Skip to main content

Assistive Mobile Technologies for Health Monitoring and Brain–Computer Interface for Patients with Motor Impairments

  • Chapter
  • First Online:
Mobile Solutions and Their Usefulness in Everyday Life

Abstract

This book chapter presents the importance of mobile solutions based on body sensor network (BSN) architecture for health monitoring in case of motor-impaired people. In this work, we present a noninvasive system based on mobile technology that allows biomedical signal monitoring by wearable electrodes. The concept of brain–computer interfaces (BCIs) is the ultimate trend for the entertainment industry (gaming), but this technology has potential by providing signal alerts to motor-impaired people (epilepsy or to enable communication). The mobile technologies allow developing the private cloud for tracking data from biomedical sensors and temporary data storage. Motor impairment is total or partial loss of function of a body part that can be translated to muscle weakness, lack of muscle control, or total paralysis. In case of people with motor impairments, monitoring at home involves a monitoring system based on body sensor network (BSN), Internet of Things (IoT), and feedback from doctors. Such a system may lead to reduced costs of hospitalization.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Bibliography

  1. Naomi E et al (2008) The handy anatomy answer book. Visible Ink Press Publisher, US https://www.ncbi.nlm.nih.gov/pubmedhealth/PMH0072574/

    Google Scholar 

  2. Schwartz BA et al (2006) Brain-controlled interfaces: movement restoration with neural prothetics. Neuron J 52(1):2-5-20

    Article  Google Scholar 

  3. Daly JJ, Huggins JE (2015) Brain-computer interface: current and emerging rehabilitation applications. Arch Phys Med Rehabil 96(30):S1–S7

    Article  Google Scholar 

  4. http://www.who.int/topics/disabilities/en/

  5. https://academic-resources.williams.edu/files/physical1.pdf

  6. https://www.ninds.nih.gov/Disorders/Patient-Caregiver-Education/Fact-Sheets/Motor-Neuron-Diseases-Fact-Sheet

  7. http://www.mandnhealthcare.com/physical-disabilities-26-c.asp

  8. DJ DG et al (2013) Bone and skeletal muscle: neighbours with close ties. J Bone Mineral Res: Off J Am Soc Bone Mineral Res 28(7):1509–1518

    Article  Google Scholar 

  9. http://hwa.org.sg/news/general-information-on-physical-disabilities/

  10. Gold MS et al (2009) Methamphetamine- and trauma-induced brain inju-ries: comparative cellular and molecular neurobiological substrates. Biol Psychiatr 66(2):118–127

    Article  Google Scholar 

  11. Blyth BJ, Bazarian JJ (2010) Traumatic alterations in consciousness: traumatic brain injury. Emerg Med Clin North Am 28(3):571–594

    Article  Google Scholar 

  12. Ding K et al (2016) Epilepsy after traumatic brain injury. In: Laskowitz D, Grant G (eds) Translational research in traumatic brain injury. CRC Press/Taylor and Francis Group, Boca Raton Chapter 14, Available from: https://www.ncbi.nlm.nih.gov/books/NBK326716/

    Google Scholar 

  13. Walker BN, Vujic A (2017) Engineering Psych. Seminar on Assistive Technology PSYC 8040/CS 8803-AT (2017). Motor Disabilities CS 8803, available: http://sonify.psych.gatech.edu/~walkerb/classes/assisttech/pdf/cs8803_motor-disabilities-discussion.pdf

  14. Dobkin BH (2009) Motor rehabilitation after stroke, traumatic brain, and spi- nal cord injury: common denominators within recent clinical trials. Curr Opin Neurol 22(6):563–569

    Article  Google Scholar 

  15. http://www.neuromodulation.com/motor-impairment

  16. Finnerup N (2016) Neuropathic pain in spinal cord injury, ISCoS, UK, 2016

    Google Scholar 

  17. Morganti - Kossmann C et al (2012) Traumatic brain and spinal cord injury: challenges and developments. Cambridge University Press, Cambridge, pp 1–215

    Book  Google Scholar 

  18. https://treatmentpossibleblog.wordpress.com/tag/spinal-cord-injury

  19. https://www.webmd.com/brain/brain-damage-symptoms-causes-treatments#1

  20. https://www.gmc-uk.org/accessibility/assistive_technologies/physical_impairments.asp

  21. https://www.enablemart.com/maltron-one-handed-keyboards-right-and-left-hand

  22. https://webaim.org/articles/motor/motordisabilities

  23. Barrué C (2012) Personalization and Shared Autonomy in Assistive Technol- ogies. Ph. Thesis. Universitat Politècnica de Catalunya. 2012

    Google Scholar 

  24. Skejié E, Durek M (2007) Assistive technologies for physically handicapped persons. In: Sobh T (ed) Innovations and advanced techniques in computer and information sciences and engineering. Springer, Dordrecht

    Google Scholar 

  25. https://webaim.org/articles/motor/motordisabilities#limbs

  26. Farooq A (2009) Haptics in kiosks and ATMs for the disabled. University of Tampere, Tampere

    Google Scholar 

  27. Reis CI et al (2017) Internet of things and advanced application in healthcare. ICI-global. USA:2017

    Google Scholar 

  28. Arampatzis T et al (2005) A Survey of Applications of Wireless Sensors and Wireless Sensor Networks, Proceedings of the 2005 IEEE International Symposium on Mediterrean Conference on Control and Automation Intelligent Control, Limassol, pp 719–724

    Google Scholar 

  29. Islam SMR et al (2015) The internet of things for health care: a comprehensive survey. IEEE Access 3:678–708

    Article  Google Scholar 

  30. Domingo MC (2012) Review: an overview of the internet of things for people with disabilities. J Netw Comput Appl 35(2):1084–8045

    Article  Google Scholar 

  31. Faller J et al (2014) Non-motor tasks improve adaptive brain-computer inter- face performance in users with severe motor impairment. Frontiers in Neuro- science 8:320

    Google Scholar 

  32. Pasqualotto E et al (2015) Usability and workload of access technology for people with severe motor impairment: a comparison of brain-computer interfacing and eye tracking. Neurorehabil Neural Repair 29(10):950–957

    Article  Google Scholar 

  33. Nijboer F et al (2008) A P300-based brain-computer interface for people with amyotrophic lateral sclerosis. Clin Neurophysiol 119(8):1909–1916

    Article  Google Scholar 

  34. Iturrate I et al (2009) A noninvasive brain-actuated wheelchair based on a P300 neurophysiological protocol and automated navigation. IEEE Transact Robotics 25(3):614–627

    Article  Google Scholar 

  35. Bayliss JD (2003) Use of the evoked potential P3 component for control in a virtual apartment. IEEE Trans Neural Syst Rehabil Eng 11(2):113–116

    Article  MathSciNet  Google Scholar 

  36. Mugler EM et al (2010) Design and implementation of a P300-based braincomputer interface for controlling an internet browser. IEEE Trans Neural Syst Rehabil Eng 18(6):599–609

    Article  Google Scholar 

  37. Münßinger JI et al (2010) Brain painting: first evaluation of a new brain – computer Interface application with ALS-patients and healthy volunteers. Front Neurosci 4:182

    Article  Google Scholar 

  38. Schalk G et al (2004) BCI2000: a general-purpose brain-computer interface (BCI) system. IEEE Trans Biomed Eng 51(6):1034–1043

    Article  Google Scholar 

  39. Pierce JR (2016) An introduction to information theory: symbols. Signals Noise Courier Corp

    Google Scholar 

  40. Bangor A et al (2008) An empirical evaluation of the system usability scale. Int J Human–Comp Interact 24(6):574–594

    Article  Google Scholar 

  41. Hart SG, Staveland LE (1988) Development of NASA-TLX (task load index): results of empirical and theoretical research. Adv Psychol 52(C):139–183

    Article  Google Scholar 

  42. Future ready assistive technology: fostering state supports for students with disabilities. Center on Technology and Disability USA. http://ctdinstitute.org/sites/default/files/file_attachments/CTD-AIR_FutReadyAssistTech.pdf

  43. Siburkis LW (2015) Future of personal monitoring devices for epilepsy. AES 2015 Epilepsy and Seizure. Neurology Times. http://www.neurologytimes.com/aes-2015/future-personal-monitoring-devices-epilepsy

  44. Futurehome AS. Futurehome Android and iOS App. https://futurehome.no/en/app

  45. CYBERDYNE Inc. https://www.cyberdyne.jp/english/products/LowerLimb_medical.html

  46. Field A (2017) A startup that’s (literally) opening doors for wheelchair users. Forbes. https://www.forbes.com/sites/annefield/2017/07/30/opening-doors-literally-for-wheelchair-users/#4128512353d4

  47. Talkitt – Voiceitt http://www.talkitt.com

  48. Be My Eyes http://bemyeyes.com

  49. Dot Watch https://dotincorp.com

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Aileni, R.M., Suciu, G., Suciu, V., Ciurea, J., Sever, P. (2019). Assistive Mobile Technologies for Health Monitoring and Brain–Computer Interface for Patients with Motor Impairments. In: Paiva, S. (eds) Mobile Solutions and Their Usefulness in Everyday Life. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-93491-4_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-93491-4_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93490-7

  • Online ISBN: 978-3-319-93491-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics