Clinical Perspectives in Upper Limb Prostheses: An Update (original) (raw)
Abstract
Purpose of Review This paper aims to summarise the development trends in upper limb bionics over the past 5 years. Recent Findings Increasingly pattern recognition and regression control algorithms are being used to decode EMG signals for prosthetic control and are moving towards clinically available devices. Additionally, bionic reconstruction has built on the principles of targeted muscle reinnervation to add another rung to the reconstructive ladder for upper limb deficits. Finally, novel methods to provide sensation to prostheses are trialled not just in the laboratory but in home testing systems as well. Summary Engineering, surgical and rehabilitation methods are gradually adding more capabilities to modern prostheses, moving towards the goal of replicating natural hand function. Keywords Bionic reconstruction Á Upper limb amputation Á Neural interfaces Á Motor control Á Sensory feedback Á Prosthetic design This article is part of the Topical collection on Plastic Surgery.
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References (94)
- Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
- Roche A, Rehbaum H, Farina D, Aszmann O. Prosthetic myo- electric control strategies: a clinical perspective. Curr Surg Rep. 2014;2(3):1-11.
- Vujaklija I, Farina D, Aszmann O. New developments in pros- thetic arm systems. Orthop Res Rev. 2016;8:31-9.
- Graupe D, Salahi J, Kohn KH. Multifunctional prosthesis and orthosis control via microcomputer identification of temporal pattern differences in single-site myoelectric signals. J Biomed Eng. 1982;4(1):17-22.
- Ortiz-Catalan M, Hkansson B, Brnemark R. Real-time and simultaneous control of artificial limbs based on pattern recog- nition algorithms. IEEE Trans Neural Syst Rehabil Eng. 2014;22(4):756-64.
- Scheme E, Lock B, Hargrove L, Hill W, Kuruganti U, Englehart K. Motion normalized proportional control for improved pattern recognition-based myoelectric control. IEEE Trans Neural Syst Rehabil Eng. 2014;22(1):149-57.
- Hahne JM, Rehbaum H, Biessmann F, Meinecke FC, Muller K-R, Jiang N, et al. Simultaneous and proportional control of 2D wrist movements with myoelectric signals. In: Proceedings of 2012 IEEE International Workshop on Machine Learning for Signal Processing. IEEE; 2012, pp. 1-6.
- Jiang N, Rehbaum H, Vujaklija I, Graimann B, Farina D. Intu- itive, online, simultaneous, and proportional myoelectric control over two degrees-of-freedom in upper limb amputees. IEEE Trans Neural Syst Rehabil Eng. 2014;22(3):501-10.
- Simon AM, Hargrove LJ, Lock BA, Kuiken TA. Target Achievement Control Test: Evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb pros- theses. L Rehabil Res Dev. 2011;48(6):619-27.
- Jiang N, Vujaklija I, Rehbaum H, Graimann B, Farina D. Is accurate mapping of EMG signals on kinematics needed for precise online myoelectric control? IEEE Trans Neural Syst Rehabil Eng. 2014;22(3):549-58.
- Ortiz-Catalan M, Rouhani F, Branemark R, Hakansson B. Offline accuracy: A potentially misleading metric in myoelectric pattern recognition for prosthetic control. In: Proceedings of 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE; 2015, p. 1140-3.
- Hahne JM, Markovic M, Farina D. User adaptation in myoelec- tric man-machine interfaces. Sci Rep. 2017;7(1):4437.
- Vujaklija I, Roche AD, Hasenoehrl T, Sturma A, Amsuess S, Farina D, et al. Translating research on myoelectric control into clinics-are the performance assessment methods adequate? Front Media. 2017;11:7.
- Hargrove LJ, Lock BA, Simon AM. Pattern recognition control outperforms conventional myoelectric control in upper limb patients with targeted muscle reinnervation. In: Proceedings of 2013 35th Annual International Conference of the IEEE Engi- neering in Medicine and Biology Society (EMBC). IEEE; 2013. p. 1599-602.
- Wurth SM, Hargrove LJ. A real-time comparison between direct control, sequential pattern recognition control and simultaneous pattern recognition control using a Fitts' law style assessment procedure. J Neuroeng Rehabil. 2014;11(1):91.
- Kuiken TA, Miller LA, Turner K, Hargrove LJ. A comparison of pattern recognition control and direct control of a multiple degree-of-freedom transradial prosthesis. IEEE J Transl Eng Heal Med. 2016;4:1-8.
- Hargrove LJ, Miller LA, Turner K, Kuiken TA. myoelectric pattern recognition outperforms direct control for transhumeral amputees with targeted muscle reinnervation: a randomized clinical trial. Sci Rep. 2017;7(1):13840.
- Resnik L, Huang H, Winslow A, Crouch DL, Zhang F, Wolk N. Evaluation of EMG pattern recognition for upper limb prosthesis control: a case study in comparison with direct myoelectric control. J Neuroeng Rehabil. 2018;15(1):23.
- Ottobock. Technology for people 4.0: Ottobock at OTWorld 2018-Ottobock. Ottobock. 2018.
- Coapt. Complete Control Handbook. 2017.
- Hahne JM, Biebmann F, Jiang N, Rehbaum H, Farina D, Mei- necke FC, et al. Linear and Nonlinear regression techniques for simultaneous and proportional myoelectric control. Neural Syst Rehabil Eng IEEE Trans. 2014;22(2):269-79.
- Hahne JM, Da ¨hne S, Hwang HJJ, Mu ¨ller KR, Parra LC, Dahne S, et al. Concurrent adaptation of human and machine improves simultaneous and proportional myoelectric control. IEEE Trans Neural Syst Rehabil Eng. 2015;23(4):618-27.
- Lin C, Wang B, Ning J, Farina D. Robust extraction of basis functions for simultaneous and proportional myoelectric control via sparse non-negative matrix factorization. J Neural Eng. 2017;15:026017.
- Muceli S, Jiang N, Farina D. Extracting signals robust to elec- trode number and shift for online simultaneous and proportional myoelectric control by factorization algorithms. IEEE Trans Neural Syst Rehabil Eng. 2014;22(3):623-33.
- Hahne JM, Schweisfurth MA, Koppe M, Farina D. Simultaneous control of multiple functions of bionic hand prostheses: Perfor- mance and robustness in end users. Sci Robot. 2018;3(19):eaat3630.
- Ison M, Vujaklija I, Whitsell B, Farina D, Artemiadis P. High- density electromyography and motor skill learning for robust long-term control of a 7-DoF robot arm. IEEE Trans Neural Syst Rehabil Eng. 2016;24(4):424-33.
- •• Amsuess S, Vujaklija I, Goebel P, Roche AD, Graimann B, Aszmann OC, et al. Context-dependent upper limb prosthesis control for natural and robust use. IEEE Trans Neural Syst Rehabil Eng. 2016;24(7):744-53. Illustrates the benefits of combining pattern recognition and regression methods to achieve simultaneous control
- Farina D, Jiang N, Rehbaum H, Holobar AAA, Graimann B, Dietl H, et al. The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges. IEEE Trans Neural Syst Rehabil Eng. 2014;22(4):797-809.
- Madusanka DGK, Wijayasingha LNS, Gopura RARC, Amaras- inghe YWR, Mann GKI. A review on hybrid myoelectric control systems for upper limb prosthesis. In: 2015 Moratuwa Engi- neering Research Conference (MERCon). IEEE; 2015. p. 136-41.
- Krasoulis A, Kyranou I, Erden MS, Nazarpour K, Vijayakumar S. Improved prosthetic hand control with concurrent use of myo- electric and inertial measurements. J Neuroeng Rehabil. 2017;14(1):71.
- Markovic M, Dosen S, Popovic D, Graimann B, Farina D. Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis. J Neural Eng. 2015;12(6):066022.
- Farina D, Amsu ¨ss S. Reflections on the present and future of upper limb prostheses. Expert Rev Med Devices. 2016;13(4):321-4.
- Neuroengineering Ortiz-Catalan M. Deciphering neural drive. Nat. Biomed Eng. 2017;1(2):0034.
- Kapelner T, Negro F, Aszmann OC, Farina D. Decoding motor unit activity from forearm muscles: perspectives for myoelectric control. IEEE Trans Neural Syst Rehabil Eng. 2018;26(1):244-51.
- Farina D, Vujaklija I, Sartori M, Kapelner T, Negro F, Jiang N, et al. Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation. Nat Biomed Eng. 2017;1(2):0025.
- Holobar A, Zazula D. Multichannel Blind Source Separation Using Convolution Kernel Compensation. IEEE Trans Signal Process. 2007;55(9):4487-96.
- Holobar A, Zazula D. Gradient convolution kernel compensation applied to surface electromyograms. In: Lecture Notes in Com- puter Science. 2010. p. 617-24.
- Negro F, Muceli S, Castronovo AM, Holobar A, Farina D. Multi- channel intramuscular and surface EMG decomposition by con- volutive blind source separation. J Neural Eng. 2016;13(2):026027.
- Chen M, Zhou P. A Novel Framework Based on FastICA for High Density Surface EMG Decomposition. IEEE Trans Neural Syst Rehabil Eng. 2016;24(1):117-27.
- Glaser V, Holobar A, Zazula D. Real-time motor unit identifi- cation from high-density surface EMG. IEEE Trans Neural Syst Rehabil Eng. 2013;21(6):949-58.
- Liu Z, Liu X. Progress on fabric electrodes used in biological signal acquisition. J Miner Mater Charact Eng. 2015;3(May):204-14.
- Lake C, Dodson R. Progressive upper limb prosthetics. Phys Med Rehabil Clin North Am. 2006;17:49-72.
- Daly W. Clinical application of roll-on sleeves for myoelectri- cally controlled transradial and transhumerai prostheses. J Pros- thetics Orthot. 2000;12:88-91.
- Brown S, Ortiz-Catalan M, Peterson J, Ro ¨dby K, Seoane F. Intarsia-Sensorized Band and Textrodes for the Acquisition of Myoelectric Signals. In: The Second International Conference on Smart Portable, Wearable, Implantable and Disability-oriented Devices and Systems. Valencia; 2016. p. 14-9.
- Li G, Geng Y, Tao D, Zhou P. Performance of electromyography recorded using textile electrodes in classifying arm movements. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2011.
- Reissman T, Miller L, Halsne E, Kuiken T. A novel gel liner system with embedded electrodes for use with upper limb myo- electric prostheses. Rev JRRD. 2017;13:1-15.
- Farina D, Lorrain T, Negro F, Jiang N. High-density EMG E-textile systems for the control of active prostheses. 2010 Annu Int Conf IEEE Eng Med Biol Soc EMBC'10. 2010;3591-93.
- Stro ¨mshed BE. The Perfect Fit: Using 3D technologies to create custom-fitted prosthetic arm sockets. 2016.
- Chitresh N, Singh A, Himanshu C. Customised prosthetic socket fabrication using 3D scanning and printing. Proc 4th Int Conf Addit Manuf Technol. 2014;(September).
- Zuniga J, Katsavelis D, Peck J, Stollberg J, Petrykowski M, Carson A, et al. Cyborg beast: a low-cost 3d-printed prosthetic hand for children with upper-limb differences. BMC Res Notes. 2015. 10.1186/s13104-015-0971-9
- Ten Kate J, Smit G, Breedveld P. 3D-printed upper limb pros- theses: a review. Disabil Rehabil Assist Technol. 2017;12(3):300-14.
- Zuniga JM, Major MJ, Peck JL, Srivastava R, Pierce J, Stergiou N. Technical and Clinical Considerations for the Development of 3D Printed Upper-Limb Prostheses for Pediatric Patients. http:// www.aopanet.org/wp-content/uploads/2017/05/Technical-and- Clinical-Considerations-for-3D-Printed-Upper-Limb-Prosthes_ FINAL.pdf.
- Vujaklija I, Farina D. 3D printed upper limb prosthetics. Expert Rev Med Dev. 2018;15(7):505-12.
- Pierrie SN, Gaston RG, Loeffler BJ. Current concepts in upper- extremity amputation. J Hand Surg Am. 2018;43:657-67.
- •• Aszmann OC, Roche AD, Salminger S, Paternostro-Sluga T, Herceg M, Sturma A, et al. Bionic reconstruction to restore hand function after brachial plexus injury: a case series of three patients. Lancet (London, England). 2015;385(9983):2183-89. The first paper to demonstrate patients who have electively chosen to have a biologically intact, but non-functioning limb, amputated in favour or a bionic replacement.
- Hruby LA, Sturma A, Mayer JA, Pittermann A, Salminger S, Aszmann OC. Algorithm for bionic hand reconstruction in patients with global brachial plexopathies. J Neurosurg. 2017;127(5):1163-71.
- Aszmann OC, Vujaklija I, Roche AD, Salminger S, Herceg M, Sturma A, et al. Elective amputation and bionic substitution restore functional hand use after critical soft tissue injuries. Sci Rep. 2016;6:34960.
- •• Gesslbauer B, Hruby LA, Roche AD, Farina D, Blumer R, Aszmann OC. Axonal components of nerves innervating the human arm. Ann Neurol. 2017;82(3):396-408. Peripheral nerve topographical study which shows that sensory axons outnumber their motor counterparts by 9:1, a finding which will affect how sensory prosthesis are designed and implemented.
- Jezernik S, Grill WW, Sinkjaer T. Neural network classification of nerve activity recorded in a mixed nerve. Neurol Res. 2001;23(5):429-34.
- Haugland MK, Sinkjaer T. Cutaneous whole nerve recordings used for correction of footdrop in hemiplegic man. IEEE Trans Rehabil Eng. 1995;3(4):307-17.
- Navarro X, Krueger TB, Lago N, Micera S, Stieglitz T, Dario P. A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems. J Peripher Nerv Syst. 2005;10(3):229-58.
- Hoffer JA, Loeb GE. Implantable electrical and mechanical interfaces with nerve and muscle. Ann Biomed Eng. 1980;8(4-6):351-60.
- Micera S, Rossini PM, Rigosa J, Citi L, Carpaneto J, Raspopovic S, et al. Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces. J Neuroeng Rehabil. 2011;8:53.
- Urbanchek MG, Kung TA, Frost CM, Martin DC, Larkin LM, Wollstein A, et al. Development of a Regenerative Peripheral Nerve Interface for Control of a Neuroprosthetic Limb. Biomed Res Int. 2016;2016:1-8.
- Jiang N, Dosen S, Muller KR, Farina D. Myoelectric control of artificial limbs-is there a need to change focus? IEEE Signal Process Mag. 2012;29(5):152-60.
- Hartmann C, Linde J, Dosen S, Farina D, Seminara L, Pinna L, et al. Towards prosthetic systems providing comprehensive tac- tile feedback for utility and embodiment. In: 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pro- ceedings [Internet]. IEEE; 2014. p. 620-3. http://ieeexplore.ieee. org/document/6981802/.
- Witteveen HJB, Droog EA, Rietman JS, Veltink PH. Vibro-and electrotactile user feedback on hand opening for myoelectric forearm prostheses. IEEE Trans Biomed Eng. 2012;59(8):2219-26.
- Ninu A, Dosen S, Muceli S, Rattay F, Dietl H, Farina D. Closed- loop control of grasping with a myoelectric hand prosthesis: which are the relevant feedback variables for force control? IEEE Trans Neural Syst Rehabil Eng. 2014;22(5):1041-52.
- Dosen S, Krajoski G, Damir JÐ, Farina D, Jorgovanovi N. Closed-loop control of dynamic systems using electrotactile feedback. In: Proceedings of 18th IFESS Annual Conference. 2013.
- Vallbo A, Johansson R. Properties of cutaneous mechanorecep- tors in the human hand related to touch sensation. Hum Neuro- biol. 1984;3:3-14.
- Kuiken TA, Marasco PD, Lock BA, Harden RN, Dewald JPA. Redirection of cutaneous sensation from the hand to the chest skin of human amputees with targeted reinnervation. Proc Natl Acad Sci USA. 2007;104(50):20061-6.
- Schultz AE, Marasco PD, Kuiken TA. Vibrotactile detection thresholds for chest skin of amputees following targeted rein- nervation surgery. Brain Res. 2009;1251:121-9.
- Marasco PD, Schultz AE, Kuiken TA. Sensory capacity of reinnervated skin after redirection of amputated upper limb nerves to the chest. Brain. 2009;132(Pt 6):1441-8.
- Rossini PM, Micera S, Benvenuto A, Carpaneto J, Cavallo G, Citi L, et al. Double nerve intraneural interface implant on a human amputee for robotic hand control. Clin Neurophysiol. 2010;121(5):777-83.
- Raspopovic S, Capogrosso M, Petrini FM, Bonizzato M, Rigosa J, Pino G Di, et al. Bioengineering: Restoring natural sensory feedback in real-time bidirectional hand prostheses. Sci Transl Med. 2014;6(222).
- Tan DW, Schiefer MA, Keith MW, Anderson JR, Tyler J, Tyler DJ. A neural interface provides long-term stable natural touch perception. Sci Transl Med. 2014;6(257):257ra138-257ra138
- Graczyk EL, Resnik L, Schiefer MA, Schmitt MS, Tyler DJ. Home use of a neural-connected sensory prosthesis provides the functional and psychosocial experience of having a hand again OPEN.
- Marasco PD, Hebert JS, Sensinger JW, Shell CE, Schofield JS, Thumser ZC, et al. Illusory movement perception improves motor control for prosthetic hands. Sci Transl Med. 2018;10(432):eaao6990.
- Wendelken S, Page DM, Davis T, Wark HAC, Kluger DT, Duncan C, et al. Restoration of motor control and proprioceptive and cutaneous sensation in humans with prior upper-limb amputation via multiple Utah Slanted Electrode Arrays (USEAs) implanted in residual peripheral arm nerves. J Neuroeng Rehabil. 2017;14(1):1-17.
- Osborn LE, Dragomir A, Betthauser JL, Hunt CL, Nguyen HH, Kaliki RR, et al. Prosthesis with neuromorphic multilayered e-dermis perceives touch and pain. Sci Robot. 2018;3(19):eaat3818.
- Srinivasan SS, Carty MJ, Calvaresi PW, Clites TR, Maimon BE, Taylor CR, et al. On prosthetic control: a regenerative agonist- antagonist myoneural interface. Sci Robot. 2017;2(6):eaan2971.
- Li Y, Bra ˚nemark R. Osseointegrated prostheses for rehabilitation following amputation. Unfallchirurg. 2017;120(4):285-92.
- Ortiz-Catalan M, Mastinu E, Bra ˚nemark R, Ha ˚kansson B. Direct Neural sensory feedback and control via osseointegration. In: XVI World Congress of the International Society for Prosthetics and Orthotics (ISPO). 2017. p. 1-2.
- Tillander J, Hagberg K, Hagberg L, Bra ˚nemark R. Osseointe- grated titanium implants for limb prostheses attachments: infec- tious complications. Clin Orthop Relat Res. 2010;468(10):2781-8.
- Salminger S, Gradischar A, Skiera R, Roche AD, Sturma A, Hofer C, et al. Attachment of upper arm prostheses with a sub- cutaneous osseointegrated implant in transhumeral amputees. Prosthet Orthot Int. 2018;42(1):93-100.
- Bergmeister KD, Hader M, Lewis S, Russold M-F, Schiestl M, Manzano-Szalai K, et al. Prosthesis Control with an implantable multichannel wireless electromyography system for high-level amputees. Plast Reconstr Surg. 2016;137(1):153-62.
- Sturma A, Hruby LA, Prahm C, Mayer JA, Aszmann OC. Rehabilitation following nerve transfers in the upper extremity. In: FESSH. Copenhagen; 2018. p. A-1114.
- Roche AD, Vujaklija I, Amsu ¨ss S, Sturma A, Go ¨bel P, Farina D, et al. A structured rehabilitation protocol for improved multi- functional prosthetic control: a case study. J Vis Exp. 2015;105:e52968.
- Winslow BD, Ruble M, Huber Z. Mobile, game-based training for myoelectric prosthesis control. Front Bioeng Biotechnol. 2018;6:1-8.
- Prahm C, Kayali F, Vujaklija I, Sturma A, Aszmann O. Increasing motivation, effort and performance through game- based rehabilitation for upper limb myoelectric prosthesis con- trol. Int Conf Virtual Rehabil ICVR. 2017. https://doi.org/10\. 1109/ICVR.2017.8007517.
- Prahm C, Kayali F, Sturma A, Aszmann O. Recommendations for games to increase patient motivation during upper limb amputee rehabilitation. In: Biosystems and Biorobotics. 2017. p. 1157-61.
- Van Dijk L, van der Sluis CK, van Dijk HW, Bongers RM. Task- oriented gaming for transfer to prosthesis use No Title. IEEE Trans Neural Syst Rehabil Eng. 2016;24(12):1384-94.
- Engdahl SM, Christie BP, Kelly B, Davis A, Chestek CA, Gates DH. Surveying the interest of individuals with upper limb loss in novel prosthetic control techniques. J Neuroeng Rehabil. 2015;12(1):53.
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