlled has been limited by the number of reinnervated muscle sites. In this study we assess how much control information can be extracted from reinnervated muscles using high-density surface EMG electrode arrays to record surface EMG signals over the reinnervated muscles. We then applied pattern classification techniques to the surface EMG signals. High accuracy was achieved in the classification of 16 intended arm, hand, and finger/thumb movements. Preliminary analyses of the required number of EMG channels and computational demands demonstrate clinical feasibility of these methods. This study indicates that TMR combined with pattern-recognition techniques has the potential to further improve the function of prosthetic limbs. In addition, the results demonstrate that the central motor control system is capable of eliciting complex efferent commands for a missing limb, in the absence of peripheral feedback and without retraining of the pathways involved.

scholarly journals Early and Contemporary Human Neuroimaging Studies of Serotonergic Psychedelics

2020 ◽  
Author(s):  
Enzo Tagliazucchi
Keyword(s):  
Human Subjects ◽  
Brain Activity ◽  
Neural Correlates ◽  
The Self ◽  
Conscious Awareness ◽  
Altered Consciousness ◽  
Healthy Human ◽  
Non Invasive ◽  
Healthy Human Subjects ◽  
Human Neuroimaging

Serotonergic psychedelics are known to elicit changes in conscious awareness, including perception of the environment and the self, as well as in mood, emotion and different aspects of cognition (Nichols, 2016). The effect of these compounds is complex and resists a straightforward classification that is useful for other drugs, such as “stimulants” or “sedatives”. While the effects of certain psychedelics do have a stimulant dimension, their defining characteristic is the capacity to temporarily induce a state of altered consciousness. Because of this, the study of psychedelics cannot be based only on animal models, since humans are alone in their capacity to explicitly report the contents of their conscious awareness. Psychedelic research with healthy human subjects necessitates techniques for the non-invasive recording of brain activity or its physiological and metabolic correlates. These techniques are referred to as “neuroimaging”, and here we review their application in the study of the neural correlates of altered consciousness induced by serotonergic psychedelics.

Shared control of a robotic arm using non-invasive brain–computer interface and computer vision guidance

2019 ◽  
Vol 115 ◽  
pp. 121-129 ◽  
Author(s):  
Yang Xu ◽  
Cheng Ding ◽  
Xiaokang Shu ◽  
Kai Gui ◽  
Yulia Bezsudnova ◽  
...  
Keyword(s):  
Computer Vision ◽  
Brain Computer Interface ◽  
Shared Control ◽  
Computer Interface ◽  
Robotic Arm ◽  
Non Invasive ◽  
Vision Guidance

Wavelet Transform Analysis the Recognizing Brain Activities for Development the Palm-Size and Simplification Near-Infrared Spectroscopy Prototype System by Using Arduino

2018 ◽  
Vol 22 (3) ◽  
pp. 306-315
Author(s):  
Yukinobu Hoshino ◽  
Masayuki Kubo ◽  
Thang Cao ◽  
◽  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Human Subjects ◽  
Brain Activity ◽  
Prototype System ◽  
Functional Near Infrared Spectroscopy ◽  
Non Invasive ◽  
Medical Device Manufacturers ◽  
Safe Technique

Functional near-infrared spectroscopy (fNIRS) and brain computer interface (BCI) have become indispensable tools for recording and monitoring brain activity, comprising a non-invasive and safe technique that allows researchers to monitor blood flow in the front part of the brain. Although some medical device manufacturers developed complex fNIRS systems, downsized fNIRS systems are important for other uses, such as in portable (palm-sized) and wearable healthcare devices. This paper proposes a downsized compact fNIRS prototype that detects hemodynamics in the frontal lobe. The aim is to develop a compact fNIRS system, which is reliable and easy to integrate into portable (palm-sized) BCI devices. Through practical experiments with human subjects, our proposed system showed an ability to detect and monitor the start and end time of human brain activities when participants were solving a calculation table.

scholarly journals Towards Brain-Computer Interface Control of a 6-Degree-of-Freedom Robotic Arm Using Dry EEG Electrodes

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Alexander Astaras ◽  
Nikolaos Moustakas ◽  
Alkinoos Athanasiou ◽  
Aristides Gogoussis
Keyword(s):  
Degrees Of Freedom ◽  
Cost Minimization ◽  
Brain Computer Interface ◽  
Low Cost ◽  
Computer Interface ◽  
Robotic Arm ◽  
Combined System ◽  
Position Sensing ◽  
Dry Electrode ◽  
Smooth Movement

Introduction. Development of a robotic arm that can be operated using an exoskeletal position sensing harness as well as a dry electrode brain-computer interface headset. Design priorities comprise an intuitive and immersive user interface, fast and smooth movement, portability, and cost minimization.Materials and Methods. A robotic arm prototype capable of moving along 6 degrees of freedom has been developed, along with an exoskeletal position sensing harness which was used to control it. Commercially available dry electrode BCI headsets were evaluated. A particular headset model has been selected and is currently being integrated into the hybrid system.Results and Discussion. The combined arm-harness system has been successfully tested and met its design targets for speed, smooth movement, and immersive control. Initial tests verify that an operator using the system can perform pick and place tasks following a rather short learning curve. Further evaluation experiments are planned for the integrated BCI-harness hybrid setup.Conclusions. It is possible to design a portable robotic arm interface comparable in size, dexterity, speed, and fluidity to the human arm at relatively low cost. The combined system achieved its design goals for intuitive and immersive robotic control and is currently being further developed into a hybrid BCI system for comparative experiments.

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