Enhancements of a tongue-operated robotic rehabilitation system

Zhang, Z.; Ostadabbas, Sarah; Sahadat, Nazmus; Sebkhi, Nordine; Wu, David; Butler, Andrew; Ghovanloo, Maysam

doi:10.1109/biocas.2015.7348284

Cited by 6 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…in which n, n 1 , and m represent the unit numbers of the input layer, hidden layer, and output layer of the BP neural network, respectively, and a is a natural number with a value in the range of [1,10]. In our study, the values of n and m are 5 and 3, respectively.…”

Section: Bp Neural Networkmentioning

confidence: 99%

“…Vinoj et al used human motion imagination combined with visual stimulation to identify basic human motion characteristics such as sitting, standing, forward movement, turning right, and turning left, and these actions could be used as instructions to control the movement of exoskeletons, thus enabling exoskeletons to assist the normal movement of human beings [9]. Zhang et al and Kong et al applied tongue electrical signal features to the rehabilitation of paralyzed patients [10,11]. Sahadat et al successfully applied tongue electrical signal features to complete four computer access tasks without using their hands [12].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on Home-Auxiliary Robot System Based on Characteristics of Human Physiological and Motion Signals

Wang

Zhang

2020

Complexity

View full text Add to dashboard Cite

A home-auxiliary robot system based on characteristics of the electrooculogram (EOG) and tongue signal is developed in the current study, which can provide daily life assistance for people with physical mobility disabilities. It relies on five simple actions (blinking twice in a row, tongue extension, upward tongue rolling, and left and right eye movements) of the human head itself to complete the motions (moving up/down/left/right and double-click) of a mouse in the system screen. In this paper, the brain network and BP neural network algorithms are used to identify these five types of actions. The result shows that, for all subjects, their average recognition rates of eye blinks and tongue movements (tongue extension and upward tongue rolling) were 90.17%, 88.00%, and 89.83%, respectively, and after training, the subjects can complete the five types of movements in sequence within 12 seconds. It means that people with physical disabilities can use the system to quickly and accurately complete life self-help, which brings great convenience to their lives.

show abstract

Section: Bp Neural Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on Home-Auxiliary Robot System Based on Characteristics of Human Physiological and Motion Signals

Wang

Zhang

2020

Complexity

View full text Add to dashboard Cite

show abstract

“…In a previous study, a tongue-operated rehabilitation robot has been developed to translate tongue motion to commands via the tongue drive system (TDS) [43][44][45][46]. Commands were used to control a wrist-based rehabilitation robot called the hand mentor [27,47]. This device has been shown to elicit improvements in strength and range of motion in moderate to severely impaired stroke survivors [28,48].…”

Section: Introductionmentioning

confidence: 99%

Design and Preliminary Evaluation of a Tongue-Operated Exoskeleton System for Upper Limb Rehabilitation

Zhang

Prilutsky

Butler

et al. 2021

IJERPH

View full text Add to dashboard Cite

Stroke is a devastating condition that may cause upper limb paralysis. Robotic rehabilitation with self-initiated and assisted movements is a promising technology that could help restore upper limb function. Previous studies have established that the tongue motion can be used to communicate human intent and control a rehabilitation robot/assistive device. The goal of this study was to evaluate a tongue-operated exoskeleton system (TDS-KA), which we have developed for upper limb rehabilitation. We adopted a tongue-operated assistive technology, called the tongue drive system (TDS), and interfaced it with the exoskeleton KINARM. We also developed arm reaching and tracking tasks, controlled by different tongue operation modes, for training and evaluation of arm motor function. Arm reaching and tracking tasks were tested in 10 healthy participants (seven males and three females, 23–60 years) and two female stroke survivors with upper extremity impairment (32 and 58 years). All healthy and two stroke participants successfully performed the tasks. One stroke subject demonstrated a clinically significant improvement in Fugl-Meyer upper extremity score after practicing the tasks in six 3-h sessions. We conclude that the TDS-KA system can accurately translate tongue commands to exoskeleton arm movements, quantify the function of the arm, and perform rehabilitation training.

show abstract

A Review on Tongue Based Assistive Technology, Devices and FPGA Processors Using Machine Learning Module

Prasanna,

Tripathi

2024

Wireless Pers Commun

View full text Add to dashboard Cite

Enhancements of a tongue-operated robotic rehabilitation system

Cited by 6 publications

References 17 publications

Research on Home-Auxiliary Robot System Based on Characteristics of Human Physiological and Motion Signals

Research on Home-Auxiliary Robot System Based on Characteristics of Human Physiological and Motion Signals

Design and Preliminary Evaluation of a Tongue-Operated Exoskeleton System for Upper Limb Rehabilitation

A Review on Tongue Based Assistive Technology, Devices and FPGA Processors Using Machine Learning Module

Contact Info

Product

Resources

About