Spasticity Diagnostics Tool
Spasticity Diagnostics Tool
2017-2018
Our team developed a fabric touch sensor glove to be used as a medical diagnostics tool for doctors and patients. It is designed to be used in the treatment and diagnostics of muscular dystrophy and other related muscle deficiency diseases and illnesses. It consists of a force sensor based on capacitive technology able to detect the force acting on the user's hand, the surface subjected to a load, and the pressure distribution over the entire hand equipped with the sensor. In addition to the sensors, the glove will be equipped with the necessary electronics and hardware to capture, store, analyze, and transmit data from the glove to a phone, tablet, or computer. The sensor consists of 24 independent sensing areas positioned on the palm and fingers of the user's hand. By using fabric based capacitive touch sensors, made from an organic, dielectric elastomer such as PDMS or Ecoflex foam, the product can seamlessly be integrated into the glove not interrupting the doctors analysis and diagnostics of the patients medical condition.
Skills/Tools used:
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3D design using Solidworks
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PCB design and schematic design using Altium Designer
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Entrepreneurship presentations
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System design
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Electronic Circuits: capacitance to digital converter (CDC), microchip microcontroller, LEDs, uart to USB
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Python GUI, data logging and graphing, threading
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High rate data collection
The above slideshow shows our presentation that we used to win the Zpower Bowl Undergraduate Competition to win $25,000.
The above slideshow shows the technical side of our product. This slideshow will show you parts of our GUI, PCB development, and schematic representation of the electronic circuits.
The above video shows our prototype in action, recording the pressure exerted on the sensors on the glove and recording and displaying these values live using a GUI. Additionally, the data is then exported to an excel spreadsheet for analysis and further recording.