Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Levi Hargrove"'
Publikováno v:
Sensors, Vol 24, Iss 15, p 4840 (2024)
Pattern recognition (PR)-based myoelectric control systems can naturally provide multifunctional and intuitive control of upper limb prostheses and restore lost limb function, but understanding their robustness remains an open scientific question. Th
Externí odkaz:
https://doaj.org/article/a3c91aee015c44748f07dd81588386cd
Autor:
Matthew R. Short, Daniel Ludvig, Emek Baris Kucuktabak, Yue Wen, Lorenzo Vianello, Eric J. Perreault, Levi Hargrove, Kevin Lynch, Jose L. Pons
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 3864-3873 (2023)
While treating sensorimotor impairments, a therapist may provide physical assistance by guiding their patient’s limb to teach a desired movement. In this scenario, a key aspect is the compliance of the interaction, as the therapist can provide subt
Externí odkaz:
https://doaj.org/article/a730696e97e7484786f4ee4e230755c3
Autor:
Sangjoon J. Kim, Yue Wen, Daniel Ludvig, Emek Baris Kucuktabak, Matthew R. Short, Kevin Lynch, Levi Hargrove, Eric J. Perreault, Jose L. Pons
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 416-425 (2023)
Optimizing skill acquisition during novel motor tasks and regaining lost motor functions have been the interest of many researchers over the past few decades. One approach shown to accelerate motor learning involves haptically coupling two individual
Externí odkaz:
https://doaj.org/article/eafa78c031ab4f44b30e8b30ed159f48
Publikováno v:
Sensors, Vol 22, Iss 24, p 9849 (2022)
A pattern-recognition (PR)-based myoelectric control system is the trend of future prostheses development. Compared with conventional prosthetic control systems, PR-based control systems provide high dexterity, with many studies achieving >95% accura
Externí odkaz:
https://doaj.org/article/68ee3f6493494d9497e3c222b2ab4373
Publikováno v:
Journal of NeuroEngineering and Rehabilitation, Vol 15, Iss S1, Pp 1-7 (2018)
Abstract Background Advances such as targeted muscle reinnervation and pattern recognition control may provide improved control of upper limb myoelectric prostheses, but evaluating user function remains challenging. Virtual environments are cost-effe
Externí odkaz:
https://doaj.org/article/645cdbe929f045eab37cb25e41118241
Publikováno v:
Journal of NeuroEngineering and Rehabilitation, Vol 15, Iss 1, Pp 1-13 (2018)
Abstract Background Active upper-limb prostheses are used to restore important hand functionalities, such as grasping. In conventional approaches, a pattern recognition system is trained over a number of static grasping gestures. However, training a
Externí odkaz:
https://doaj.org/article/756a130d11dc433fa28a5783066fc80e
Publikováno v:
Frontiers in Robotics and AI, Vol 5 (2018)
Externí odkaz:
https://doaj.org/article/c6437ad4daba49299fcec64dcf28b9c2
Publikováno v:
Frontiers in Robotics and AI, Vol 5 (2018)
Wearable lower-limb assistive devices have the potential to dramatically improve the walking ability of millions of individuals with gait impairments. However, most control systems for these devices do not enable smooth transitions between locomotor
Externí odkaz:
https://doaj.org/article/19c3fd8bde734961a488a38657f92a31
Publikováno v:
Frontiers in Robotics and AI, Vol 5 (2018)
Externí odkaz:
https://doaj.org/article/8d0445a50d8745af896398d8a5b1415f
Publikováno v:
PLoS ONE, Vol 9, Iss 11, p e112091 (2014)
Common goals in the development of human-machine interface (HMI) technology are to reduce cognitive workload and increase function. However, objective and quantitative outcome measures assessing cognitive workload have not been standardized for HMI r
Externí odkaz:
https://doaj.org/article/b99d29ac9e8149da9a435189d5cfa34f