Gras et al., 2014 - Google Patents
Cooperative control of a compliant manipulator for robotic-assisted physiotherapyGras et al., 2014
- Document ID
- 665980475818306719
- Author
- Gras G
- Vitiello V
- Yang G
- Publication year
- Publication venue
- 2014 IEEE International Conference on Robotics and Automation (ICRA)
External Links
Snippet
In recent years, robotic systems have been playing an increasingly important role in physiotherapy. The aim of these platforms is to aid the recovery process from strokes or muscular damage by assisting patients to perform a number of controlled tasks, thus …
- 238000000554 physical therapy 0 title abstract description 21
Classifications
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B23/00—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes
- G09B23/28—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes for medicine
- G09B23/288—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes for medicine for artificial respiration or heart massage
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B19/00—Teaching not covered by other main groups of this subclass
- G09B19/003—Repetitive work cycles; Sequence of movements
- G09B19/0038—Sports
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B23/00—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes
- G09B23/28—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes for medicine
- G09B23/285—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes for medicine for injections, endoscopy, bronchoscopy, sigmoidscopy, insertion of contraceptive devices or enemas
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Atkeson et al. | Using humanoid robots to study human behavior | |
Fong et al. | Kinesthetic teaching of a therapist's behavior to a rehabilitation robot | |
CN105512621A (en) | Kinect-based badminton motion guidance system | |
Devanne et al. | A co-design approach for a rehabilitation robot coach for physical rehabilitation based on the error classification of motion errors | |
Salazar et al. | Path-following guidance using phantom sensation based vibrotactile cues around the wrist | |
Tanguy et al. | Computational architecture of a robot coach for physical exercises in kinaesthetic rehabilitation | |
Chaparro-Rico et al. | Design of arm exercises for rehabilitation assistance | |
Devanne | Multi-level motion analysis for physical exercises assessment in kinaesthetic rehabilitation | |
Luciani et al. | Trajectory Learning by Therapists' Demonstrations for an Upper Limb Rehabilitation Exoskeleton | |
Carmichael et al. | Towards using musculoskeletal models for intelligent control of physically assistive robots | |
Ugartemendia et al. | Machine learning for active gravity compensation in robotics: Application to neurological rehabilitation systems | |
Todrov | Studies of goal directed movements | |
Liarokapis et al. | Learning the post-contact reconfiguration of the hand object system for adaptive grasping mechanisms | |
Gras et al. | Cooperative control of a compliant manipulator for robotic-assisted physiotherapy | |
Luciani et al. | Imitation learning using Gaussian mixture models and Dynamic Movement Primitives for rehabilitation exoskeletons: a comparison | |
Moran-MacDonald | Energy injection for mechanical systems through the method of Virtual Nonholonomic Constraints | |
Wu et al. | A framework of rehabilitation-assisted robot skill representation, learning, and modulation via manifold-mappings and Gaussian processes | |
Vatsal et al. | Biomechanical design optimization of passive exoskeletons through surrogate modeling on industrial activity data | |
Younis et al. | Assist-as-needed control strategies for upper limb rehabilitation therapy: A review | |
Pernalete et al. | Eye-hand coordination assessment metrics using a multi-platform haptic system with eye-tracking and motion capture feedback | |
Haufe et al. | Reference trajectory adaptation to improve human-robot interaction: A database-driven approach | |
Beraldo et al. | AI-Enabled Framework for Augmenting Upper Limb Rehabilitation With a Social Robot | |
Starke et al. | Temporal force synergies in human grasping | |
De La Rosa Gutierrez et al. | Design goals for end-user development of robot-assisted physical training activities: a participatory design study | |
Goldfarb et al. | Toward generalization of bipedal gait cycle during stair climbing using learning from demonstration |