Frontiers in Robotics and AI · 2020 · 22 citations · 22 references
MedicineBiomedical EngineeringRehabilitation MedicineAssistive TechnologyMotor ControlProstheticsMotion CaptureProsthetic Control SystemsProsthetic RehabilitationRehabilitation RoboticsRobotic RehabilitationUpper-limb ProstheticsBionic ProsthesesClinical Relevance AssessmentControl AlgorithmsData LoggingProsthetic Arm SystemsProsthetic ControlRobotic ProstheticsUpper-limb Prosthetic Control
This paper describes a portable, prosthetic control system and the first at-home use of a multi-degree-of-freedom, proportionally controlled bionic arm. The system uses a modified Kalman filter to provide 6 degree-of-freedom, real-time, proportional control. We describe (a) how the system trains motor control algorithms for use with an advanced bionic arm, and (b) the system's ability to record an unprecedented and comprehensive dataset of EMG, hand positions and force sensor values. Intact participants and a transradial amputee used the system to perform activities-of-daily-living, including bi-manual tasks, in the lab and at home. This technology enables at-home dexterous bionic arm use, and provides a high-temporal resolution description of daily use-essential information to determine clinical relevance and improve future research for advanced bionic arms.
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Bradley Efron, Trevor Hastie, Iain M. Johnstone et al. · The Annals of Statistics · 2004 · 9.5K citations · Full text
Bayesian Population Decoding of Motor Cortical Activity Using a Kalman Filter
Wei Wu, Yun Gao, Elie Bienenstock et al. · Neural Computation · 2005 · 459 citations