Intelligent Biomechatronics in Neurorehabilitation

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Intelligent Biomechatronics in Neurorehabilitation
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Contributors
Preface
Part I: Neural coding mechanisms
1. Toward bidirectional closed-loop brain–machine interfaces (BMIs): a summary on invasive BMI research in China
	Introduction
	BMIs on nonprimates
		Neural decoding in rodents
		Neural coding of sensory information using brain stimulation
		Portable system for neural stimulation and recording
	BMIs in non-human primates
		Neural data reduction and decoding models
		Grasp decoding and neural prosthesis control
	Pilot studies in clinic research
		Prosthesis control using human ECoG BMI
		Closed-loop BMI for seizure detection and inhibition
	Conclusion
	Acknowledgments
	References
2. Neural decoding by invasive electrocorticography
	Introduction
	Experimental paradigm and data collection
		Participants and implantation
		Cortical mapping
		Behavioral tasks
		Neural signals and behavioral data recording
	Hand gesture encoding within ECoG
		Data analysis and channel selection
			Feature extraction
			Decoding performance evaluation
			Channel selection strategies
		Results
			Time–frequency analysis and decoding performance
			Channel selections and anatomical patterns
			Decoding performance using nearest-neighboring channels
	Rapid decoding of hand gestures with recurrent neural networks
		RNN-based hand gesture recognition
			Feature extraction
			Recurrent neural network-based gesture recognition
		Results
			Feature analysis
			Performance of gesture recognition
				Model selection
				Comparison with other methods
			Rapid recognition
	Conclusion
	References
3. Neural coding by electroencephalography (EEG)
	Introduction
	Novel signal processing methods for few EEG electrode-based neural decoding
		Spatial filter for improving signal-to-noise ratio
			Bipolar derivation
			Laplacian derivation
		Subject-specific channel selection for individualized recording setup
		Time–frequency analysis for extracting CSMR
	Remaining challenges and future directions
	References
4. Electromyography (EMG) examination on motor unit alterations after stroke
	Introduction
	Complex neuromuscular changes demonstrated by interference surface EMG analysis
	Motor unit loss after stroke
		Motor unit control property alterations after stroke
	Remodeling of surviving motor units after stroke
	Significance and future perspectives
	Funding statement
	References
5. Automatic analysis of segmentwise locomotion details of Drosophila larva
	Introduction
	Related work
		Automatic behavior analysis
		Pose estimation
	Method
		Problem formulation
		Cascaded regression model for larval segment endpoint localization
			Explicit shape regression-based endpoint location
			Learning framework
		Segment endpoint locating method
			Rotate image
			Split dataset
			Regression-based method
	Result
		Dataset
			Dataset property
			Error metrics
		Experiments
	Conclusion
	Acknowledgment
	References
Part II: Biomechatronic Systems Integrated with the Human Body
6. Bionic robotics for post polio walking
	Background
	Current status of individuals with poliomyelitis
	Robotic knee orthosis design
		Thermal plastic mold KAFO
		Sensory system
		Electromechanical lock knee joint
		Actuation system
		Control algorithm
	Training program
		Case description
		Don and doff
		Sit-to-stand
		Walking preparation
		Level ground walking
		Turning
		Slope walking
		Kerb crossing
		Outdoor walking
	Method
		Clinical performance
		Outcome measures
			Clinical assessments
			Gait analysis
	Results
	Discussion
	Conclusion
	Acknowledgments
	References
7. Voluntary intention-driven rehabilitation robots for the upper limb
	Introduction
	Methodology
		Participants
		Experimental platform
		Experimental procedure
		The dynamics of the robot
	Gravity compensation strategies
		An EMG-based control strategy
		Data analysis
	Results
	Discussion
	Conclusion
	References
8. Artificial sensory feedback for bionic hands
	Introduction
	Sensors
	Interfaces with the peripheral nervous system
		Targeted sensory reinnervation
		Electrical interfaces with the somatosensory nerves
		Perceptual effects of nerve stimulation
		Functional tests
		Biomimicry
		Embodiment, phantom pain, and patient acceptance
		Lower limb prostheses
	Interfaces with the central nervous system
		Somatosensory cortex
		Electrocorticography
		Intracortical microstimulation
		Perceptual effects of brain stimulation
		Functional tests
	Conclusions
	References
9. Robotic and neuromuscular electrical stimulation (NMES) hybrid system
	Introduction
	EMG-driven NMES-robots
		EMG-driven NMES-robotic hand
		EMG-driven NMES-robotic sleeve
	Clinical trials
		Early stroke UE rehabilitation by the EMG-driven NMES-robotic sleeve
		Application of the EMG-driven NMES-robotic hand in chronic stroke
		Comparison of different joint-supportive schemes in chronic stroke
	Conclusion
	References
10. Soft robotics for hand rehabilitation
	Introduction
	Materials and methods
		Actuators design and fabrication
		Actuator characterization
		Cable drive system
		User intent detection
	Results
	Conclusions and future trends
	References
Part III: Clinical Applications
11. Clinical evaluations with robots in rehabilitation
	Introduction
		The ACT-3D robotic device
	Quantifying improvements in shoulder/elbow performance following an intervention
		Progressive abduction loading therapy
		Measuring improvements in reaching distance and velocity on a robotic device
			Data analysis
			Results
	Quantifying cortical reorganization related to the hand and arm following an intervention
		ReIn-Hand intervention
		Measuring cortical activity on a robotic device
			Data analysis for cortical activity
			Results
	Conclusions
	References
12. Quantitative evaluation
	Introduction: the need for quantitative outcome measures
		Electrical impedance myography (EIM)
		EIM measurements during muscle contraction
		Application of EIM in spinal cord injury
	Muscle spasticity
		Myotonometer—validity
			Myotonometer—reliability
		Interpretation of myotonometric data
	Ultrasound imaging
		Muscle architecture changes induced by intervention
	Conclusion
	References
13. Automation in neurorehabilitation: needs addressed by clinicians
	Conventional approach in cognitive rehabilitation
		Cognitive functional evaluation
		Neurofunctional approach
		Human elements in the cognitive rehabilitation
		Types of cognitive assessments
		Computerized cognitive assessment
		Examples of computerized assessment
		Technology-enhanced cognitive assessment using a physiological signal (quantitative electroencephalography and eye tracking)
		Automation in QEEG
		Eye tracking
		Virtual reality
		Automation in functional home-based rehabilitation
		The way forward—developing the automation system for a cognitive rehabilitation program
	References
14. Translation of robot-assisted rehabilitation to clinical service in upper limb rehabilitation
	Background
	The EMG-driven robotic hand
	Clinic versus laboratory
		The clinical setting
		The laboratory setting
	Participants
	Training protocol
	Rehabilitation outcome
		Outcome evaluations and statistics
		Functional achievement after training
	Discussion
	Conclusion
	Acknowledgments
	References
Part IV: Commercialization
15. Commercialization of rehabilitation robotics in Hong Kong
	Correct time (government contribution)
	Correct place (government contribution)
	Correct person 1 (government, academia, and research contribution)
	Correct person 2 (industrial contribution)
	Correct person 3 (industrial contribution)
	Importance of a market-oriented approach
	Transfer of technologies/knowledge
	Key factors for successful commercialization
		Balance of market demand and technologies
		Identification of application sectors
		Find a key opinion leader (KOL)
		Financial support
	Company structure and management complexity
		R&D team
		Clinical team
		Marketing team
		Prototyping team
		Regulatory team
		Industrialization team
		Managing start-up and project commercialization
	Finale
Index
	A
	B
	C
	D
	E
	F
	G
	H
	I
	J
	K
	L
	M
	N
	O
	P
	Q
	R
	S
	T
	U
	V
	W
	Y
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