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Enabling easier mirroring setup for SoftGlove

Updated: Mar 17, 2023

I am Davide Bacilieri and I am a 1st year student at the Physics of Data master program at UniPD (University of Padova, IT).

I am currently collaborating with Francesco Bondesani, a 2nd year medical student at Humanitas University (IT), on a project called SoftGlove, with the purpose of using FlowIO and soft robotic actuators for medical rehabilitation of the hand.

The full description of the physical and medical aspects of the project can be found in his blog post on this site: https://www.softrobotics.io/post/flowio-powering-a-softrobotic-glove-for-rehabilitation.


My objective is to build a software platform that allows for an easier use of the device in response to inputs from sensing systems of various kinds, as for example another glove with positioning sensors or a motion-capture device, thus making the device both easier to use and more effective.

The basic idea is to create a calibration and control routine that, regardless of which kind of system is used to gather data, flexes each finger of the gloved hand the same amount as the corresponding finger on the other hand. The platform itself has not been chosen yet, but we are considering either using directly a small wearable device, such as an Arduino or a Raspberry, or creating a computer program to read data from the sensing system and relay the appropriate commands via bluetooth.

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Development update:

We chose to use as a starting point a leap motion sensor connected to a PC, since both the sensor and the flowIO have a JavaScript API available.


The first idea was to use the sensor to read the position of the fingers on both hands and inflate or deflate the glove to match finger positioning on the two hands; however, unfortunately the sensor has trouble reading the position of the hand with the glove on. We hypothesized trying reflective patches like those used in CGI motion capture, but currently we are working with the position of the free hand on one side and the pressure in each finger's actuator on the other.

Because of this, we'll need…


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