NSF Award
1915872
The natural patterns of human movement depend on interactions between the nervous system, muscles and skeleton. A problem with any of these elements--perhaps due to medical conditions, illnesses or injuries--can lead to movement limitations. In such cases, people may follow physical therapy procedures to recover the loss or change in movement ability. Currently, robots and exoskeletons are used in physical therapy to help individuals return to their prior level of functioning and to assist them to do activities-of-daily living (ADL). However, these robots and exoskeletons do not align with the human anatomical joints, which can result in discomfort or injury to the user and affect the success of the rehabilitation therapy. In this research project, human joint motions during ADL will be studied, recorded, and analyzed using video motion capture data and musculoskeletal computer simulations. The analyzed human motion patterns will be used to inspire the design of bio-exoskeletons that are capable of mimicking the complex 3D motions involved in human movement. The bio-inspired exoskeletons developed will then be compared to the traditional exoskeletons designed to mimic a human joint. The outcome of the comparison study will help to advance the knowledge in the design and utilization of bio-exoskeletons for the improved synergy between the human-exoskeleton systems in medical, industrial, and military applications. To inspire the new generation and STEM education, findings will also be shared with the public via publication, exhibitions at the Exploration Place science museum in Wichita, and university sponsored summer camps for K-12 students. Additionally, at the university level, the team will integrate research findings from the proposed work into the undergraduate and graduate courses to motivate students to perform systematic research and to reduce conceptual learning barriers of assistive devices through the implementation of Project-Based-Learning (PBL) approaches in the classroom.<br/><br/>The objective of this project is to investigate a correlation model between parameters involved in human joint movements in the fitting and alignment of exoskeletons to a human body for an effective human-exoskeleton cooperation. Traditionally, exoskeletons are designed to align with the human joint axes of motion by assigning each human joint with an equivalent exoskeleton joint (e.g. a hinge joint for the elbow) that assumes that the location of the axis can be accurately known, and that such a fixed axis exists for the range of motion of the joint or set of joints. Unfortunately, this is not always the case. The compound motion of joints makes their alignment with an exoskeleton more difficult and misalignment can create large stresses on the attached systems and underlying human anatomy, giving rise to the need for novel exoskeleton design strategies that permit the complex 3D motions independent of anatomical measures and landmarks. To address this need, the Research Plan is organized under four tasks. The FIRST Task is to collect joint movement parameters involved in human joint movements (hand and arm) while performing desired limb trajectories. Conventional motion capture systems (MoCap) will be combined with a mobile MoCap system that uses sensors to obtain inertial measurements that are communicated wirelessly to a mobile data logger, e.g., a smartphone. The data base assembled will provide 1) fundamental knowledge on the underlying human limb motion and 2) techniques to identify and select functional limb motion for a desired task. The SECOND Task is to analyze, model, and simulate the parameters involved in human joint movements using a musculoskeletal software application. The parameters of an arm, wrist, and hand musculoskeletal model will be scaled using the OpenSim Scale Model tool to best fit the experimentally measured subject mass and marker positions. The simulations provide 1) muscle force interaction and joint reaction forces during the execution of the desired motions and 2) a tool for the identification of sources for misalignment and fitting challenges. The THIRD Task is to investigate bio-inspired exoskeletons based on the related human joint parameters related to the desired trajectory of the human limb. This task will provide: 1) geometrical and algebraic insight\representation of the human limb workspace based on the motion captured data and 2) an atlas of mechanism topologies and their workspaces to closely approximate the geometrical pattern of the human limb workspace. The FOURTH Task is to prototypes and investigate the correlation between parameters and exoskeleton fitting and alignments. A bio-inspired prototype will be fabricated using an additive manufacturing process followed by integration of electronic components for real-time control and feedback. The bio-inspired exoskeletons will be compared to a 3 DOF joint-based exoskeleton previously developed by the investigators. The exoskeletons will be mounted on a wheelchair and be used in human subject testing on persons with reduced upper limb mobility, and the ADL performed will provide datasets such as trajectory path, EMG signals, FMG readings, and effectiveness and comparative analysis using the two different exoskeleton mechanisms. Data collected will be used to 1) develop a correlation model for the two exoskeletons independently and 2) to assess the intervention of each of the exoskeleton designs (the task-based approach based on the bioinspired method and joint-to-joint alignment-based design approaches).<br/><br/>This project is jointly funded by the Disabilities and Rehabilitation Engineering (DARE) program and the Established Program to Stimulate Competitive Research (EPSCoR).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
