REU/ELEVATE/CHNF SUMMER PROJECTS 2020
Name of Project: Impact of obesity on gait kinematic and kinetic parameters
Description: In the United States, approximately one in three adults are considered to have obesity. Obesity puts individuals at risk for a variety of secondary complications and has been shown to affect gait patterns. The purpose of this project is to determine kinematic and kinetic differences in gait when walking on the Computer Assisted Rehabilitation Environment (CAREN) with/without an additional load.
Project Level: Advanced
Preferred Major/Background: Engineering preferred, specifically biomedical or computer engineering
Required Skills/Courses: Proficiency in Matlab is required; proficiency in Microsoft Excel is preferred; experience or knowledge of biomechanics and inverse dynamics is preferred
Submitted by: Hailee Kulich, Dr. Alicia Koontz
Name of Project: Adaptor tools for Assistive Robotic Manipulators
Description: This development project will address the less efficient manipulation performance in existing ARMs for everyday manipulation tasks by designing the adaptive tools.
Project Level: Basic
Preferred Major/Background: Mechanical Engineer
Required Skills/Courses: Mechanical design using Solidworks or other CAD software
Submitted by: Dr. Joshua Chung, Dr. Dan Ding
Name of Project: Vision-Guided Shared-Control for Assistive Robotic Manipulators
Description: This development project will address the lack of effective and efficient control in existing ARMs for everyday manipulation tasks by developing a novel but practical vision-guided shared (VGS) control method. We will use fiducial markers fixed to objects of interest to simplify the challenges that face modern day high-fidelity perception of robotic systems for real-world applications (e.g., reliability, detection rates, and immunity to lighting).
Project Level: Basic
Preferred Major/Background: Computer science
Basic knowledge of computer vision and robotics
Required Skills/Courses: Python, Robotic Operating System
Submitted by: Dr. Joshua Chung, Dr. Dan Ding
Name of Project: Using Wearable Sensors to Track Movements and Physical Activity of Wheelchair Users
Description: The purpose of this study is to collect and process data from wearable devices and develop machine-learning algorithms to identify movement patterns and physical activity parameters in wheelchair users. The algorithms will enable end-users who use wheelchairs for mobility to track their habitual physical activity and help clinicians develop activity plans for these individuals.
Project Level: Intermediate
Preferred Major/Background: Computer/Information Science or any major with the ability to code with Matlab or Python.
Required Skills/Courses: Matlab or Python
Submitted by: Dr. Dan Ding
Name of Project: Evaluating limb accelerations from individuals with spinal cord injury in relation to neuromuscular impairment and mobility
Description: From very early in the acute phase after spinal cord injury (SCI), strength and sensation are measured through clinical assessment to monitor neurorecovery. While these assessments can be performed relatively quickly and without any additional equipment, they are often an inaccurate representation of the actual level of impairment which may mask small differences in impairment that may be clinically relevant, especially in the application of prediction models for mobility. Based on previous studies and preliminary analysis, we believe that limb movements measured by wearable accelerometers may be related to clinical measures of neuromuscular impairment (strength, sensation, spasticity) and mobility (walking, wheelchair use).
Project Level: Advanced
Preferred Major/Background: Engineering (with coding or signals courses completed), computer science
Required Skills/Courses: Required: proficiency in Matlab, Python, or similar coding language, knowledge of signal analysis and processing
Suggested: statistical software (i.e. SPSS), knowledge of statistical tests, machine learning, and signal analysis
Submitted by: Stephanie Rigot, Dr. Lynn Worobey, Dr. Michael Boninger
Name of Project: The relationship between ambulatory ability and personal, psychosocial, and environmental factors among individuals with chronic spinal cord injury
Description: One of the first questions often asked after a spinal cord injury (SCI) is “Will I walk again?”. While there are clinical prediction rules that estimate the probability of becoming an independent ambulator based on simple clinical tests, these rules lack accuracy among the population that needs them the most, those with moderate impairments. While studies have evaluated the influence of personal, psychosocial, and environmental factors (PPEF) in the SCI population, how they affect mobility outcomes has not been examined. Successful adjustment to SCI relies on factors such as coping style, social support, and home and community accessibility, which are influenced by socioeconomic status. In addition, personal factors such as race, comorbidities, and a history of substance abuse can impact ambulatory ability. As a first step towards integrating PPEF into a new clinical prediction rule for ambulatory ability, we aim to establish the relationship between these factors and mobility among a population with chronic SCI.
Project Level: Basic
Preferred Major/Background: Rehab Science, public health, psychology
Required Skills/Courses: Proficient in excel, statistical software (i.e. SPSS)
knowledge of statistical tests
Submitted by: Stephanie Rigot, Dr. Lynn Worobey, Dr. Michael Boninger
Name of Project: Cornhole Catapult interface
Description: A catapult is being developed to toss a bean bag for people with limited arm function to participate in cornhole. This project will develop the controller for the device using embedded systems and app development
Project Level: Intermediate
Preferred Major/Background: Electrical Engineering, Computer Science
Required Skills/Courses: Experience with app and/or microcontroller coding
Submitted by: Dr. Jonathan Duvall
Name of Project: Cornhole catapult device
Description: In order to allow people with limited arm function to participate with their friends at tailgates or other events, this project will make a catapult for tossing a bean bag. This project will involve the design and fabrication of the arm itself.
Project Level: Intermediate
Preferred Major/Background: Mechanical Engineering, Physics
Required Skills/Courses: Mechanical design
Statics and Dynamics
Submitted by: Dr. Jonathan Duvall
Name of Project: Robotic bed and power wheelchair for transfers
Description: The AgileLife robotic transfer system is bed that automatically transfers a person to and from a custom manual wheelchair. This project is to design and fabricate modifications and add-ons that will make the AgileLife bed compatible with a Group 3 power wheelchair with seating functions.
Project Level: Basic
Preferred Major/Background: Mechanical Engineering, Bioengineering
Required Skills/Courses: Mechanical Design
CAD experience
Submitted by: Dr. Jonathan Duvall
Name of Project: Hybrid Powered Scooter
Description: Traditionally, power wheelchairs use heavy batteries which have limited ranges and need to be charged every day. This project will involve building and testing a hybrid powered scooter to quantify benefits and use cases.
Project Level: Intermediate
Preferred Major/Background: Electrical Engineering, Mechanical Engineering
Required Skills/Courses: Preferably some electrical courses
Submitted by: Dr. Jonathan Duvall
Name of Project: Identifying the IMPACT
Description: Our collaborative team from SCI, Katz and SHRS are proposing to develop the Translational Research and ENtrepreneurship Decision Support System, or TRENDS, which will use artificial intelligence (AI) to predict the likelihood of translational success for research and development projects. TRENDS has the potential to streamline and significantly improve the ability of organizations, such as Pitt, to identify promising technologies that may have a major social and/or economic impact. Organizations currently use committee-based approaches, such as grant review panels, which are time-consuming and are naturally biased based on the backgrounds of the reviewers. TRENDS will use an AI predictive engine which has been developed based on large datasets of translational research activities to predict the likelihood for success, and thus supplement these committee-based panels. As TRENDS is expanded and its accuracy validated across different technology domains, we envision that it will replace some functions of these grant review panels which are making funding decisions. We therefore predict TRENDS will become a valuable and possibility essential tool to aid in the project prioritization and resource allocation activities of University innovation centers and technology transfer offices, funding agencies and investors, as well as intermediaries that mentor and match inventors with funding and other resources. Using the Momentum funds, we will develop a proof of concept of TRENDS which will include a user Interface, a database, a knowledge management system, and an analytics and modeling tool. The core innovation in TRENDS is the analytics and modeling tool, which will serve as predictive modeling engine that is developed through machine learning approaches applied to Pitt’s Innovation Institute invention disclosure and licensing database. Funding opportunities exist at NSF and other federal agencies to support scale-up of TRENDS so that it can be leveraged by national funding organizations (e.g. NSF, NIH) and private sector companies.
Project Level: Basic
Preferred Major/Background: Information/Computer Science
Required Skills/Courses: A combo of or familiarity with any of the following: SQL, Python, data science, big data analysis, user interface design
Submitted by: Dr. Mary Goldberg
Name of Project: Development of the Caregiver Assisted Transfer Technique Instrument (CATT)
Description: When an individual cannot safely or effectively move from one surface to another, a caregiver may need to perform an assisted transfer to move the care recipient. However, performing assisted transfers can be detrimental to both the caregiver and user, especially if the caregiver is an informal or untrained caregiver who may not have been taught how to safely and effectively perform a transfer. Currently, there is no way to quantitative evaluate a caregiver’s transfer skills. A new instrument, called the Caregiver Assisted Transfer Technique Instrument (CATT) has been developed to provide an objective way to evaluate proper technique of caregivers who provide transfer assistance to individuals with spinal cord injury/dysfunction. This project will focus on performing human subjects testing to refine the CATT so that it can be used as a clinical tool.
Project Level: Intermediate
Preferred Major/Background: Biomedical engineering, rehabilitation science, health sciences
Required Skills/Courses: Microsoft Excel, experience with statistical software (SPSS, SAS, or other comparable statistical packages) is preferred, excellent communication skills
Submitted by: Hailee Kulich, Dr. Alicia Koontz
Name of Project: Fairy-Tail
Description: Most legged animals have tails. The functions of those can be multi-faceted, but often include dynamic stabilization during locomotion (flying, swimming, jumping, running/walking). Humans have evolved to not need tails, providing stability by effective use of their fore-limbs to counter most destabilizing moments that may be introduced by normal ambulation. However, some disabilities or illnesses result in decreased gait stability and increased fall risk, which is conventionally addressed by passive assistive devices, such as canes or walkers. The "Fairy-Tail" project pursues an approach that actively counters dynamic imbalances much like a tail would. The device will be refined and tested as part of this internship experience
Project Level: Intermediate
Preferred Major/Background: Bio-engineering, mechanical engineering, studio arts
Required Skills/Courses: Engineering design, additive manufacturing, human subjects research conduct
Submitted by: Alexandra Delazio, Dr. Goeran Fiedler
Name of Project: Development of TransKinect: A Clinically Robust System for Transfer Assessment
Description: The use of good transfer mechanics to avoid pain and injury is important for wheelchair users when performing transfers. The Transfer Assessment Instrument (TAI), is a tool developed to evaluate the transfer technique and help clinicians and users to recognize deficits in technique. An artificial intelligence system that can automatically score the TAI may potentially reduce the barriers associated with TAI’s usability. We aim to develop a system that can watch a patient transfer and allow for automating the TAI using marker-less motion capture technology and machine learning algorithms that classify the motions into proper and improper techniques. Therefore, the results of the current study could increase the usability and feasibility of TAI in a clinical setting.
Project Level: Intermediate
Preferred Major/Background: Biomechanical engineering, mechanical engineering, computer/information science, machine learning, data science.
Required Skills/Courses: Linear algebra; Basic knowledge in biomechanical engineering and statistics
Submitted by: Lin Wei, Dr. Alicia Koontz
Name of Project: AgileLife Patient Transfer System with Group 2 Power Wheelchair
Description: The AgileLife Patient Transfer system is a combined bed and wheelchair system that automatically transfers an individual to and from a manual wheelchair. Recently, a new system has been created that makes use of an electric powered wheelchair instead of a manual wheelchair. The goal of this project is to make design modifications to an existing prototype of the AgileLife electric powered wheelchair based on feedback from relevant stakeholders, including rehabilitation professionals, power wheelchair users, and family members of power wheelchair users.
Project Level: Basic
Preferred Major/Background: Bioengineering, Mechanical Engineering
Required Skills/Courses: Mechanical design experience preferred
Submitted by: Hailee Kulich, Dr. Rory Cooper
Name of Project: Wheelchair skills metric analysis
Description: The goal of this project is to identify objective variables associated to the driving skills level of power wheelchair users in order to provide an efficient wheelchair skills training
Project Level: Basic/Intermediate
Preferred Major/Background: BioEngineering, Computer and Science, or Health and Information Science
Required Skills/Courses: Programming skills (Matlab), Digital signal processing, and Basic understanding of accelerometers
Submitted by: Dr. Jorge Candiotti
Name of Project: MEBot Terrain Recognition
Description: MEBot is an existing robotic wheelchair that can climb curbs and self-level on any terrain built at the Human Engineering Research Laboratories. The purpose of this project is the ability to detect terrain in real time and to incorporate feedback instructions to MEBot to adjust the terrain accordingly.
Project Level: Advanced
Preferred Major/Background: Electrical Engineering, Computer Engineering
Required Skills/Courses:
Required: Electrical and Computing Engineering or similar, C++
Preferred: Worked with computer vision
Submitted by: Sivashankar Sivakanthan, Dr. Rory Cooper
Name of Project: WHEEL-LEARN: The Development of an Internet-Based Healthy Lifestyle Behavior Intervention for People with Physical, Cognitive, and Sensory Disabilities
Description: Physical and psychosocial barriers place people with disabilities at greater risk for chronic disease risk than those without disabilities. Lifestyle management is a key factor in behavior change for preventing chronic disease risk. Standard Behavioral Therapy is a proven method for tackling barriers to a healthy lifestyle. There are limited options for usable, accessible, and low-cost, evidence-based behavioral lifestyle programs for disability populations. A user centered design approach is proposed to (1) develop WHEEL-LEARN, an Internet-based behavioral lifestyle program and (2) test the usability and accessibility of WHEEL-LEARN program. It will be pilot tested in a diverse cohort of people with sensory, cognitive, and physical disabilities.
Project Level: Intermediate
Preferred Major/Background: Mechanical Engineering; familiarity with Adobe Connect
Required Skills/Courses: Excellent written and verbal skills; leadership skills
Submitted by: Dr. Theresa Crytzer
Name of Project: Origami-inspired Manual Wheelchair Design
Description: Most manual wheelchairs are designed using bent and welded tubing. Few composite wheelchairs on the market use plates and shells to take advantage of the properties of composites. Design of manual wheelchairs has evolved incrementally over the past decade. Origami-inspired design has started to gain traction in engineering applications such as aerospace. For example, origami-inspired designs create ultralight-weight and compact folding structures. In addition, the folded shapes can be optimized to be stiff where needed, and yet flexible in other portions of the structure. The goal of this project is to reduce the weight of manual wheelchairs while increasing their rolling and propulsion efficiency, and to lead the way for new design methods. Better manual wheelchairs will help provide wheelchairs that allow PwD to remain healthy and engaged longer, and delay or prevent the need to transition to a powered wheelchair.
Project Level: Intermediate
Preferred Major/Background: Mechanical Engineering; familiarity with Adobe Connect
Required Skills/Courses: Mechanical design experience preferred
Submitted by: Dr. Rory Cooper, Dr. Garrett Grindle
Support for this program is provided by the National Science Foundation, Grant EEC 1852322.
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