A review on the advancements in the field of upper limb prosthesis

References

• Smith DG. General principles of amputation surgery. In: Smith DG, Michael JW, Bowker JH, eds. Atlas of amputations and limb deficiencies: surgical, prosthetic, and rehabilitation principles. 3rd ed. Rosemont (IL): American Academy of Orthopaedic Surgeons; 2004. p. 21–30.
   Google Scholar
• Paudel B, Shrestha BK, Banskota AK. Two faces of major lower limb amputations. KUMJ. 2005;3:212–216.
   PubMedGoogle Scholar
• Magee R. Amputation through the ages: the oldest major surgical operation. ANZ J Surg. 1998;68:675–678.
   Web of Science ®Google Scholar
• Olaolorun DA. Amputations in general practice. Niger Postgrad Med J. 2001;8:133–135.
   PubMedGoogle Scholar
• Ziegler-Graham K, MacKenzie EJ, Ephraim PL, et al. Estimating the prevalence of limb loss in the United States: 2005 to 2050. Arch Phys Med Rehabil. 2008;89:422–429.
   PubMed Web of Science ®Google Scholar
• Robert K, Heck JR. 2008. General principles of amputations. In: Canale ST, Beaty JH, editors. Campbell's operative orthopedics. 11th ed. Philadelphia (PA): Mosby/Elsevier. p. 561–578.
   Google Scholar
• Sabzi AS, Taheri AA. Amputation: a ten-year survey. Trauma Monthly. 2013;18:126–129.
   PubMedGoogle Scholar
• Abou-Zamzam AM, Teruya TH, Killeen JD, et al. Major lower extremity amputation in an academic vascular center. Ann Vasc Surg. 2003;17:86–90.
   PubMed Web of Science ®Google Scholar
• Olasinde AA, Oginni LM, Bankole JO, et al. Indications for amputations in Ile-Ife, Nigeria. Niger J Med. 2002;11:118–121.
   PubMedGoogle Scholar
• Gabos PG. Modified technique for the surgical treatment of congenital constriction bands of the arms and legs of infants and children. Orthopedics. 2006;29:401–404.
   PubMed Web of Science ®Google Scholar
• Walter JH, Goss LR, Lazzara AT. Amniotic band syndrome. J Foot Ankle Surg. 1998;37:325–333.
   PubMedGoogle Scholar
• Light TR, Ogden JA. Congenital constriction band syndrome. Pathophysiology and treatment. Yale J Biol Med. 1993;66:143–155.
   PubMed Web of Science ®Google Scholar
• Vanderwerker EE. A brief review of the history of amputations and prostheses. Inter Clinic Information Bulletin. 1976;15:15–16. 25.
   Google Scholar
• Norton K. A brief history of prosthetics. InMotion. 2007;17:11–13.
   Google Scholar
• Putti V. “Scritti Medici”. La chirurgia degli organi di movimento. 1925;IX:4–5. “Historical Prostheses (Reprint)”. Journal of Hand Surgery (British & European Volume) 2005;30.3:310–325.
   Google Scholar
• Grypma S. Brought to life: exploring the history of medicine. The Science Museum. Supported by the Welcome Trust. Simon Chambers (Project Manager). 2011. http://www.sciencemuseum.org.uk/broughttolife.aspx
   Google Scholar
• Kuniholm J. Prosthetic history: the body-powered arm and William Selpho. In: The Open Prosthetics Project. 2010. URL: http://openprosthetics.ning.com/profiles/blogs/prosthetic-history-the.
   Google Scholar
• Selpho W, inventor. Construction of artificial hands. US Patent 18021. 1857.
   Google Scholar
• Reichenbach J, inventor. Improvement in substitutes for artificial hands. US Patent 48440. 1865.
   Google Scholar
• Dorrance DW, inventor. Artificial hand. US Patent 1042413. 1912.
   Google Scholar
• Simpson DC. The choice of control system for the multimovement prosthesis: Extended physiological proprioception (EPP). In: Herberts P, Kadefors R, Magnusson R, Petersen I, eds. The Control of Upper-Extremity Prostheses and Orthoses. Springfield, IL: Thomas, 1974; 146–150.
   Google Scholar
• Koprnicky J, Najman P, Safka J. 3D printed bionic prosthetic hands. 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (13th IEEE ECMSM-2017, ID: #39496). May 24–26th, 2017; University of Mondragon, Donosti – San Sebastian, Spain; 2017.
   Google Scholar
• Childress D. Upper-limb prosthetics: control of limb prostheses. In: Bowker HK, Michael JW, eds. Atlas of limbprosthetics: surgical, prosthetic, and rehabilitation principles. 2nd ed. Rosemont (IL): American Academy of Orthopaedic Surgeons; 1992.
   Google Scholar
• Fougner A, Stavdahl Ø, Kyberd PJ, et al. Control of upper limb prostheses: terminology and proportional myoelectric control - a review. IEEE Trans Neural Syst Rehabil Eng. 2012;20:663–677.
   PubMed Web of Science ®Google Scholar
• Basmajian JV, De Luca CJ. Muscles alive: their functions revealed by electromyography. Baltimore: Williams and Wilkins; 1985. Letters to the Editor.
   Google Scholar
• Reaz MBI, Hussain MS, Mohd-Yasin F. Techniques of EMG signal analysis: detection, processing, classification and applications. Biol Proced Online. 2006;8:11–35.
   PubMed Web of Science ®Google Scholar
• Scheme EJ, Hudgins B, Parker PA. Myoelectric signal classification for phoneme-based speech recognition. IEEE Trans Biomed Eng. 2007;54:694–699.
   PubMed Web of Science ®Google Scholar
• Saridis GN, Gootee TP. EMG pattern analysis and classification for a prosthetic arm. IEEE Trans Biomed Eng. 1982;29:403–412.
   PubMed Web of Science ®Google Scholar
• Zardoshti-Kermani M, Wheeler BC, Badie K, et al. EMG feature evaluation for movement control of upper extremity prostheses. IEEE Trans Rehab Eng. 1995;3:324–333.
   Google Scholar
• Huang HP, Chen CY. Development of a myoelectric discrimination system for a multi-degree prosthetic hand. IEEE Int Conf Robot Autom. 1999;3:2392–2397.
   Google Scholar
• Chu JU, Moon I, Mun MS. A real-time EMG pattern recognition system based on linear-nonlinear feature projection for a multifunction myoelectric hand. IEEE Trans Biomed Eng. 2006;53:2232–2239.
   PubMed Web of Science ®Google Scholar
• Khushaba RN, Kodagoda S, Takruri M, et al. Toward improved control of prosthetic fingers using surface electromyogram (EMG) signals. Expert Syst Appl. 2012;39:10731–10738.
   Web of Science ®Google Scholar
• Englehart K, Hudgins B, Parker PA, et al. Classification of the myoelectric signal using time-frequency based representations. Med Eng Phys. 1999;21:431–438.
   PubMed Web of Science ®Google Scholar
• Luo Z, Yang G. Study of myoelectric prostheses based on fuzzy control and touch feedback. China Neural Network Council (CNNC), In: Mingsheng Zhao, Zhongzhi Shi, eds. IEEE Computational Intelligence Society, Beijing Section Chapter, International Conference on Neural Networks and Brain (ICNN&B’05) IEEE Press, Beijing, China, Piscataway, NJ, October 13–15, 2005.
   Google Scholar
• Guangying Y. Study of myoelectric prostheses hand based on independent component analysis and fuzzy controller. In: Cui Jianping, Qi Jiming, eds. 8th International Conference on Electronic Measurement and Instruments, 2007: ICEMI ’07 ; Aug. 16, 2007 – Aug. 18, 2007, Xian, China [Piscataway, N.J.] : [IEEE], [2007]. Vol. 1. 2007. p. 174–178.
   Google Scholar
• Tenore FV, Ramos A, Fahmy A, et al. Decoding of individuated finger movements using surface electromyography. IEEE Trans Biomed Eng. 2009;56:1427–1434.
   PubMed Web of Science ®Google Scholar
• Huang HP, Chiang CY. DSP-based controller for a multi-degree prosthetic hand. IEEE Int Conf Robot Autom. 2000;2:1378–1383.
   Google Scholar
• Tenore F, Ramos A, Fahmy A, et al. Towards the control of individual fingers of a prosthetic hand using surface EMG signals. Conf Proc IEEE Eng Med Biol Soc. 2007;6146–6149.
   PubMedGoogle Scholar
• Smith RJ, Tenore F, Huberdeau D, et al. Continuous decoding of finger position from surface EMG signals for the control of powered prostheses. Conf Proc IEEE Eng Med Biol Soc. 2008;197–200.
   PubMedGoogle Scholar
• Khezri M, Jahed M, Sadati N. Neuro-fuzzy surface EMG pattern recognition for multifunctional hand prosthesis control. In: 2007 IEEE International Symposium on Industrial Electronics. Piscataway, N.J.: IEEE, 2007 (DLC) 2006935487. Sponsored by IEEE, ICS ; technically co-sponsored by Universidade de Vigo, SICE. p. 269–274.
   Google Scholar
• Kajitani I, Murakawa M, Nishikawa D, et al. An evolvable hardware chip for prosthetic hand controller. In: Proceedings of the Seventh IEEE International Conference on Microelectronics for Neural, Fuzzy, and Bio-Inspired systems. Granada, Spain. Piscataway, NJ: IEEE. 1999. p. 179–186.
   Google Scholar
• Yong Liu, Kiyoshi Tanaka, Masaya Iwata, Tetsuya Higuchi, Moritoshi Yasunaga: Evolvable Systems: From Biology to Hardware, 4th International Conference, ICES 2001 Tokyo, Japan, October 3-5, 2001, Proceedings. Lecture Notes in Computer Science 2210, Springer 2001.
   Google Scholar
• Lovely DF. Signals and signal processing for myoelectric control. In: Muzumdar, Ashok (Ed.). Powered upper limb prostheses. Springer-Verlag; 2004. Chapter 3; Berlin, Germany: Springer. p. 35–54.
   Google Scholar
• Zhou P, Lowery MM, Englehart KB, et al. Decoding a new neural–machine interface for control of artificial limbs. J Neurophysiol. 2007;98:2974–2982.
   PubMed Web of Science ®Google Scholar
• Agur AM, Dalley AF. 2009. Grant's atlas of anatomy. Philadelphia, Pennsylvania, USA: Lippincott Williams & Wilkins.
   Google Scholar
• Weir RF, Troyk PR, DeMichele G, et al. Implantable myoelectric sensors (IMES) for upper-extremity prosthesis control-preliminary work. Conf Proc IEEE Eng Med Biol Soc. 2003;2:1562–1565.
   Google Scholar
• Huang HP, Liu YH, Wong CS. Automatic EMG feature evaluation for controlling a prosthetic hand using supervised feature mining method: an intelligent approach. IEEE Int Conf Robot Autom. 2003;1:220–225.
   Google Scholar
• Farrell TR, Weir RF. Pilot comparison of surface vs. implanted EMG for multifunctional prosthesis control. IEEE Int Conf Rehabil Robot. 2005;277–280.
   Google Scholar
• Andrade AO, Soares AB. EMG pattern recognition for prosthesis control. In COBEM 2001: Brazilian Congress of Mechanical Engineering. 2001.
   Google Scholar
• Zecca M, Micera S, Carrozza MC, et al. Control of multifunctional prosthetic hands by processing the electromyographic signal. Crit Rev Biomed Eng. 2002;30:459–485.
   PubMedGoogle Scholar
• Bashamajian JV, De Luca CJ. Muscles Alive. Baltimore (MD): Williams & Wilkins; 1985.
   Google Scholar
• Joshi D, Atreya S, Arora AS, et al. Trends in EMG based prosthetic hand development: a review. Indian J Biomech. 2009;228–232.
   Google Scholar
• Hudgins B, Parker P, Scott RN. A new strategy for multifunction myoelectric control. IEEE Trans Biomed Eng. 1993;40:82–94.
   PubMed Web of Science ®Google Scholar
• Zardoshti M, Wheeler BC, Badie K, et al. Evaluation of EMG features for movement control of prostheses. Conf Proc IEEE Eng Med Biol Soc. 1993;15:1141–1142.
   Google Scholar
• Micheli-Tzanakou E. Supervised and unsupervised pattern recognition: feature extraction and computational intelligence. Boca Raton, Florida, USA: CRC Press; 1999.
   Google Scholar
• Carrozza MC, Massa B, Micera S, et al. The development of a novel prosthetic hand-ongoing research and preliminary results. IEEE ASME Trans Mechatron. 2002;7:108–114.
   Web of Science ®Google Scholar
• Harvey D, Longstaff B. The development of a prosthetic arm. Adelaide: The University of Adelaide; 2001.
   Google Scholar
• Carrozza MC, Cappiello G, Stellin G, et al. A cosmetic prosthetic hand with tendon driven under-actuated mechanism and compliant joints: ongoing research and preliminary results. IEEE Int Conf Robot Autom. 2005;2661–2666.
   Google Scholar
• Reischl M, Mikut R, Pylatiuk C, Schulz S. Control strategies for hand prostheses using myoelectric patterns. In: Proc. 9th Fuzzy Colloquium, Zittau, Germany, 2001; 168–174.
   Google Scholar
• Light CM, Chappell PH, Hudgins B, et al. Intelligent multifunction myoelectric control of hand prostheses. J Med Eng Technol. 2002;26:139–146.
   PubMedGoogle Scholar
• Herberts P, Almström C, Kadefors R, et al. Hand prosthesis control via myoelectric patterns. Acta Orthop Scand. 1973;44:389–409.
   PubMed Web of Science ®Google Scholar
• Almström C. 1977. An electronic control system for a prosthetic hand with six degrees of freedom. Department of Applied Electronics, Chalmers University of Technology in collaboration with Department of Orthopaedic Surgery I and Department of Clinical Neurophysiology, Sahlgren Hospital.
   Google Scholar
• Almström C, Herberts P, Körner L. Experience with Swedish multifunctional prosthetic hands controlled by pattern recognition of multiple myoelectric signals. Int Orthop. 1981;5:15–21.
   PubMed Web of Science ®Google Scholar
• Finley FR, Wirta RW. Myocoder studies of multiple myopotential response. Arch Phys Med Rehabil. 1967;48:598–601.
   PubMedGoogle Scholar
• Graupe D, Beex AA, Monlux WJ, et al. A multifunctional prosthesis control system based on time series identification of EMG signals using microprocessors. Bull Prosthet Res. 1977;10:4–16.
   PubMedGoogle Scholar
• Lock BA, Simon AM, Stubblefield K, et al. Prosthesis-guided training for practical use of pattern recognition control of prostheses. Proceedings of the Myoelectric Controls Symposium (MEC); 2011; Fredericton, NB, Canada.
   Google Scholar
• Roesler H. Statistical analysis and evaluation of myoelectric signals for proportional control. In: Herberts P, editor. The control of upper-extremity prostheses and orthoses. Springfield, IL, USA: Charles C. Thomas Publishing; 1974. p. 44–53.
   Google Scholar
• Sorbye R. Myoelectric controlled hand prostheses in children. Int J Rehabil Res. 1977;1:15–25.
   Google Scholar
• Alley RD, Sears HH. Powered upper limb prosthetics in adults. In: Muzumdar A, editor. Powered upper limb prostheses: control, implementation and clinical application. Berlin, Germany: Springer-Verlag; 2004. Chapter 7; p. 117–145.
   Google Scholar
• Sears HH, Shaperman J. Proportional myoelectric hand control: an evaluation. Am J Phys Med Rehabil. 1991;70:20–28.
   PubMed Web of Science ®Google Scholar
• Scheme E, Biron K, Englehart K. Improving myoelectric pattern recognition positional robustness using advanced training protocols. Conf Proc IEEE Eng Med Biol Soc. 2011;33:4828–4831.
   Google Scholar
• Scheme E, Englehart K. Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. J Rehabil Res Dev. 2011;48:643–659.
   PubMed Web of Science ®Google Scholar
• Hargrove L, Losier Y, Lock B, et al. A real-time pattern recognition based myoelectric control usability study implemented in a virtual environment. Conf Proc IEEE Eng Med Biol Soc. 2007;2007:4842–4845.
   PubMedGoogle Scholar
• Cordella F, Ciancio AL, Sacchetti R, et al. Literature review on needs of upper limb prosthesis users. Front Neurosci. 2016;10:209.
   PubMed Web of Science ®Google Scholar
• Markovic M, Dosen S, Cipriani C, et al. Stereovision and augmented reality for closed-loop control of grasping in hand prostheses. J Neural Eng. 2014;11:046001.
   PubMed Web of Science ®Google Scholar
• Atzori M, Müller H. Control capabilities of myoelectric robotic prostheses by hand amputees: a scientific research and market overview. Front Syst Neurosci. 2015;9:162.
   PubMed Web of Science ®Google Scholar
• Available from: http://www.touchbionics.com/
   Google Scholar
• Available from: http://www.bebionic.com
   Google Scholar
• Available from: http://www.living-with-michelangelo.com/home/<
   Google Scholar
• Belter JT, Segil JL, Dollar AM, et al. Mechanical design and performance specifications of anthropomorphic prosthetic hands: a review. J Rehabil Res Dev. 2013;50:599–618.
   PubMed Web of Science ®Google Scholar
• Dhillon GS, Horch KW. Direct neural sensory feedback and control of a prosthetic arm. IEEE Trans Neural Syst Rehabil Eng. 2005;13:468–472.
   PubMed Web of Science ®Google Scholar
• Clement RG, Bugler KE, Oliver CW. Bionic prosthetic hands: a review of present technology and future aspirations. Surgeon. 2011;9:336–340.
   PubMed Web of Science ®Google Scholar
• Reinkensmeyer DJ. Robotic assistance for upper extremity training after stroke. Stud Health Technol Inform. 2009;145:25–39.
   PubMedGoogle Scholar
• Kuiken TA, Miller LA, Lipschutz RD, et al. Targeted reinnervation for enhanced prosthetic arm function in a woman with a proximal amputation: a case study. Lancet. 2007;369:371–380.
   PubMed Web of Science ®Google Scholar
• Kyriazi NE. AI and prosthetics [master’s thesis]. Barcelona, Spain: Universitat Politècnica de Catalunya; 2016.
   Google Scholar
• Zhou P, Lock B, Kuiken TA. Real time ECG artifact removal for myoelectric prosthesis control. Physiol Meas. 2007;28:397–e413.
   PubMed Web of Science ®Google Scholar
• Herr HM, Grabowski AM. Bionic ankle-foot prosthesis normalizes walking gait for persons with leg amputation. Proc R Soc B Biol Sci. 2012;279:457–464.
   PubMed Web of Science ®Google Scholar
• Rouse EJ, Hargrove LJ, Perreault EJ, et al. Estimation of human ankle impedance during the stance phase of walking. IEEE Trans Neural Syst Rehabil Eng. 2014;22:870–878.
   PubMed Web of Science ®Google Scholar
• Wolf EJ, Everding VQ, Linberg AA, et al. Comparison of the power knee and C-leg during step-up and sit-to-stand tasks. Gait Posture. 2013;38:397–402.
   PubMed Web of Science ®Google Scholar
• Agrawal V, Gailey RS, Gaunaurd IA, et al. Comparison between microprocessor-controlled ankle/foot and conventional prosthetic feet during stair negotiation in people with unilateral transtibial amputation. J Rehabil Res Dev. 2013;50:941–950.
   PubMed Web of Science ®Google Scholar
• Luchetti M, Cutti AG, Verni G, et al. Impact of Michelangelo prosthetic hand: findings from a crossover longitudinal study. J Rehabil Res Dev. 2015;52:605–618.
   PubMed Web of Science ®Google Scholar