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- Creators: Marshall, Kimberly
Description
The world population is aging. Age-related disorders such as stroke and spinal cord injury are increasing rapidly, and such patients often suffer from mobility impairment. Wearable robotic exoskeletons are developed that serve as rehabilitation devices for these patients. In this thesis, a knee exoskeleton design with higher torque output compared to the first version, is designed and fabricated.
A series elastic actuator is one of the many actuation mechanisms employed in exoskeletons. In this mechanism a torsion spring is used between the actuator and human joint. It serves as torque sensor and energy buffer, making it compact and
safe.
A version of knee exoskeleton was developed using the SEA mechanism. It uses worm gear and spur gear combination to amplify the assistive torque generated from the DC motor. It weighs 1.57 kg and provides a maximum assistive torque of 11.26 N·m. It can be used as a rehabilitation device for patients affected with knee joint impairment.
A new version of exoskeleton design is proposed as an improvement over the first version. It consists of components such as brushless DC motor and planetary gear that are selected to meet the design requirements and biomechanical considerations. All the other components such as bevel gear and torsion spring are selected to be compatible with the exoskeleton. The frame of the exoskeleton is modeled in SolidWorks to be modular and easy to assemble. It is fabricated using sheet metal aluminum. It is designed to provide a maximum assistive torque of 23 N·m, two times over the present exoskeleton. A simple brace is 3D printed, making it easy to wear and use. It weighs 2.4 kg.
The exoskeleton is equipped with encoders that are used to measure spring deflection and motor angle. They act as sensors for precise control of the exoskeleton.
An impedance-based control is implemented using NI MyRIO, a FPGA based controller. The motor is controlled using a motor driver and powered using an external battery source. The bench tests and walking tests are presented. The new version of exoskeleton is compared with first version and state of the art devices.
A series elastic actuator is one of the many actuation mechanisms employed in exoskeletons. In this mechanism a torsion spring is used between the actuator and human joint. It serves as torque sensor and energy buffer, making it compact and
safe.
A version of knee exoskeleton was developed using the SEA mechanism. It uses worm gear and spur gear combination to amplify the assistive torque generated from the DC motor. It weighs 1.57 kg and provides a maximum assistive torque of 11.26 N·m. It can be used as a rehabilitation device for patients affected with knee joint impairment.
A new version of exoskeleton design is proposed as an improvement over the first version. It consists of components such as brushless DC motor and planetary gear that are selected to meet the design requirements and biomechanical considerations. All the other components such as bevel gear and torsion spring are selected to be compatible with the exoskeleton. The frame of the exoskeleton is modeled in SolidWorks to be modular and easy to assemble. It is fabricated using sheet metal aluminum. It is designed to provide a maximum assistive torque of 23 N·m, two times over the present exoskeleton. A simple brace is 3D printed, making it easy to wear and use. It weighs 2.4 kg.
The exoskeleton is equipped with encoders that are used to measure spring deflection and motor angle. They act as sensors for precise control of the exoskeleton.
An impedance-based control is implemented using NI MyRIO, a FPGA based controller. The motor is controlled using a motor driver and powered using an external battery source. The bench tests and walking tests are presented. The new version of exoskeleton is compared with first version and state of the art devices.
ContributorsJhawar, Vaibhav (Author) / Zhang, Wenlong (Thesis advisor) / Sugar, Thomas G. (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2018
Description
Wearable robotics has gained huge popularity in recent years due to its wide applications in rehabilitation, military, and industrial fields. The weakness of the skeletal muscles in the aging population and neurological injuries such as stroke and spinal cord injuries seriously limit the abilities of these individuals to perform daily activities. Therefore, there is an increasing attention in the development of wearable robots to assist the elderly and patients with disabilities for motion assistance and rehabilitation. In military and industrial sectors, wearable robots can increase the productivity of workers and soldiers. It is important for the wearable robots to maintain smooth interaction with the user while evolving in complex environments with minimum effort from the user. Therefore, the recognition of the user's activities such as walking or jogging in real time becomes essential to provide appropriate assistance based on the activity.
This dissertation proposes two real-time human activity recognition algorithms intelligent fuzzy inference (IFI) algorithm and Amplitude omega ($A \omega$) algorithm to identify the human activities, i.e., stationary and locomotion activities. The IFI algorithm uses knee angle and ground contact forces (GCFs) measurements from four inertial measurement units (IMUs) and a pair of smart shoes. Whereas, the $A \omega$ algorithm is based on thigh angle measurements from a single IMU.
This dissertation also attempts to address the problem of online tuning of virtual impedance for an assistive robot based on real-time gait and activity measurement data to personalize the assistance for different users. An automatic impedance tuning (AIT) approach is presented for a knee assistive device (KAD) in which the IFI algorithm is used for real-time activity measurements. This dissertation also proposes an adaptive oscillator method known as amplitude omega adaptive oscillator ($A\omega AO$) method for HeSA (hip exoskeleton for superior augmentation) to provide bilateral hip assistance during human locomotion activities. The $A \omega$ algorithm is integrated into the adaptive oscillator method to make the approach robust for different locomotion activities. Experiments are performed on healthy subjects to validate the efficacy of the human activities recognition algorithms and control strategies proposed in this dissertation. Both the activity recognition algorithms exhibited higher classification accuracy with less update time. The results of AIT demonstrated that the KAD assistive torque was smoother and EMG signal of Vastus Medialis is reduced, compared to constant impedance and finite state machine approaches. The $A\omega AO$ method showed real-time learning of the locomotion activities signals for three healthy subjects while wearing HeSA. To understand the influence of the assistive devices on the inherent dynamic gait stability of the human, stability analysis is performed. For this, the stability metrics derived from dynamical systems theory are used to evaluate unilateral knee assistance applied to the healthy participants.
This dissertation proposes two real-time human activity recognition algorithms intelligent fuzzy inference (IFI) algorithm and Amplitude omega ($A \omega$) algorithm to identify the human activities, i.e., stationary and locomotion activities. The IFI algorithm uses knee angle and ground contact forces (GCFs) measurements from four inertial measurement units (IMUs) and a pair of smart shoes. Whereas, the $A \omega$ algorithm is based on thigh angle measurements from a single IMU.
This dissertation also attempts to address the problem of online tuning of virtual impedance for an assistive robot based on real-time gait and activity measurement data to personalize the assistance for different users. An automatic impedance tuning (AIT) approach is presented for a knee assistive device (KAD) in which the IFI algorithm is used for real-time activity measurements. This dissertation also proposes an adaptive oscillator method known as amplitude omega adaptive oscillator ($A\omega AO$) method for HeSA (hip exoskeleton for superior augmentation) to provide bilateral hip assistance during human locomotion activities. The $A \omega$ algorithm is integrated into the adaptive oscillator method to make the approach robust for different locomotion activities. Experiments are performed on healthy subjects to validate the efficacy of the human activities recognition algorithms and control strategies proposed in this dissertation. Both the activity recognition algorithms exhibited higher classification accuracy with less update time. The results of AIT demonstrated that the KAD assistive torque was smoother and EMG signal of Vastus Medialis is reduced, compared to constant impedance and finite state machine approaches. The $A\omega AO$ method showed real-time learning of the locomotion activities signals for three healthy subjects while wearing HeSA. To understand the influence of the assistive devices on the inherent dynamic gait stability of the human, stability analysis is performed. For this, the stability metrics derived from dynamical systems theory are used to evaluate unilateral knee assistance applied to the healthy participants.
ContributorsChinimilli, Prudhvi Tej (Author) / Redkar, Sangram (Thesis advisor) / Zhang, Wenlong (Thesis advisor) / Sugar, Thomas G. (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2018
Description
Lower-limb wearable assistive robots could alter the users gait kinematics by inputting external power, which can be interpreted as mechanical perturbation to subject normal gait. The change in kinematics may affect the dynamic stability. This work attempts to understand the effects of different physical assistance from these robots on the gait dynamic stability.
A knee exoskeleton and ankle assistive device (Robotic Shoe) are developed and used to provide walking assistance. The knee exoskeleton provides personalized knee joint assistive torque during the stance phase. The robotic shoe is a light-weighted mechanism that can store the potential energy at heel strike and release it by using an active locking mechanism at the terminal stance phase to provide push-up ankle torque and assist the toe-off. Lower-limb Kinematic time series data are collected for subjects wearing these devices in the passive and active mode. The changes of kinematics with and without these devices on lower-limb motion are first studied. Orbital stability, as one of the commonly used measure to quantify gait stability through calculating Floquet Multipliers (FM), is employed to asses the effects of these wearable devices on gait stability. It is shown that wearing the passive knee exoskeleton causes less orbitally stable gait for users, while the knee joint active assistance improves the orbital stability compared to passive mode. The robotic shoe only affects the targeted joint (right ankle) kinematics, and wearing the passive mechanism significantly increases the ankle joint FM values, which indicates less walking orbital stability. More analysis is done on a mechanically perturbed walking public data set, to show that orbital stability can quantify the effects of external mechanical perturbation on gait dynamic stability. This method can further be used as a control design tool to ensure gait stability for users of lower-limb assistive devices.
A knee exoskeleton and ankle assistive device (Robotic Shoe) are developed and used to provide walking assistance. The knee exoskeleton provides personalized knee joint assistive torque during the stance phase. The robotic shoe is a light-weighted mechanism that can store the potential energy at heel strike and release it by using an active locking mechanism at the terminal stance phase to provide push-up ankle torque and assist the toe-off. Lower-limb Kinematic time series data are collected for subjects wearing these devices in the passive and active mode. The changes of kinematics with and without these devices on lower-limb motion are first studied. Orbital stability, as one of the commonly used measure to quantify gait stability through calculating Floquet Multipliers (FM), is employed to asses the effects of these wearable devices on gait stability. It is shown that wearing the passive knee exoskeleton causes less orbitally stable gait for users, while the knee joint active assistance improves the orbital stability compared to passive mode. The robotic shoe only affects the targeted joint (right ankle) kinematics, and wearing the passive mechanism significantly increases the ankle joint FM values, which indicates less walking orbital stability. More analysis is done on a mechanically perturbed walking public data set, to show that orbital stability can quantify the effects of external mechanical perturbation on gait dynamic stability. This method can further be used as a control design tool to ensure gait stability for users of lower-limb assistive devices.
ContributorsRezayat Sorkhabadi, Seyed Mostafa (Author) / Zhang, Wenlong (Thesis advisor) / Lee, Hyunglae (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2018
Description
Prosthetic sockets are a static interface for dynamic residual limbs. As the user's activity level increases, the volume of the residual limb decreases by up to 11% and increases by as much as 7% after activity. Currently, volume fluctuation is addressed by adding/removing prosthetic socks to change the profile of the residual limb. However, this is time consuming. These painful/functional issues demand a prosthetic socket with an adjustable interface that can adapt to the user's needs. This thesis presents a prototype design for a dynamic soft robotic interface which addresses this need. The actuators are adjustable depending on the user's activity level, and their structure provides targeted compression to the soft tissue which helps to limit movement of the bone relative to the socket. The engineering process was used to create this design by defining system level requirements, exploring the design space, selecting a design, and then using testing/analysis to optimize that design. The final design for the soft robotic interface meets the applicable requirements, while other requirements for the electronics/controls will be completed as future work. Testing of the prototype demonstrated promising potential for the design with further refinement. Work on this project should be continued in future research/thesis projects in order to create a viable consumer product which can improve lower limb amputee's quality of life.
ContributorsHolmes, Breanna Swift (Author) / Zhang, Wenlong (Thesis director) / Polygerinos, Panagiotis (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
ContributorsMarshall, Kimberly (Performer) / Meszler, Alexander (Performer) / Yatso, Toby (Narrator) / ASU Library. Music Library (Publisher)
Created2018-09-16
Description
The thesis covers the development and modeling of the supervisory hybrid controller using two different methods to achieve real-world optimization and power split of a parallel hybrid vehicle with a fixed shaft connecting the Internal Combustion Engine (ICE) and Electric Motor (EM). The first strategy uses a rule based controller to determine modes the vehicle should operate in. This approach is well suited for real-world applications. The second approach uses Sequential Quadratic Programming (SQP) approach in conjunction with an Equivalent Consumption Minimization Strategy (ECMS) strategy to keep the vehicle in the most efficient operating regions. This latter method is able to operate the vehicle in various drive cycles while maintaining the SOC with-in allowed charge sustaining (CS) limits. Further, the overall efficiency of the vehicle for all drive cycles is increased. The limitation here is the that process is computationally expensive; however, with advent of the low cost high performance hardware this method can be used for the hybrid vehicle control.
ContributorsMaady, Rashad Kamal (Author) / Redkar, Sangram (Thesis advisor) / Mayyas, Abdel R (Thesis advisor) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2017
ContributorsMarshall, Kimberly (Performer) / ASU Library. Music Library (Publisher)
Created2019-03-17
ContributorsMarshall, Kimberly (Performer) / ASU Library. Music Library (Publisher)
Created2007-03-11
ContributorsMarshall, Kimberly (Performer) / Cook, L. Keith (Performer) / Zweiback, Adam J (Performer) / ASU Library. Music Library (Publisher)
Created2000-02-06
ContributorsMarshall, Kimberly (Performer) / ASU Library. Music Library (Publisher)
Created2008-03-09