29-10-2010, 08:22 AM
BIONIC LIMBS AND THEIR CONTROLS
By :
Arya Sree.T
S7 AEI
College Of Engineering, Trivandrum
2007-11 batch
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Overview
Bionics
Prosthetics
Hybrid bionic system
Signal pathway
Invasive PNS neural interfaces
Targeted muscle reinnervation
Prosthetic proprioception
EAP as artificial muscles
Challenges posed
Conclusion
Bionics
Bi( as in ‘life’) + onics( as in ‘electronics’)
Mechanical systems that function like living organisms or parts of living organisms
Prosthetics
Powered prosthetics: deducing user intend from existing structures in motor pathway for natural control
Fundamental control problem for prosthetics:
Limb amputation level prop. to DOF needed
Limb amputation level inv prop. to control inputs
Hybrid bionic system
Artificial system + HMI
Background - Action potential
Polarization - K+ move out
Depolarization - Na+ move in
Repolarization - back to initial ion concentrations
Signal pathway
Human Machine Interfaces
Extract voluntary commands and deliver sensory feedback
Different types
EMG based control
Cortical noninvasive HMIs
Cortical invasive HMIs
Invasive PNS HMIs
Invasive PNS neural interfaces
More intuitive limb control
Sensory feedback given through peripheral nerves giving the user more control over joint position and grip force
Pulse train of varying current amplitudes sent to electrodes in pns to recreate signals conveying touch and proprioception
PNS neural interfaces (diag)
Recording and processing signals using LIFE (expt)
Targeted muscle reinnervation
Goal : to create more natural control by ‘rewiring’
Denervate an expendable muscle area
Attach motor neurons from the amputed arm to different areas of dennervated region
Control inputs to the prosthetics are taken from these nerve endings
If successful, thinking about using the limb would result in the contraction of limb
TMR (diagram)
Prosthetic proprioception
The ability to perceive position and movement of one’s own body
Done by a class of receptors called proprioceptors
Originates from receptors in muscles, joints and skin
Sensors and encoders give signals which is given as feedback
EAP as artificial muscles
Can mimic muscle to actuate biologically inspired mechanisms
Resilient, fault tolerant, noiseless, low power consumers
Two types
Electronic
Ionic
Challenges posed
Inherent complexity of the neural system
Connecting up small neurons without causing excessive damage
Every person’s brain is different, so difficult to adapt hardware
Difficulty in making complex algorithms for signal recognition
Expensive
Conclusion
Goal : restoration of sensorimotor functions for the control of artificial limbs
PNS invasive interfaces, TMR- feasible medium term solution
Adequate characteristics
Reduced secondary risk concerns
Only little training needed for the amputees
The near future
Improvement in the quality of life
Development of mind controlled systems that can work in different environments
Applications in robotics
Scope of various researches and projects
References
Improved Myoelectric Prosthesis Control Using Targeted Reinnervartion Surgery: A Case Series
By: Miller, L.A.Stubblefield, K.A. Lipschutz, R.D.Lock, B.A.Kuiken, T.A.Rehabilitation Inst. of Chicago, Chicago
This paper appears in: Neural Systems and Reinnervation Engineering, IEEE Transactions on
Issue Date: Feb 2008
Date of Current Version: 12 February 2008
Development of BIONic Muscle Spindle for Prosthetic Proprioception
By: Sachs, N.A. Loeb, G.E. Dept of Biomed. Eng., Univ. of Southern California, Los Angeles, CA
This paper appears in: Biomedical Engineering, IEEE Transactions on
Issue Date: June 2007
Date of Current Version: 21 May 2007
On the Use of Longitudinal Peripheral Interfaces for the Control of Cybernetic Hand Prostheses in Amputees
By: Micera, S. Navarro, X. Carpaneto, J. Citi, L. Tonet, O.Rossini, P.M.Carrozza, M.C. Hoffmann, K.P. Vivo, M. Yoshida, K. Dario, P.
ARTS & CRIM Labs., Pisa
Issue Date: Oct. 2008
Date of Current Version: 05 Nov 2008
The Bionic Design and Intelligent Control of Multi-Axis Artificial Leg
By: Fei Weiqi Yuan Hualong Xie
Sch. of Inf. Sci & Eng., Shenyang Univ. of Technol., Shenyang, China
Issue Date: June 2009
Date of Current Version: 14 July 2009