Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Analysis of the Acoustic Power Emitted by a Physiotherapeutic Ultrasound Equipment Used at the Brazilian Air Force Academy Kapitel lesen Erstes Kapitel lesen

2022 | OriginalPaper | Buchkapitel

Perspectives on EMG-Controlled Prosthetic Robotic Hands: Trends and Challenges

verfasst von : Carlos Eduardo Pontim, Arturo Vaine, Hygor Vinícius Pereira Martins, Kevin Christlieb Deessuy, Eduardo Felipe Ardigo Braga, José Jair Alves Mendes Júnior,, D. P. Campos

Erschienen in: XXVII Brazilian Congress on Biomedical Engineering

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Prostheses are devices used to substitute specific members of the human body, whether upper or lower limbs. They have become useful either for the amputee population or for those who have a congenital deficiency. There is not a consensus on how to develop a whole myoelectric prosthesis. The literature is mostly fragmented and it is hard to find a monolithic work about it. Thus, the main goal of this work is to summarize all element and systems of a myoelectric controlled robotic hand and pinpoint the trends and detail major issues and recommendations such as the use of biofeedback, EMG classification trends, compliant mechanisms and the current commercial devices.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Absence from Work in Pregnancy Related to Racial Factors: A Bayesian Analysis in the State of Bahia—Brazil
Nächstes Kapitel Use of Workspaces and Proxemics to Control Interaction Between Robot and Children with ASD
Literatur
1.
Maurice L (2008) Give hope-give a hand. LN-4 Prosthetic Hand
2.
Harthikote NV, Bergmann Jeroen HM, Dibakar S, Thompson Mark S (2016) Examining the needs of affordable upper limb prosthetic users in India: a questionnaire-based survey. Technol Disability 28:101–110
3.
4.
Monteiro PA, Adriana ZS, César Alves OA, Luiz Souza MR, Kelly Gomes CT (2017) Prevalência de amputações de membros superiores e inferiores no estado de Alagoas atendidos pelo SUS entre 2008 e 2015. Fisioterapia e Pesquisa 24:378–384
5.
De Vincenzo CV, da Cunha FL, Schneeheli HA, Bastos TF, Dynnikov VI (2000) Agent-based control of a multifunction myoelectric prosthesis. In: Proceedings of the 22nd annual international conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143), vol 3, pp 2398-2401
6.
Sim K, Rao Z, Zou Z et al (2019) Metal oxide semiconductor nanomembrane–based soft unnoticeable multifunctional electronics for wearable human-machine interfaces. Sci Adv 5:eaav9653
7.
Wu Y, Liu Y, Zou Y et al (2018) A skin-inspired tactile sensor for smart prosthetics. Sci Robot 3
8.
Choi KY, Aadeel A, Timothy B (2017) A compliant four-bar linkage mechanism that makes the fingers of a prosthetic hand more impact resistant, pp 6694–6699
9.
10.
11.
12.
Engdahl S, Christie B, Kelly B, Davis A, Chestek C, Gates D (2015) Surveying the interest of individuals with upper limb loss in novel prosthetic control techniques. J Neuroeng Rehabil 12:53
13.
Biddiss Elaine A, Chau Tom T (2007) Upper limb prosthesis use and abandonment: a survey of the last 25 years. Prosthetics Orthotics Int 31:236–257
14.
Linda R, Meucci Marissa R, Shana L-K et al (2012) Advanced upper limb prosthetic devices: implications for upper limb prosthetic rehabilitation. Arch Phys Med Rehabil 93:710–717
15.
Khushaba RN, Kodagoda S (2012) Electromyogram (EMG) feature reduction using mutual components analysis for multifunction prosthetic fingers control. In: 2012 12th international conference on control automation robotics vision (ICARCV), pp 1534–1539
16.
Rami K, Sarath K, Diaki L, Gamini D (2013) Muscle computer interfaces for driver distraction reduction. Comput Methods Programs Biomed 110
17.
Manfredo A, Matteo C, Henning M (2016) Deep learning with convolutional neural networks applied to electromyography data: a resource for the classification of movements for prosthetic hands. Front Neurorobotics 10
18.
Geng Y, Ouyang Y, Samuel OW et al (2018) A robust sparse representation based pattern recognition approach for myoelectric control. IEEE Access 6:38326–38335
19.
Bishop Christopher M (2006) Pattern recognition and machine learning (information science and statistics). Springer, New York
20.
Foster P, Tom F (2013) Data science for business: what you need to know about data mining and data-analytic thinking. O’Reilly Media, Inc.
21.
Mitchell Tom M (1997) Machine learning. McGraw-Hill, New York
22.
Rahim M, Gursel A, Marc P, Geoffrey S (2016) 3D printed flexure hinges for soft monolithic prosthetic fingers. Soft Robot 3:120–133
23.
Angkoon P, Khushaba Rami N, Erik S (2018) Feature extraction and selection for myoelectric control based on wearable EMG sensors. Sensors (Switzerland) 18:1–17
24.
Resnik L, Helen HH, Anna W, Crouch Dustin L, Fan Z, Nancy W (2018) Evaluation of EMG pattern recognition for upper limb prosthesis control : a case study in comparison with direct myoelectric control, pp 1–13
25.
Geethanjali P (2016) Myoelectric control of prosthetic hands : state-of-the-art review, pp 247–255
26.
27.
Brzostowski K, Szpala A, Rutkowska-kucharska A (2012) Two stage EMG onset detection method. 22:427–440
28.
Jie L, Ying D, Rymer William Z, Ping Z (2015) Robust muscle activity onset detection using an unsupervised electromyogram robust muscle activity onset detection using an unsupervised electromyogram learning framework
29.
Rafiee J, Rafiee MA, Yavari F, Schoen MP (2011) Feature extraction of forearm EMG signals for prosthetics. Expert Syst Appl 38:4058–4067
30.
Geethanjali P, Ray KK (2014) EMG based man-machine interaction—a pattern recognition research platform. Robot Autono Syst 62:864–870
31.
Krishnan S, Athavale Y (2018) Biomedical signal processing and control trends in biomedical signal feature extraction. Biomed Signal Process Control 43:41–63
32.
Schofield Jonathon S, Evans Katherine R, Carey Jason P, Hebert Jacqueline S (2014) Applications of sensory feedback in motorized upper extremity prosthesis: a review. Expert Revi Med Devices 11:499–511
33.
Dosen S, Markovic M, Somer K, Graimann B, Farina D (2015) EMG biofeedback for online predctive control of grasping force in a myoelectric prosthesis. J NeuroEng Rehabil 12:1–13
34.
Max O-C, Rickard B, Bo H (2013) BioPatRec: a modular research platform for the control of artificial limbs based on pattern recognition algorithms. Source Code Biol Med 8:11
35.
Ribeiro J, Mota F, Cavalcante T et al (2019) Analysis of man-machine interfaces in upper-limb prosthesis: a review. Robotics 8:16
36.
Andrianesis K, Tzes A (2015) Development and control of a multifunctional prosthetic hand with shape memory alloy actuators. J Intell Robotic Syst 78:257–289
37.
Witteveen Heidi JB, Frauke L, Rietman Johan S, Veltink Peter H (2013) Stiffness feedback for myoelectric forearm prostheses using vibrotactile stimulation. IEEE Trans. Neural Syst Rehabil Eng 22:53–61
38.
Stanisa R, Marco C, Maria PF et al (2014) Restoring natural sensory feedback in real-time bidirectional hand prostheses. 6:222ra19–222ra19
39.
Dong W, Wang Y, Zhou Y et al (2018) Soft human–machine interfaces: design, sensing and stimulation. Int J Intell Robot Appl
40.
Lee W, Tan YJ, Yao H et al (2019) A neuro-inspired artificial peripheral nervous system for scalable electronic skins. Sci Robot 4:eaax2198
41.
Won P, Park JJ, Lee T et al (2019) Stretchable and transparent Kirigami conductor of nanowire percolation network for electronic skin applications. Nano Lett 19
42.
Chen J, Zheng J, Gao Q et al (2018) Polydimethylsiloxane (PDMS)-based flexible resistive strain sensors for wearable applications. Appl Sci 8
43.
Choi D, Kim M, Oh Y et al (2016) Highly stretchable, hysteresis-free ionic liquid-based strain sensor for precise human motion monitoring. ACS Appl Mater Interfaces 9
44.
Reza KS, Samane A, Alireza A (2020) Robotic hand: a review on linkage-driven finger mechanisms of prosthetic hands and evaluation of the performance criteria. Mech Mach Theory 145:103677
45.
Belter Joseph T (2016) Mechanical design and performance specifications of anthropomorphic prosthetic hands: a review
46.
Yoo H, Lee S, Kim J et al (2019) Development of 3D-printed myoelectric hand orthosis for patients with spinal cord injury. J NeuroEng Rehabil 16:1–14
47.
Rose C, O’Malley M (2019) Hybrid rigid-soft hand exoskeleton to assist functional dexterity. IEEE Robot Autom Lett 4:73–80
48.
Rasulić L, Savić A, Živković B et al (2017) Outcome after brachial plexus injury surgery and impact on quality of life. Acta Neurochirurgica 159:1257–1264
49.
Joseph M, Constant R, Rickloff M et al (2018) A survey of client experiences with orthotics using the QUEST 2.0. J Hand Therapy 31:538–543
Metadaten
Titel
Perspectives on EMG-Controlled Prosthetic Robotic Hands: Trends and Challenges
verfasst von
Carlos Eduardo Pontim
Arturo Vaine
Hygor Vinícius Pereira Martins
Kevin Christlieb Deessuy
Eduardo Felipe Ardigo Braga
José Jair Alves Mendes Júnior,
D. P. Campos
Copyright-Jahr
2022
Buch
XXVII Brazilian Congress on Biomedical Engineering

Print ISBN: 978-3-030-70600-5

Electronic ISBN: 978-3-030-70601-2

Copyright-Jahr: 2022

DOI
https://doi.org/10.1007/978-3-030-70601-2_205

Neuer Inhalt

    Bildnachweise