Achieving fine control movement in mind controlled prosthetics

INTRODUCTION:Due to various political, economic and demographic factors, there has been an increase in the number of amputees and patients with limb dysfunctions over the past few  decades. It has been reported that about 15% of the world’s population suffers from some sort of disability, with only 5-15% of them having access to assistive technology, especially in low to middle income countries [1]. However, there has also been a simultaneous improvement in the field of prosthetics to provide amputees with as similar an experience to natural limbs as possible. Unfortunately, there are still many problems that are associated with this, such as lack of operative naturality, slurred interactions with the environment, and invasive surgeries [1]. With new developments in biotechnology and neuroprosthetics, efforts are being made to combat these challenges, using the brain as a vessel to attain more smooth and controlled movements. Despite the remarkable progress that has been made in the realm of of brain-machine interfaces, difficulties persist in terms of utilizing neural signals to drive artificial actuators—these are responsible for moving and controlling the prosthesis, helping to produce predictive movements in response to dynamic stimuli [3].  

THE MEANS BEHIND THE POSTERIOR PARIETAL CORTEX: Previous neuroprosthetic research pertaining to forward planning—the desired movement of the individual—focused more on direct neural feedback, rather than providing the general trajectory of the movement that the patient wanted to make [2]. Due to this, many mind-controlled prosthetics linked the artificial limb to a person’s motor and premotor cortex, allowing the translation of basic movement signals from the brain to the limbs. This came with many implications, such as slurred movement in the artificial arm and limited ability to interact with the environment [3]. However, neuroscientists and biomedical engineers were able to figure out that the posterior parietal cortex (PPC), which is located behind the primary somatosensory cortex in the parietal cortex, can actually have a more proactive role in predictive motor control [2]. This region of the brain acts as a sensorimotor interface by integrating multisensory inputs and forming initial plans to make movements [4]. 

Experiments performed by a team at the California Institute of Technology assessed the proficiency and overall productivity of the bionic arm when it was connected to the PPC of the brain. The researchers found that the PPC tells the motor cortex the general trajectory of the movement intended [2]. Then, it can smooth out the movements of the artificial arm so that resemblance of a natural limb can be seen. This was a dramatic improvement from previous designs of mind-controlled bionic arms, which connected only the premotor and motor cortices. In these designs, they were only able to decode signals involved with individual movements, such as raising an arm [2]. The newer designs were able to look at the entire action intended.

BEYOND THE CENTRAL NERVOUS SYSTEM: Although the central nervous system provides a mass amount of information, regarding the development of the fine-tune improvements of artificial limbs, the peripheral nerves, in the peripheral nervous system,  also contain additional connection sites for these devices. They can provide a direct access to nerves that are involved in both sensory perception and motor intention, as well as provide less surgical risk [7]. There are three designs to which technicians use this system to provide for the vast array of neuroprosthetics that are seen: interneural, extraneural and electromyography. 

Interneural designs penetrate the nerve allowing electrodes to enter their way into the individual axons of the target nerve [7]. These allow for more fine tune selective commands for motor activations as well as for sensory recording. However, due to being subject to signal degradation and fibrosis, a usual design is the sieve, which is a regenerative electrode that provides a stable and specific interface without long term signal decay [6]. This is done by nerve regeneration through a small hole that is implemented in the array [7]. 

Extraneural designs place electrodes around the target nerve instead of penetrating them [7]. While this is less invasive, there is a reduced selectivity for different fibers within the nerve. Therefore, these designs are poorly suited for the precise stimulation that is required to achieve fine motor control [6]. However, these types of designs show promise for applications requiring stimulation of the whole nerve, such as moving the whole arm [7]. 

Electromyography can monitor the electrical signal that is generated by muscle contractions, which can serve as a source signal for device control [7]. By monitoring the volitional control of the muscles in the chest, neck or shoulders, researchers can convert the EMG activity into control signals for the paralyzed or prosthetic limbs [1]. This allows simple movements such as a shoulder shrug to be allowed to restore functional actions such as elbow flexing, hand grasping or direct control of the robotic prostheses [5]. 

CONTROLLING THE BIONIC ARM: New advancements in mind-controlled bionic arms have facilitated the ability for patients to make precise movements, while undergoing less invasive surgeries. In one such method, engineers use an electroencephalogram to record brain waves associated with a certain movement or facial expression [1]. The readings are then converted into commands for the arm.

In order for the brain to regulate its activities, electric waves emit electrochemical impulses with different frequencies that are decoded by the electroencephalogram, which obtains information about the type of movement that the person wanted to pursue. Different frequencies are associated with different commands for actions [1]. For example, beta waves are usually emitted when a person feel nervous or afraid, with frequencies ranging from 13 to 60 Hertz. Alpha waves are emitted when a person feels relaxed, and they range from 7-13 Hertz [1]. With new advancements in technology, EEG frequencies can now be processed by using a brain-computer interface. 

 The process by which the arm or any artificial limb operates is usually divided into four major units [1]. These units are known as the input, the processing, the electro-mechanical, and the interface unit. It is in the input unit where the brain waves are captured, using an array of advanced EEG sensors communicating with secure, low-power Bluetooth connectivity. These EEG signals are acquired using an Emotiv wireless recording headset, which bears around 14 channels for the sensors [1]. These EEG signals are then sampled and processed in the processing unit, where a pattern recognition algorithm identifies different brain behaviours captured by the input unit and also generates a series of commands to be sent to the mechatronics system of the arm [1]. 

To allow for smooth movements and adaptations to the changing environment, the electro-mechanical and the interface units are utilized. The electro-mechanical unit controls the movements of the arm by placing a microcontroller within the setup to allow for communication between the mechanical unit and the processing unit.The interface unit allows for the arm to interact with the surrounding environment by having temperature, skin pressure, and ultrasonic proximity sensors placed throughout the outer surface of the hand. Furthermore, this unit also allows for bi-directional communication to occur, thereby allowing the sensors to give commands to the arm, as well as receive information from it [1].  

FUTURE RESEARCH: Current research is looking into how these neuroprosthetic limbs can help those with epilepsy, chronic pain, depression, Alzheimer’s disease, spinal cord injury, and those who have sustained the loss loss of limbs [8]. However, before any advancements, engineers are first making innovative use of materials to design and fabricate devices that allow continued functioning in the harsh environment of the human body, without causing any tissue infection or any serious adverse conditions. Research have focused on enhancing the performance of various types of materials, in addition to developing interface technologies that enable the micro-devices to be safely implanted in human tissue for long periods of time [8]. 

Devices and surgical methods that can be expanded for future applications in the deep brain, as well as for spinal cord stimulation, are being researched. Such developments can help physicians advance neural prosthetics to the next level of human health and find better ways for amputees to have more control of their artificial limbs. 

Written by Nauman Zain.

Photo by Polina Tankilevitch from Pexels


  1. Beyrouthy T, Al Kork S, Akl Korbane Joe, Abouelela M. EEG mind controlled smart prosthetic arm – a comprehensive study. ASTESJ. 2017;2(3):891-99.
  2. LiveScience. Bionic arm taps new part of brain for natural moves [Internet]. 2015 [cited 2019 Feb 22]. Available from:
  3. Cui H. Forward prediction in the posterior parietal cortex and dynamic brain-machine interface. Front Integr Neurosci. 2016;10:35.
  4. Anderson RA, Kellis S, Klaes C, Aflalo T. Toward more versatile and intuitive cortical brain machine interfaces. Curr Biol. 2014;24(18):885-97.
  5. Hatsopoulos NG, Donoghue JP. The science of neural interface systems. Annu Rev Neurosci.2009;32:249-66.
  6. Stieglitz T. Restoration of neurological functions by neuroprosthetic technologies: future prospects and trends towards miro-,nano-, and biohybrid systems. Operative Neuromodulation Acta Neurochirurgica Supplements. 2007;97(1):435-42.
  7. The Scientist Magazine. Neuroprosthetics [Internet]. 2014 November 1 [cited 2019 May 1]. Available from:
  8. ASME Public Information. The Next Generation in Neural Prosthetics [Internet]. 2014 January [cited 2019 May 1]. Available from:
  9. Futurism. Florida man becomes first person to live with advanced mind-controlled robotic arm [Internet]. 2018 February 3 [cited 2019 May 1]. Available from:

Be the first to comment on "Achieving fine control movement in mind controlled prosthetics"

Leave a comment

Your email address will not be published.