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Purdue ExoMIND Glove

The ExoMIND Glove is a stroke rehabilitation device used to to generate biofeedback for physical threrapists and patients.

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The ExoMind Glove is a wearable device equipped with 7 accelerometers that are used to quantify forearm, wrist, and finger angles. Additionally, an EMG with conductive fabric electrodes is secured into the sleeve of the device to monitor muscle activity. The glove houses an Ardiuno Pro Mini which runs an interactive program to prompt the user through motions in order to gauge range of motion and detect muscle activity which can be used by the physical therapist.

Check out our video for more information about the need and how we met it!
https://youtu.be/yvd7Qi0p_yI

Executive Summary

Problem: In the United States, there are 143,000 individuals who have lost the use of their dominate hand due to a stroke. Of these, approximately 93,000 will have not successfully recovered the use of their hand after 6 months of treatment. Experts suggest that this lack of recovery is due to a lack of data. This lack of data contributes to poor success rates because (1) reimbursements for care at these centers is dependent upon quantifiable results, (2) the optimal intensity of training cannot be determined without specific data to quantify the patient’s progress, and (3) patients lose motivation without concrete evidence that they are making progress.

Solution: In response, Purdue MIND created the ExoMIND Glove. This glove will meet the identified needs by (1) facilitating the creation of quantitative reports of therapeutic progress to allow for complete reimbursements, (2) allowing physical therapists the ability to identify and address specific deficiencies in the patient’s therapy, and (3) providing robotic rehabilitation solutions to patients struggling to regain use of their hands.

Differentiation: Due to the narrow focus of these devices on patient recovery, other stakeholders, specifically the acute care center’s needs, have not been adequately addressed. The ExoMIND Glove presents the first attempt in this market to provide acute care centers with holistic analytical reports to track the progression of the patient’s recovery during acute rehabilitation care.

Prototype of final design

Our solution utilizes seven velcro ring accelerometers and one fabric bipolar electrode EMG sensor unified within a single adjustable glove that slides over the user’s forearm and hand to allow ease of use. The glove is equipped with one EMG sensor sewn into the device with conductive silver fabric to comfortably measure electrical activity produced by skeletal forearm muscles. This EMG sensor is wired to a central housing unit (i.e. a breadboard) that is mounted on the top of the device. Five ring accelerometers housed in 3D printed units are mounted on each of the user’s finger tips to measure relative finger position. The remaining two accelerometers measure wrist motion by analyzing the position of one accelerometer on the back of the hand relative to an accelerometer in the central housing unit on the user's forearm. All accelerometers are wired to the central housing unit without impeding the user’s range of motion. Contained within the central housing unit is an Arduino Pro Mini which is paired with a software that implements an interactive program to walk the user through proper usage of the ExoMIND Glove.

Documentation of final design

Accelerometers

The circuitry of the accelerometers were designed and developed on custom printed circuit boards (PCBs) via Eagle software and sent to OSHPark to print for use. Due to these criteria, the MPU6050 was used for all accelerometers. The accelerometers detect changes in the angle of each fingertip with respect to a baseline position of a closed fist by using a reference accelerometer fastened to the backside of the patient’s hand. These values must be used to obtain a measure of the range of motion of each individual finger such that a physician or physical therapist may quantify and personalize the therapy over time by identifying which fingers or types of exercises need more direct attention. The user needs a simple and interactive program to walk the user through proper usage of the device to ensure accurate readings and clearly displayed results.

Custom MPU6050

Electromyograms

The analog front end (AFE) and bipolar electrodes of the EMGs were designed and developed on custom printed circuit boards (PCBs) via Altium software. The AFE and electrode design had to be small enough to be comfortably worn within a wrist brace encapsulating the forearm, and to filter frequencies outside the 70 Hz - 1590 Hz range while amplifying the differential signal by 1000x to meet design specifications. The dry...

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fritz.PNG

I used Fritzing to better show how we did the setup. Refer to the EMG schematics for more clarity on the EMG.

Portable Network Graphics (PNG) - 167.93 kB - 06/22/2017 at 04:08

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Portable Network Graphics (PNG) - 62.06 kB - 06/17/2017 at 18:38

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MIND reEdited MPU 6050 newer-1.STL

Custom MPU 6050 made to fit in out velcro holders.

Standard Tesselated Geometry - 926.06 kB - 06/15/2017 at 15:23

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Lid.stl

Lid to the MPU 6050 holder

Standard Tesselated Geometry - 47.35 kB - 06/15/2017 at 15:22

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Accelerometerhold.stl

Base of the MPU 6050 holder

Standard Tesselated Geometry - 6.82 kB - 06/15/2017 at 15:22

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View all 10 files

  • 7 × MPU 6050 Accelerometer
  • 1 × Ardiuno Pro Mini
  • 1 × EMG Designed and printed by Purdue MIND in Dr. Pedro Irazoqui’s lab (Center for Implantable Devices)
  • 1 × Velcro sleeve with mount We sewed this custom glove/sleeve together by hand. It even has conductive fabric in it for a better EMG reading.
  • 1 × Fabric Electrodes We made fabric electrodes using conductive fabric sewn into the glove.

View all 6 components

  • Thank you Altium!

    skuhns5 days ago 0 comments

    Altium just tweeted us out and posted our project on their facebook!

    It's pretty cool to get some exposure from a company like them! Thanks!

  • Live on Hackster

    skuhns06/16/2017 at 18:42 0 comments

    We just published for the first time on Hackster.io for Intel's Young Maker Competition!

    We will be looking for more opportunities through Hackster as well as potentially upgrading to using an Ardiuno 101 for bluetooth and and its built-in accelerometer and gyroscope.

    Check it out here: https://www.hackster.io/purdue-mind/purdue-exomind-glove-1b32dc

  • We're Featured!

    skuhns06/15/2017 at 19:21 0 comments

    We just saw that this project was featured on the home page!

    Being completely new to Hackaday up until now, this is very exciting. Big thanks to them for featuring us! This whole process has been a lot of fun, and I am excited to see where this will take us!

  • Competitions Update

    skuhns06/15/2017 at 15:35 0 comments

    A small back log about some competition things we have completed.

    We recently completed our application to the DEBUT Venturewell competition as well as the Purdue BMES competition where we will enter as an undergrad team!

    During the upcoming school year we will be looking at continuing the development of this project.

    Hopefully we will find some more potential competitions for us to compete in!

  • First Log!

    skuhns06/14/2017 at 15:20 0 comments

    First Log!

    The prototype is finally done and we are super excited with our first version.

    Check out the video we made to better show the need met by the ExoMIND Glove and a little bit about how it works!

View all 5 project logs

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