A PORTABLE MYOELECTRIC PATTERN RECOGNITION-DRIVEN VIRTUAL TRAINING SYSTEM FOR PHANTOM LIMB PAIN MANAGEMENT

Authors

  • Zachary Wright
  • Blair Lock
  • Kristi Turner
  • Andrea Ikeda
  • Katie Cai
  • Xavier Oberhelman
  • Carlos Martinez
  • Levi Hargrove

DOI:

https://doi.org/10.57922/mec.2509

Abstract

Individuals with limb absence commonly suffer from phantom limb pain (PLP), a debilitating condition with poorly understood mechanisms and limited treatment options. Current approaches to treat PLP have broadly proven unsafe or ineffective, leaving patients searching for alternative, long-term options. Recent studies have demonstrated the potential of phantom motor execution therapy, aided by myoelectric pattern recognition software and virtual reality systems, in alleviating PLP. However, widespread clinical adoption has been hindered by limited accessibility, especially for the lower limb absent population. This paper presents the design and development of a portable, myoelectric pattern recognition-driven virtual training system, tailored for at-home use by individuals with upper or lower limb absence to safely and effectively manage and reduce PLP.

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Published

2024-08-15

How to Cite

[1]
Z. Wright, “A PORTABLE MYOELECTRIC PATTERN RECOGNITION-DRIVEN VIRTUAL TRAINING SYSTEM FOR PHANTOM LIMB PAIN MANAGEMENT”, MEC Symposium, Aug. 2024.

Conference Proceedings Volume

2024: MEC24

Section

User Experience