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Novel swing-assist un-motorized exoskeletons for gait training.

Mankala KK, Banala SK, Agrawal SK - J Neuroeng Rehabil (2009)

Bottom Line: On analysis, we found that at 2.0 mph, the device was effective in reducing the maximum hip torque requirement and the knee joint torque during the beginning of the swing.We believe that the results can be further improved in the future.Nevertheless, this promises to provide a useful and effective methodology for design of un-motorized exoskeletons to assist and train swing of motor-impaired patients.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Mechanical Engineering, University of Delaware, Newark, DE 19716, USA. kalyan.mankala@asml.com

ABSTRACT

Background: Robotics is emerging as a promising tool for functional training of human movement. Much of the research in this area over the last decade has focused on upper extremity orthotic devices. Some recent commercial designs proposed for the lower extremity are powered and expensive - hence, these could have limited affordability by most clinics. In this paper, we present a novel un-motorized bilateral exoskeleton that can be used to assist in treadmill training of motor-impaired patients, such as with motor-incomplete spinal cord injury. The exoskeleton is designed such that the human leg will have a desirable swing motion, once it is strapped to the exoskeleton. Since this exoskeleton is un-motorized, it can potentially be produced cheaply and could reduce the physical demand on therapists during treadmill training.

Results: A swing-assist bilateral exoskeleton was designed and fabricated at the University of Delaware having the following salient features: (i) The design uses torsional springs at the hip and the knee joints to assist the swing motion. The springs get charged by the treadmill during stance phase of the leg and provide propulsion forces to the leg during swing. (ii) The design of the exoskeleton uses simple dynamic models of sagittal plane walking, which are used to optimize the parameters of the springs so that the foot can clear the ground and have a desirable forward motion during walking. The bilateral exoskeleton was tested on a healthy subject during treadmill walking for a range of walking speeds between 1.0 mph and 4.0 mph. Joint encoders and interface force-torque sensors mounted on the exoskeleton were used to evaluate the effectiveness of the exoskeleton in terms of the hip and knee joint torques applied by the human during treadmill walking.

Conclusion: We compared two different cases. In case 1, we estimated the torque applied by the human joints when walking with the device using the joint kinematic data and interface force-torque sensors. In case 2, we calculated the required torque to perform a similar gait only using the kinematic data collected from joint motion sensors. On analysis, we found that at 2.0 mph, the device was effective in reducing the maximum hip torque requirement and the knee joint torque during the beginning of the swing. These behaviors were retained as the treadmill speed was changed between 1-4 mph. These results were remarkable considering the simplicity of the dynamic model, model uncertainty, non-ideal spring behavior, and friction in the joints. We believe that the results can be further improved in the future. Nevertheless, this promises to provide a useful and effective methodology for design of un-motorized exoskeletons to assist and train swing of motor-impaired patients.

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Joint trajectories from an experimetal result. (a) Hip versus Knee during a trial when treadmill speed was 2 mph. Red lines represent swing phase extracted from full step data represented by red and blue lines combined. Solid black lines represent average swing phase. (b) Hip angle vs time (c) Knee angle vs time.
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Figure 7: Joint trajectories from an experimetal result. (a) Hip versus Knee during a trial when treadmill speed was 2 mph. Red lines represent swing phase extracted from full step data represented by red and blue lines combined. Solid black lines represent average swing phase. (b) Hip angle vs time (c) Knee angle vs time.

Mentions: In the current device, the encoder and force-torque sensor data were collected using a dSpace 1103 system at 1000 Hz. The force-torque sensors were manufactured by ATI and the encoders by USDigital. The subject walked on the treadmill for 15 minutes with the exoskeleton to become acclimated. Data was collected when a subject walked on a treadmill at different speeds, ranging from 1.0 mph to 4.0 mph. Figure 7(a) shows the joint data, θ2 vs θ1, of a trial where the treadmill speed was 2 mph. Note that the design was optimized for walking at a treadmill speed of around 2.0 mph; hence, we show the results of this trial in more detail. In this figure, multiple loops indicate multiple steps during a trial. Red lines represent just the swing phase, extracted from the full step data represented by both red and blue lines. Solid black line represents the average swing data, computed by averaging over the multiple cycles. In order to perform averaging, we normalized the step data to a fixed time length. The same data is plotted against time in Figs. 7(b), (c). A 20 point moving average was used to smoothen the joint encoder data to compute the joint velocity and acceleration, using central difference scheme.


Novel swing-assist un-motorized exoskeletons for gait training.

Mankala KK, Banala SK, Agrawal SK - J Neuroeng Rehabil (2009)

Joint trajectories from an experimetal result. (a) Hip versus Knee during a trial when treadmill speed was 2 mph. Red lines represent swing phase extracted from full step data represented by red and blue lines combined. Solid black lines represent average swing phase. (b) Hip angle vs time (c) Knee angle vs time.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2713968&req=5

Figure 7: Joint trajectories from an experimetal result. (a) Hip versus Knee during a trial when treadmill speed was 2 mph. Red lines represent swing phase extracted from full step data represented by red and blue lines combined. Solid black lines represent average swing phase. (b) Hip angle vs time (c) Knee angle vs time.
Mentions: In the current device, the encoder and force-torque sensor data were collected using a dSpace 1103 system at 1000 Hz. The force-torque sensors were manufactured by ATI and the encoders by USDigital. The subject walked on the treadmill for 15 minutes with the exoskeleton to become acclimated. Data was collected when a subject walked on a treadmill at different speeds, ranging from 1.0 mph to 4.0 mph. Figure 7(a) shows the joint data, θ2 vs θ1, of a trial where the treadmill speed was 2 mph. Note that the design was optimized for walking at a treadmill speed of around 2.0 mph; hence, we show the results of this trial in more detail. In this figure, multiple loops indicate multiple steps during a trial. Red lines represent just the swing phase, extracted from the full step data represented by both red and blue lines. Solid black line represents the average swing data, computed by averaging over the multiple cycles. In order to perform averaging, we normalized the step data to a fixed time length. The same data is plotted against time in Figs. 7(b), (c). A 20 point moving average was used to smoothen the joint encoder data to compute the joint velocity and acceleration, using central difference scheme.

Bottom Line: On analysis, we found that at 2.0 mph, the device was effective in reducing the maximum hip torque requirement and the knee joint torque during the beginning of the swing.We believe that the results can be further improved in the future.Nevertheless, this promises to provide a useful and effective methodology for design of un-motorized exoskeletons to assist and train swing of motor-impaired patients.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Mechanical Engineering, University of Delaware, Newark, DE 19716, USA. kalyan.mankala@asml.com

ABSTRACT

Background: Robotics is emerging as a promising tool for functional training of human movement. Much of the research in this area over the last decade has focused on upper extremity orthotic devices. Some recent commercial designs proposed for the lower extremity are powered and expensive - hence, these could have limited affordability by most clinics. In this paper, we present a novel un-motorized bilateral exoskeleton that can be used to assist in treadmill training of motor-impaired patients, such as with motor-incomplete spinal cord injury. The exoskeleton is designed such that the human leg will have a desirable swing motion, once it is strapped to the exoskeleton. Since this exoskeleton is un-motorized, it can potentially be produced cheaply and could reduce the physical demand on therapists during treadmill training.

Results: A swing-assist bilateral exoskeleton was designed and fabricated at the University of Delaware having the following salient features: (i) The design uses torsional springs at the hip and the knee joints to assist the swing motion. The springs get charged by the treadmill during stance phase of the leg and provide propulsion forces to the leg during swing. (ii) The design of the exoskeleton uses simple dynamic models of sagittal plane walking, which are used to optimize the parameters of the springs so that the foot can clear the ground and have a desirable forward motion during walking. The bilateral exoskeleton was tested on a healthy subject during treadmill walking for a range of walking speeds between 1.0 mph and 4.0 mph. Joint encoders and interface force-torque sensors mounted on the exoskeleton were used to evaluate the effectiveness of the exoskeleton in terms of the hip and knee joint torques applied by the human during treadmill walking.

Conclusion: We compared two different cases. In case 1, we estimated the torque applied by the human joints when walking with the device using the joint kinematic data and interface force-torque sensors. In case 2, we calculated the required torque to perform a similar gait only using the kinematic data collected from joint motion sensors. On analysis, we found that at 2.0 mph, the device was effective in reducing the maximum hip torque requirement and the knee joint torque during the beginning of the swing. These behaviors were retained as the treadmill speed was changed between 1-4 mph. These results were remarkable considering the simplicity of the dynamic model, model uncertainty, non-ideal spring behavior, and friction in the joints. We believe that the results can be further improved in the future. Nevertheless, this promises to provide a useful and effective methodology for design of un-motorized exoskeletons to assist and train swing of motor-impaired patients.

Show MeSH
Related in: MedlinePlus