REU/ELeVATE Summer Projects 2018

Name of Project:  Using functional MRI to map cortical hand control

Description:  Our lab is currently working to use functional magnetic resonance imaging (fMRI) to identify the specific brain areas involved in dexterous hand movements. This project involves working with an existing environment of processing and analysis tools to learn about how our brains control our hands, and how these areas are affected by tetraplegia due to cervical spinal cord injuries (SCI).
The student will be responsible for analyzing fMRI data collected while able-bodied volunteers and participants with SCI either imagined or attempted to move their hands. The goal will be to determine whether the activity generated in motor and somatosensory areas during this task is affected by chronic SCI. The project will heavily involve the use of Matlab and Python-based shell scripts to process and analyze the data. 

Project Level:  Intermediate 

Preferred Major/Background:  Neuroscience/psychology/biomedical engineering

Required Skills/Courses:   Programming in Matlab; Experience with neuroimaging tools such as Freesurfer and AFNI/SUMA is recommended but not required. 

Submitted by:  Dylan Royston, Jennifer Collinger 

 


 

Name of Project:  Validation of a Biomechanical Exoskeleton Simulator System (BESS)

Description:  As technology advances, the use of powered exoskeletons to assist soldiers is becoming a possibility. However, a lack of understanding the potential injury mechanisms for human users limits their widespread use. The primary goal of this study is to evaluate a model called the Biomechanical Exoskeleton Simulator System. RE2 Inc. has developed a Biomechanical Exoskeleton Simulator System (BESS), which is used to model the interaction between a robotic exoskeleton and the human user. The system directly models the interaction between the operator and the exoskeleton, which will enable faster turnaround for design change, a better understanding of potential injuries, and faster deployment when exoskeletons are ultimately introduced for widespread use. The objective of the research study is to collect experimental data (e.g. forces, body motion, muscle activity, and metabolic data) while subjects walk on various surfaces with and without an exoskeleton. The data will be used as inputs to BESS to confirm that BESS accurately models human and exoskeleton interactions.

Project Level:  Advanced 

Preferred Major/Background: Engineering preferred, specifically biomedical, mechanical or computer science/engineering

Required Skills/Courses:  Proficiency in Matlab is required, as well as the ability to use Microsoft Word and Excel. A basic understanding of anatomy would also be useful. Excellent communication skills are required, as the intern would be working directly with human subjects. 

Submitted by:  Hailee Kulich, Dr. Koontz

 


 

Name of Project:  Visual feedback for gait retraining

Description:  The goal of this ongoing research is to help people with lower limb prostheses achieve better gait by providing customized visual feedback while they are walking. Our current prototype uses sensors in the prosthesis, as well as smart-glasses for the feedback. Part of the REU project objectives will be to optimize the design of both hardware and software of this prototype and to test the results with some actual lower limb prosthesis users. 

Project Level:  Intermediate

Preferred Major/Background:  Computer Science, Biomedical Engineering 

Required Skills/Courses:  C++, Java, App programming experience preferred, CITI training for human subjects research (may be obtained in first weeks of internship) 

Submitted by:  Krista Kutina; Goeran Fiedler 

 


 

Name of Project:  IOT-enabled Automatic Classification of Activities of Daily Living

Description:  To prototype an automatic classification of activities of daily living (ADL), using a variety of IoT sensors and devices. They gather data on environment,
and information on temperature, humidity, pressure etc. is obtained; they gather data on human body, and information on health, treatment or therapy outcomes is obtained; they gather data on objects, and information for monitoring and control of these objects is obtained; they gather data on subjects or objects functions, and information for better decisions, control and action is obtained. Based on the collected data and information, an algorithm to automatically classify a variety of ADLs with a smartphone/watch. 

Project Level:  Intermediate

Preferred Major/Background:  Computer Science, Health Sciences/Informatics, Information Science 

Required Skills/Courses:  software algorithms; OOP programming;
mobile software development skills (Android/IOS)

Submitted by:  Hyun Ka

 


 

Name of Project:  Development of Electro-Hydraulic Control Testing Platform for Mobility-Enhanced Robotic Wheelchairs

Description:  Mobility-Enhanced Robotic wheelchair (MEBot) is to improve the ability of terrain negotiation using actuated wheel control. This project is to build a platform for testing electro-hydraulic actuators and apply various control methods, that may be used to maintain stability and safety for the MEBot users. 

Project Level:  Advanced 

Preferred Major/Background:  Mechanical design and fabrication
Microcontroller related projects 

Required Skills/Courses:  Mechanical Design, Mechanisms, Robotics, Control Theories 

Submitted by:  Dr. Joshua Chung 

 


 

Name of Project:  Enhanced Gripper for the Assistive Robotic Arm for People with Disabilities

Description:  Assistive robotic arms are the robotic arms that improve the quality of life and increase independence for the people with disabilities. However, studies found that current commercial gripper designs showed relatively weaker prehensile strength. This project is to develop a viable way to evaluate the robotic arm performance with different gripper design.  

Project Level:  Intermediate 

Preferred Major/Background:  Physical Therapy, Occupational Therapy 

Required Skills/Courses:  N/A 

Submitted by:  Dr. Joshua Chung  

 


 

Name of Project:  Wheelchair Comparison Data Analysis and Journal Paper

Description:  This project will collect and analyze data from wheelchair testing comparison studies and incorporate that data into a paper that will be published in a peer-reviewed journal.

Project Level:  Intermediate 

Preferred Major/Background:   General Engineering background (Mechanical/Biomedical Engineering preferred) 

Required Skills/Courses:  Knowledge of statistical methods; experience with IBM SPSS statistical analysis software preferred; ability to conduct testing (with or without assistance) in a laboratory setting (this involves administering tests based on standards and/or collection of test results); competent technical writing skills 

Submitted by:  Ben Gebrosky 

 


 

Name of Project:  MeBot - Design

Description:  MeBot is an advanced prototype power wheelchair which has capabilities of climbing curbs and self-leveling. It uses information from a variety of sensors to determine how to autonomously perform different tasks.  Student will be redesigning parts for an advanced wheelchair prototype that uses electro-hydraulics to raise and lower each wheel independently. The system you design will be more reliable, more efficient, and lower cost than the current system. The design will include evaluating specifications of available, off-the-shelf, parts and/or design and fabrication of custom parts with the help of the HERL machine shop. 

Project Level:  Intermediate 

Preferred Major/Background:  Mechanical Engineering 

Required Skills/Courses:  Simulation (preferably using Matlab), SolidWorks, hands-on fabrication and assembly skills a plus. 

Submitted by:  Jon Duvall; Dr. Rory Cooper 

 


 

Name of Project:  MeBot - Software

Description:  MeBot is an advanced prototype power wheelchair which has capabilities of climbing curbs and self-leveling.  It uses information from a variety of sensors to determine how to autonomously perform different tasks. Student will be redesigning parts for an advanced wheelchair prototype that uses electro-hydraulics to raise and lower each wheel independently. The system you design will be more reliable, more efficient, and lower cost than the current system. The design will include evaluating specifications of available, off-the-shelf, parts and/or design and fabrication of custom parts with the help of the HERL machine shop.

Project Level:  Intermediate 

Preferred Major/Background:  Computer Science, Electrical/Computer Engineering 

Required Skills/Courses: Programming, especially C++, microprocessor control, work with real-time systems, understanding of sensors and actuators

Submitted by:  Jon Duvall; Dr. Rory Cooper 

 


 

Name of Project:  Elimination of microstimulation artifact in human intracortical microelectrode recordings

Description:  Our lab is testing a closed-loop intracortical brain-computer interface in a human subject, which involves recording from motor cortex while stimulating in somatosensory cortex. Microstimulation generates stimulation artifacts that are typically larger in magnitude than the extracellular spike potentials we record. We currently rely on a combination of signal blanking and filtering to ignore the artifacts and record data between stimulus pulses. However, we lose approximately 15-20% of our data by doing this. We also do not have a method to remove artifact from local field potentials (LFP, continuous brain signals) during microstimulation.
This project will involve iterating on our existing artifact rejection strategy by testing the effects of various filters and signal processing techniques on data recorded during microstimulation. The goal will be to reduce or eliminate the "blanking period" in which neural data is lost during and after each stimulus pulse. A secondary goal will be to recover the continuous LFP signal during stimulation. The student will have the opportunity to validate methods during closed-loop BCI experiments.

Project Level:  Intermediate 

Preferred Major/Background:  Bioengineering or Electrical Engineering with an interest in neural engineering 

Required Skills/Courses: Matlab (required); Signals and Systems; Digital Signal Processing or equivalent (highly recommended)

Submitted by:  Jeffrey Weiss; Dr. Jennifer Collinger 

 


 

Name of Project:  Assessment of daily activity patterns in wheelchair users

Description:  Wearable sensors are increasingly being used in human activity research. In this project, manual wheelchair users will be tested in the community for a week and their data will be analyzed using MATLAB. A wrist worn sensor and a sensor attached to the wheel of wheelchair will be used to find different variables related to daily activity patterns. Variables will be plotted and observed. Student will help with subject testing, analyze sensors data for each subject, coding in MATLAB to calculate different variables related to daily activity patterns, and plotting all variables to observe.

Project Level:  Intermediate

Preferred Major/Background:  Bioengineering, Biomedical Engineering

Required Skills/Courses:  Knowledge of MATLAB (coding), classification in MATLAB (preferred) 

Submitted by:  Akhila Veerubhotla; Dr. Dan Ding 

 


 

Name of Project:  Understanding population neural activity during an object interaction task using BCI

Description:  Brain computer interfaces can restore lost limb function using neural signals recorded from the primary motor cortex to control a prosthetic robotic arm. This population neural activity can be thought of as a representation of the user’s intent. However, how can task context change patterns of neural activity? We aim to find how interacting with an object in space can change or vary the co-modulation of neurons and whether these changes can affect our decoding of the user’s intent.

The student will be responsible for analyzing neural data recorded while a subject used a robotic arm to interact with objects. The goal will be to determine how both single unit and population level analyses of neural data are affected by changes in object features as well as presence. The project will heavily involve the use of Matlab to analyze the data. A knowledge of machine learning is recommended but not required.

Project Level:  Advanced 

Preferred Major/Background:  Biomedical Engineering; Neuroscience; Computer Science 

Required Skills/Courses:  Matlab, Intro to Neuroscience, Intro to Machine Learning 

Submitted by:  Angelica Herrera; Dr. Jennifer Collinger 

 


 

Name of Project:  Terrain detection and classification for advanced wheelchair navigation

Description:  Student will assist with furthering development of a system that uses light detection and ranging to identify obstacles and types of terrain that a wheelchair may encounter, and integrating that information into the wheelchair’s control system to improve the efficiency of its self-leveling an obstacle negotiating features.

Project Level:  Advanced 

Preferred Major/Background:  Bioengineering, Mechanical Engineering, Electrical Engineering

Required Skills/Courses:  Programming experience, preferably C/C++

Submitted by:  Andrea Sundaram; Dr. Rory Cooper


 

 

Name of Project:  Factors associated with transitions in mode wheeled mobility

Description:  Wheelchairs are the single most enabling device for individuals with spinal cord injury, but there are distinct pros and cons of manual and power wheelchairs. Manual wheelchairs are lighter-weight, more portable, and enable physical activity for the user. However, power wheelchairs allow for increased independence with decreased stress on the upper extremities and offer advanced electronics. The longitudinal factors associated with transitions between manual and power wheelchairs have not been evaluated. This project will evaluate the association between mode of wheeled mobility and patient characteristics, wheelchair breakdown and repairs, quality of life and participation, disparities in healthcare, and wheelchair skills. The results of this project will advance the knowledge of the characteristics of individuals who use and transition between manual and power wheelchairs.

Project Level:  Basic

Preferred Major/Background:  Interest in assistive technology

Required Skills/Courses:  Microsoft Office, effective communication skills, basic statistical knowledge and use of a statistical computation program preferred

Submitted by:  Stephanie Rigot; Dr. Michael Boninger

 


 

Name of Project:  Remote wheelchair skills training

Description:  There is a significant push in clinical settings to integrate evidence based practice into patient care. Unfortunately, recent data has shown that wheelchair-related skills are lacking among end-users. In a cohort of manual wheelchair users, over 70% have difficulty with curb negotiation, and approximately 40% have difficulty with wheelie skills. These deficiencies may be tied to a lack of clinician knowledge on the topic, as clinical curriculums often include limited exposure to wheelchairs. Additionally, a lack of time and resources to provide training in these areas has been identified as a barrier. Web-based training offers an opportunity to reach both clinicians and increase dissemination of best-practice techniques. This project will focus on developing a series of web resources based on video of in-person training sessions to complement existing materials (http://www.wheelchairskillsprogram.ca/eng/index.php). Once developed, there will be an opportunity to pilot the materials and complete data analysis to evaluate their effectiveness.

Project Level:  Basic

Preferred Major/Background:  Interest in clinical interventions

Required Skills/Courses:  Microsoft Office, effective communication skills

Submitted by:  Lynn Worobey

 


 

Name of Project:  Manual wheelchair Virtual Coach

Description:  You will be furthering the hardware and software development of a system to monitor manual wheelchair users’ seated position, propulsion activity patterns, and other characteristics to support health interventions. The hardware portion involves both mechanical and electronic design, and the software portion involves data acquisition with multiple sensors, machine learning, smartphone app development, and cloud storage/computing. During your internship, we will be actively conducting a study using the device with participants who are manual wheelchair users.

Project Level:  Advanced

Preferred Major/Background:  Bioengineering; Computer Science

Required Skills/Courses:  Instrumentation design, real-time data acquisition and analysis with machine learning techniques, smartphone app development

Submitted by:  Andrea Sundaram; Dr. Rory Cooper

 


 

Name of Project:  Development of a wheelchair training toolkit

Description:  The development of the wheelchair training toolkit involves the qualitative analysis of interviews and surveys completed by educational institutions that have PT, OT, and P&O programs to understand how wheelchair content is taught in academic programs and what resources they use. As the need for appropriate wheelchairs and services increases around the world, the integration of this information in to academic programs is crucial to increase the knowledge of the assessment of wheelchair service, and a wheelchair training toolkit may assist in increasing the number of people who are trained. Our interview and survey data will help to determine the necessary toolkit contents, for example: how to address barriers, facilitators, curricula, and specific information for resource settings.

Project Level:  Basic

Preferred Major/Background:  N/A

Required Skills/Courses:  While none are required, the following are preferred: statistics, qualitative data analysis, prior research experience, and paper writing

Submitted by:  Stephanie Vasquez Gabela; Dr. Mary Goldberg


 

 

Name of Project:  AgileLife Transfer Bed clinical trials

Description:  The goal of this project is to conduct field trials by implementing the AgileLife PTS into the homes of complex and bariatric patients to evaluate the efficacy of the device. The AgileLife Patient Transfer System (PTS) developed by and commercially available from Next Health LLC is an innovative new device that offers a “zero-lift” solution for patients who are unable to independently transfer to and from the bed. The AgileLife PTS consists of a fully powered hospital bed, a docking station, transfer system and a manual wheelchair. The system is designed to allow the patient to be simply, gently, and easily transferred with little manual intervention required. Eight subjects will be recruited for a field trial with the PTS. The bed component of the AgileLife PTS will be installed in their home and 3 weeks baseline daily transfer and bed activity (e.g. occupied/unoccupied bed time) will be collected via a data-logging system built into the bed. After collecting baseline data, the system will be enabled for 6 weeks to determine if there are improvements in transfer activity. After the study, subjects and up to 3 caregivers providing assistance to each subject will complete a series of surveys, which will enable researchers to determine subjects’ satisfaction with the system.

Project Level:  Intermediate

Preferred Major/Background:  Engineering preferred, specifically Biomedical, Mechanical; Computer Science/Engineering; other possible backgrounds include Biology, Rehabilitation Science, and Kinesiology

Required Skills/Courses:  Experience with Microsoft Excel and other Office packages; experience with statistical software preferred; excellent interpersonal and communication skills

Submitted by:  Hailee Kulich; Dr. Alicia Koontz

 


 

Name of Project:  Strong Arm

Description:  The project is about a wheelchair-mounted mobile robotic-assisted transfer device (RATD) called Strong Arm. The Strong Arm has four joint segments, powered by electric actuators. It is attached to a commercially available Permobil C500 electric power wheelchair (EPW) with a custom track system, which allows the device to be repositioned around the seat frame of the EPW. A commercially available transfer sling can be attached to the most distal segment of the Strong Arm. The Strong Arm is powered using the C500 batteries, which requires no extra power source. The Strong Arm has 5 powered degrees of freedom (DOF) which reduces the effort need to move the person. This study aims to compare the biomechanics, effectiveness, and ergonomics of the HERL-RATD to the Hoyer Presence, the “gold standard” of current transfer assist devices.

The overarching objective of this study is to engineer solutions to allow PSD who require assistance (human or mechanical) while transferring to be able to transfer in their own homes, in the homes of friends/family, and in the community at large (e.g., hotels, restaurants, shopping malls) in a safe, comfortable, efficient, and convenient manner. The major tasks that are required by the interns include assisting and working closely with the project's team in analyzing the data that were collected from the participants, helping in designing the new version of the Strong Arm.

Project Level:  Basic

Preferred Major/Background:  Bioengineering; Mechanical Engineering; Electrical Engineering; Software Engineering

Required Skills/Courses:  Student should have an engineering background; in addition, a background in designing software such as SolidWork, and data analysis software such as Matlab

Submitted by:  Saleh AlQahtani; Dr. Rory Cooper

 


 

Name of Project:  PneuMobility

Description:  Project PneuMobility is the invention of powered mobility devices using compressed air rather than batteries. The devices are capable of being recharged in minutes, are lighter weight, and are waterproof. Prototypes of a power wheelchair and Scooter version have been created and improvements are continually being made.

Project Level:  Intermediate

Preferred Major/Background:  Mechanical Engineering

Required Skills/Courses:  Experience with 3-D modeling; engineering mechanics and mechanical design; experience using tools (wrenches, files, hammers, etc.)

Submitted by:  Brandon Daveler; Dr. Rory Cooper

 


 

Name of Project:  PneuPAPAW

Description:  The PneuPAPAW project is the design and development of a power assist add-on for manual wheelchair users that is powered by compressed air. The purpose of the power assist add-on is to provide a small amount of assisted propulsion for manual wheelchair users with decreased upper extremity strength.

Project Level:  Intermediate

Preferred Major/Background:  Mechanical Engineering

Required Skills/Courses:  Experience with 3-D modeling; prototype manufacturing; prototype testing

Submitted by:  Brandon Daveler; Dr. Rory Cooper

 


 

Name of Project:  Development of wheelchair standards

Description:  There are some wheelchair standards that are under development at the International Society of Wheelchair Professionals (ISWP). Standards development include developing a validated test method to evaluate wheelchair parts or the whole wheelchair. With this project, the student will get hands-on experience with wheelchair testing and exposure to test development.

Project Level:  Intermediate

Preferred Major/Background:  Mechanical, Electrical, or Biomedical Engineering

Required Skills/Courses:  Go through wheelchair standards that are being developed by ISWP. Here are two references: Standards paper: http://ajod.org/index.php/ajod/article/view/288
Caster test paper: http://ajod.org/index.php/ajod/article/view/358

Submitted by:  Anand Mhatre; Dr. Jon Pearlman

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