@article{alili_fleming_nalam_liu_dean_huang_2024, title={Abduction/Adduction Assistance From Powered Hip Exoskeleton Enables Modulation of User Step Width During Walking}, volume={71}, ISSN={["1558-2531"]}, url={http://dx.doi.org/10.1109/tbme.2023.3301444}, DOI={10.1109/TBME.2023.3301444}, abstractNote={Using wearable robotics to modulate step width in normal walking for enhanced mediolateral balance has not been demonstrated in the field. We designed a bilateral hip exoskeleton with admittance control to power hip abduction and adduction to modulate step width. Objective: As the first step to show its potential, the objective of this study was to investigate how human's step width reacted to hip exoskeleton's admittance control parameter changes during walking. Methods: Ten non-disabled individuals walked on a treadmill at a self-selected speed, while wearing our bilateral robotic hip exoskeleton. We used two equilibrium positions to define the direction of assistance. We studied the influence of multiple stiffness values in the admittance control on the participants’ step width, step length, and electromyographic (EMG) activity of the gluteus medius. Results: Step width were significantly modulated by the change of stiffness in exoskeleton control, while step length did not show significant changes. When the stiffness changed from zero to our studied stiffness values, the participants’ step width started to modulate immediately. Within 4 consecutive heel strikes right after a stiffness change, the step width showed a significant change. Interestingly, EMG activity of the gluteus medius did not change significantly regardless the applied stiffness and powered direction. Conclusion: Tuning of stiffness in admittance control of a hip exoskeleton, acting in mediolateral direction, can be a viable way for controlling step width in normal walking. Unvaried gluteus medius activity indicates that the increase in step width were mainly caused by the assistive torque applied by the exoskeleton. Significance: Our study results pave a new way for future design and control of wearable robotics in enhancing mediolateral walking balance for various rehabilitation applications.}, number={1}, journal={IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Alili, Abbas and Fleming, Aaron and Nalam, Varun and Liu, Ming and Dean, Jesse and Huang, He}, year={2024}, month={Jan}, pages={334–342} }
 @article{alili_nalam_li_liu_feng_si_huang_2023, title={A Novel Framework to Facilitate User Preferred Tuning for a Robotic Knee Prosthesis}, volume={31}, ISSN={["1558-0210"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85147231065&partnerID=MN8TOARS}, DOI={10.1109/TNSRE.2023.3236217}, abstractNote={The tuning of robotic prosthesis control is essential to provide personalized assistance to individual prosthesis users. Emerging automatic tuning algorithms have shown promise to ease the device personalization procedure. However, very few automatic tuning algorithms consider the user preference as the tuning goal, which may limit the adoptability of the robotic prosthesis. In this study, we propose and evaluate a novel prosthesis control tuning framework for a robotic knee prosthesis, which could enable user preferred robot behavior in the device tuning process. The framework consists of 1) a User-Controlled Interface that allows the user to select their preferred knee kinematics in gait and 2) a reinforcement learning-based algorithm for tuning high-dimension prosthesis control parameters to meet the desired knee kinematics. We evaluated the performance of the framework along with usability of the developed user interface. In addition, we used the developed framework to investigate whether amputee users can exhibit a preference between different profiles during walking and whether they can differentiate between their preferred profile and other profiles when blinded. The results showed effectiveness of our developed framework in tuning 12 robotic knee prosthesis control parameters while meeting the user-selected knee kinematics. A blinded comparative study showed that users can accurately and consistently identify their preferred prosthetic control knee profile. Further, we preliminarily examined gait biomechanics of the prosthesis users when walking with different prosthesis control and did not find clear difference between walking with preferred prosthesis control and when walking with normative gait control parameters. This study may inform future translation of this novel prosthesis tuning framework for home or clinical use.}, journal={IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING}, author={Alili, Abbas and Nalam, Varun and Li, Minhan and Liu, Ming and Feng, Jing and Si, Jennie and Huang, He}, year={2023}, pages={895–903} }
 @article{yu_nalam_alili_huang_2023, title={A Wearable Robotic Rehabilitation System for Neuro-rehabilitation Aimed at Enhancing Mediolateral Balance}, ISSN={["2153-0858"]}, DOI={10.1109/IROS55552.2023.10341735}, abstractNote={There is increasing evidence of the role of compromised mediolateral balance in falls and the need for rehabilitation specifically focused on mediolateral direction for various populations with motor deficits. To address this need, we have developed a neurorehabilitation platform by integrating a wearable robotic hip abduction-adduction exoskeleton with a visual interface. The platform is expected to influence and rehabilitate the underlying visuomotor mechanisms in individuals by having users perform motion tasks based on visual feedback while the robot applies various controlled resistances governed by the admittance controller implemented in the robot. A preliminary study was performed on 3 non disabled individuals to analyze the performance of the system and observe any adaptation in hip joint kinematics and kinetics as a result of the visuomotor training under 4 different admittance conditions. All three subjects exhibited increased consistency of motion during training and interlimb coordination to achieve motion tasks, demonstrating the utility of the system. Further analysis of observed human-robot torque interactions and electromyography (EMG) signals, and its implication in neurorehabilitation aimed at populations suffering from chronic stroke are discussed.}, journal={2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, IROS}, author={Yu, Zhenyuan and Nalam, Varun and Alili, Abbas and Huang, He}, year={2023}, pages={155–160} }
 @article{alili_nalam_fleming_liu_dean_huang_2023, title={Closed-Loop Feedback Control of Human Step Width During Walking by Mediolaterally Acting Robotic Hip Exoskeleton}, ISSN={["2153-0858"]}, DOI={10.1109/IROS55552.2023.10342127}, abstractNote={Maintaining balance during gait in the mediolateral direction requires more active motor control than in the anteroposterior direction. Step width modulation is a key strategy used by healthy individuals to achieve mediolateral walking balance, but it can be disrupted in populations with poor sensorimotor integration and weak hip abductors, such as the elderly, stroke patients, and people with lower limb amputation. Wearable hip exoskeletons have the potential to serve as assistive or rehabilitation devices for these populations, but there has been limited research on their appropriate usage. In this study, we successfully demonstrated the feasibility of controlling step width using a mediolaterally acting robotic hip exoskeleton. We were able to effectively adjust the user's step width by increasing or decreasing it to predefined targets through the regulation of admittance control parameters governing the device. The maximum average error to increase or decrease the step width was 1.2 cm. This research has the potential to facilitate the development of assistive and rehabilitation applications focused on enhancing the mediolateral gait balance of individuals with neurological impairments, elderly individuals, and amputees via the control of step width.}, journal={2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)}, author={Alili, Abbas and Nalam, Varun and Fleming, Aaron and Liu, Ming and Dean, Jesse and Huang, Helen}, year={2023}, pages={6097–6102} }
 @article{alili_nalam_li_liu_si_huang_2021, title={User Controlled Interface for Tuning Robotic Knee Prosthesis}, ISSN={["2153-0858"]}, url={http://dx.doi.org/10.1109/iros51168.2021.9636264}, DOI={10.1109/IROS51168.2021.9636264}, abstractNote={The tuning process for a robotic prosthesis is a challenging and time-consuming task both for users and clinicians. An automatic tuning approach using reinforcement learning (RL) has been developed for a knee prosthesis to address the challenges of manual tuning methods. The algorithm tunes the optimal control parameters based on the provided knee joint profile that the prosthesis is expected to replicate during gait safely. This paper presents an intuitive interface designed for the prosthesis users and clinicians to choose the preferred knee joint profile during gait and use the autotuner to replicate in the prosthesis. The interface-based approach is validated by observing the ability of the tuning algorithm to successfully converge to various alternate knee profiles by testing on two able-bodied subjects walking with a robotic knee prosthesis. The algorithm was found to converge successfully in an average duration of 1.15 min for the first subject and 2.31 min for the second subject. Further, the subjects displayed different preferences for optimal profiles reinforcing the need to tune alternate profiles. The implications of the results in the tuning of robotic prosthetic devices are discussed.}, journal={2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)}, publisher={IEEE}, author={Alili, Abbas and Nalam, Varun and Li, Minhan and Liu, Ming and Si, Jennie and Huang, He}, year={2021}, pages={6190–6195} }