Lower-limb exoskeleton design for cerebral palsy … · exoskeletons in over ground gait training...
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PC Assessment Cerebral Palsy (CP) is a neurological disorder damaging a group of motor functions that are complex and patient-specific. For children, it is the most prevalent cause of permanent physical disability. Novel therapy strategies introduce wearable lower limb exoskeletons in over ground gait training for an improved rehabilitation efficiency. However, because of the complexity and variability of the gait patterns in the CP children population, it is necessary to develop a haptic exoskeleton adapting to the patient’s movements with the help of various sensors. The exoskeleton’s provided assistance is therefore constantly modulated to constrain the user’s legs around reference healthy gait trajectories while providing flexibility, transparency and comfort. Lower-limb exoskeleton design for cerebral palsy affected children Motivations Four-bar Linkage Physiological solution to model the complex knee kinematics Four moving axes of rotation: Translation added to the rotation More comfortable movement Analogous to the knee behavior (ACL, PCL, links) Accumulation of dimensional inaccuracies Design of a robotic device providing a haptic, transparent, comfortable assistance to young CP patients during gait rehabilitation in a hospital environment Goals Tristan Barjavel Sensing Potentiometers: Joint angular orientation measurements Strain gauges: Mechanical stress and human- robot interaction torques measurements Hall-effect sensors: Motor torque measurements Foot pressure sensors: Stand/swing phases differentiation Stance phase: Tight constraints (spatial, time, amount of assistance) Modulable assistance to guide the robot’s joints along healthy reference points while providing flexibility and balance support Assistive torques are computed based on the negative gradient of a potential field Swing phase: Loose constraints (spatial, time, amount of assistance) Adaptable Controls State Machine Mechanical Features 6 DOF 3 joints per leg 2 revolute joints 1 four-bar linkage Anodized aluminum and stainless steel for the mechanical structure 6.5 kg total weight Joint trajectory EPFL supervisors: Prof Dominique Pioletti at Laboratory of Biomechanical Orthopedics, Prof Silvestro Micera at Translational NeuroEngineering Chair, Harvard Medical School supervisor: Prof Paolo Bonato at Motion Analysis Lab Position control (PC) assessed with RMSE calculation between the desired position and the measured one while standing and performing steps Joint trajectory
Transcript of Lower-limb exoskeleton design for cerebral palsy … · exoskeletons in over ground gait training...
PC Assessment
Cerebral Palsy (CP) is a neurological disorder damaging a group of motor functions that are complex and patient-specific. Forchildren, it is the most prevalent cause of permanent physical disability. Novel therapy strategies introduce wearable lower limbexoskeletons in over ground gait training for an improved rehabilitation efficiency.However, because of the complexity and variability of the gait patterns in the CP children population, it is necessary to develop ahaptic exoskeleton adapting to the patient’s movements with the help of various sensors.The exoskeleton’s provided assistance is therefore constantly modulated to constrain the user’s legs around reference healthygait trajectories while providing flexibility, transparency and comfort.
Lower-limb exoskeleton design for cerebral palsy affected children
Motivations
Four-bar Linkage
Physiological solution to model the complex knee kinematics
Four moving axes of rotation:
Translation added to the rotationMore comfortable movementAnalogous to the knee behavior (ACL, PCL, links)Accumulation of dimensional inaccuracies
Design of a robotic device providing a haptic, transparent, comfortable assistance to young CP patients during gait rehabilitation in a hospital environment
Goals
Tristan Barjavel
Sensing
Potentiometers:
Joint angular orientation measurements
Strain gauges:
Mechanical stress and human-robot interaction torques measurements
Hall-effect sensors:
Motor torque measurements
Foot pressure sensors:
Stand/swing phases differentiation
Stance phase:
Tight constraints (spatial, time, amount of assistance)
Modulable assistance to guide the robot’s joints along healthy reference points while providing flexibility and balance support
Assistive torques are computed based on the negative gradient of a potential field
Swing phase:
Loose constraints (spatial, time, amount of assistance)
Adaptable Controls
State Machine
Mechanical Features
6 DOF3 joints per leg
2 revolute joints
1 four-bar linkage
Anodized aluminum and stainless steel for the mechanical structure
6.5 kg total weight
Joint trajectory
EPFL supervisors:Prof Dominique Pioletti at Laboratory of Biomechanical Orthopedics,Prof Silvestro Micera at Translational NeuroEngineering Chair,
Harvard Medical School supervisor:Prof Paolo Bonato at Motion Analysis Lab
Position control (PC) assessed with RMSE calculation between the desired position and the measured one while standing and performing steps
Joint trajectory
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