MIT has unveiled a new toolkit that allows users to design health-monitoring devices that can detect how muscles move. The University’s Laboratory of Science and Artificial Intelligence (CSAIL) made the kit using ‘electric impedance tomography’ (EIT), which measures internal conductivity to determine whether muscles are activated or relaxed. The research could enable portable devices that manage distractions, hand gestures or muscle movements for physical rehabilitation.
In a paper, the researchers wrote that EIT detection usually requires expensive hardware setups and complex algorithms to decrypt the data. The advent of 3D printing, low-cost electronics, and open source EIT image libraries has made this possible for more users, but designing a portable configuration is still a challenge.
With the 3D editor “EIT Kit”, users can enter the device parameters and place the sensors on a device that can go on a user’s wrist or leg, for example. It can then be exported to a 3D printer and compiled, and the last step is to calibrate the device with a subject. For this, it is connected to the motherboard of the EIT kit, and ‘a built-in microcontroller library automates the electrical impedance measurement and lets you see the visually measured data, even on a mobile phone’, according to CSAIL.
Where most carriers can only sense movement, and the EIT device can sense actual muscle activity. The team built a prototype that can feel muscle tension and tension in the thigh of a subject so that they can monitor muscle recovery after an injury. It also showed other possible uses, such as gesture recognition, a derivative driving detector and more.
The team is working with Massachusetts General Hospital on rehabilitation technology by using the devices while refining the technology. The ultimate goal is to develop ‘prototyping techniques for fast functions and new sensing technologies,’ “said lead author Junyi Zhu.
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