title: Multi-motion robots control based on bioelectric signals from single-channel dry electrode.
abstract: This article presents a multi-motion control system to help severe disabled people operate an auxiliary appliance using neck-up bioelectric signals measured by a single-channel dry electrode on the forehead. The single-channel dry-electrode multi-motion control system exhibits several practical advantages over its conventional counterparts that use multi-channel wet-electrodes; among the challenges is an effective technique to extract bioelectric features for reliable implementation of multi degrees-of-freedom motion control. Using both time and frequency characteristics of the single-channel dry-electrode measurements, motion commands are derived from multiple feature signals associated with concentration demands and different eye-blink actions for use in a two-level control strategy that has been developed to control predefined multi degrees-of-freedom motion trajectories. Test paradigms were designed to pre-calibrate the users' feature signals to statistically account for individual variances. Experimental trials were then carried out on able-bodied and disabled volunteers to validate the universal applicability of the algorithms. The classification success rates for two different eye-blink feature signals were approximately 95% with an average time of 2.4 s for executing a concentration feature signal. The single-channel dry-electrode-based technique has been validated on a 6-degree-of-freedom robot arm demonstrating its significant potentials to help patients suffering severe motor dysfunctions operate a multi-motion auxiliary appliance in everyday living where the ease of use is a priority.
authors: State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, China.
authors: Hui-Min
authors: HM
authors: Shen
authors: State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, China cmeehuli@zju.edu.cn kokmeng.lee@me.gatech.edu.
authors: Liang
authors: L
authors: Hu
authors: George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
authors: Kok-Meng
authors: KM
authors: Lee
authors: State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, China.
authors: Xin
authors: X
authors: Fu
mesh_terms: D000328:Adult; D000465:Algorithms; D001767:Blinking / Q000502:physiology; D006233:Persons with Disabilities / Q000534:rehabilitation; D004566:Electrodes; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D004867:Equipment Design; D005260:Female; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D012371:Robotics / Q000295:instrumentation*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D055815:Young Adult
keywords: Multi-motion control; bioelectric signals; electroencephalography; eye blink; single-channel dry electrode