21st Century Human Limb Regeneration: An Overview By Dhanya Mahesh Salamanders and newts have the extraordinary ability to regenerate lost limbs. If a newt’s tail is cut off, epidermal cells will cover the opening, and pattern formation genes (or Hox genes) will allow the proliferating cells at the edge of the wound to reform into the necessary muscle cells, nerve cells, skin cells, etc. (Endo et al., 2004). Unfortunately, humans cannot perform quite a feat through biology alone, but with technology they may be able to develop the next best thing. Human limb regeneration has been sought after by patients who suffer from paralysis, strokes, or have experienced some variation of limb amputation. By bridging neuroscience and technology, researchers may finally be able to construct a near replica of the human arm, working nerves and all. In October 2014, the first person to receive a mind controlled prosthetic was a male amputee from Sweden. This prosthetic, while a revolutionary development, was neither one hundred percent accurate nor highly sensitive to his thoughts (Criado, 2014). In May 2015, Mr. Les Baugh, a double amputee, received a high-tech prosthetic arms. Baugh was provided with a pair of prosthetic limbs that were controlled by his thoughts and would even allow him to experience physical sensations (Cot, 2015). In September 2015, a mechanical arm built by DARPA managed to allow an amputee to feel physical sensations with metal prosthetics. The prosthetics were able to stimulate sensory nerves in the brain (Wood, 2015). More recently, In February 2016, researchers at the Johns Hopkins University Applied Physics Laboratory further developed this technology and manufactured a prosthetic limb that would move individual fingers in response to the user’s thoughts (Hotson et al., 2015). The researchers at Johns Hopkins developed a Brain Machine Interface or BMI to connect the electrical signals concerning movement in the brain with the actions of a prosthetic limb. The scientists used “high density electrocorticography” to build a model of the electrical signals passed in order to initiate and control individual finger movements (Hotson et. al, 2015).
To do so, teams of scientists at Johns Hopkins first began mapping the patient’s brain by placing intracranial electrodes on sensorimotor regions.The subject then underwent several finger associated tasks to collect data for the researchers’ BMI (Brain Machine Interface). These tasks included finger tapping and “vibrotactile stimulation” or stimulation by inducing pressure upon the fingertips. While the subject underwent such experiments, the researchers collected electrical data from the brain concerning the initiation and movement of each finger. This data was then used to train the prosthetic to identify whether a movement was occurring and if so, which finger was moving, and to then move a corresponding finger at a fixed speed in response. Thus, the researchers were able to program the prosthetic limbs to respond to the movement controlling neurons in the brain accordingly (Hotson et al., 2015). Rigorous testing was administered to calculate the prosthetic limb’s overall accuracy. The accuracy of its ability to classify movement signals was calculated to be approximately 76% while the finger detection balanced accuracy, or the accuracy of the program in detecting the correct moving finger, was approximately 92%. As this technology develops, it is quite possible that the accuracy level will increase (Cot, 2015). This new technology combined with the work of other prosthetics researchers may be able to yield a high-functioning prosthetic limb that responds to user’s thoughts with a high level of accuracy. For example, studies have shown that similar electrocorticography research has allowed prosthetics to reach and grasp items with approximately 81 - 84% accuracy and to move and gather items at an accuracy level of approximately 70% (Fifer et al., 2014; McMullen et al., 2013). In the future, researchers may be able to combine such research to create a functioning BMI prosthetic. Unfortunately, at this stage in development, these prosthetics currently valued at approximately $500,000, making them unaffordable to many people (Cot, 2015). Hopefully, in the near future, scientists will be able to develop better prosthetics and increase their affordability, so that amputees and stroke victims can enjoy the sensations of their lost limbs once again.
References Cot, E. (2015, May 20). Prosthetic Limbs, Controlled by Thought. Retrieved April 24, 2016, from: http://www.nytimes.com/2015/05/21/technology/a-bionic-approach-toprosthetics-controlled-by-thought.html?_r=0 Criado, E. (2014, October 9). Swedish man first to use mind-controlled prosthetic arm. Retrieved May 25, 2016, from http://www.independent.co.uk/news/science/swedish-manis-first-to-use-mind-controlled-prosthetic-arm-9785950.html Endo, T., Bryant, S. V., & Gardiner, D. M. (2004). A stepwise model system for limb regeneration. Developmental biology, 270(1), 135-145. Fifer, M. S., Hotson, G., Wester, B. A., McMullen, D. P., Wang, Y., Johannes, M. S., ... & Anderson, W. S. (2014). Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG. Neural Systems and Rehabilitation Engineering, IEEE Transactions on,22(3), 695-705. Hotson, G., McMullen, D. P., Fifer, M. S., Johannes, M. S., Katyal, K. D., Para, M. P., ... & Crone, N. E. (2016). Individual finger control of a modular prosthetic limb using high-density electrocorticography in a human subject.Journal of neural engineering, 13(2), 026017.
Lavars, N. (2016, February 17). Mind-controlled prosthetic allows movement of individual fingers. Retrieved May 25, 2016, from http://www.gizmag.com/mind-controlledprosthetic-fingers/41886/ McMullen, D. P., Hotson, G., Katyal, K. D., Wester, B. A., Fifer, M. S., McGee, T. G., ... & Anderson, W. S. (2014). Demonstration of a Semi-Autonomous Hybrid Brain– Machine Interface Using Human Intracranial EEG, Eye Tracking, and Computer Vision to Control a Robotic Upper Limb Prosthetic.Neural Systems and Rehabilitation Engineering, IEEE Transactions on, 22(4), 784-796. Wood, A. (2015, September 14). Revolutionary mechanical hand adds a sense of touch to mind-controlled prostheses. Retrieved May 25, 2016, from http://www.gizmag.com/darpa-prosthetic-physical-sensations-mechanicalhand/39398/