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Personally customize your big white: Bioelectrical impedance tomography open source toolkit can 3D print muscle health monitoring equipment at low cost

  Bioelectrical impedance tomography is a new type of medical functional imaging technology. Its principle is to apply a weak current to the electrodes on the surface of the human body, measure the voltage values ​​on other electrodes, and reconstruct according to the relationship between voltage and current. The internal electrical impedance value of the human body or the change value of the electrical impedance is obtained.
  Since this method does not use nuclides or rays, it is harmless to the human body, so it can be repeatedly measured and used for many times, and the imaging speed is fast, and it has the characteristics of functional imaging. In addition, its cost is low and no special working environment is required. Tomography is an ideal non-invasive medical imaging technology with attractive application prospects, which quickly became a research hotspot at the end of the 20th century. At present, some commercial electrical impedance tomography equipment has been applied clinically.
  However, the hardware setup of electrical impedance tomography equipment is often bulky and expensive, and requires complex algorithms to decipher the data. Therefore, the current application of electrical impedance tomography equipment is limited to professional medical fields such as hospitals, which are used to monitor the internal structure of a certain part of the human body, such as lung function and cancer detection.

  In the past few decades, with the emergence and development of inexpensive electronics, 3D printing technology and open source bioelectrical impedance tomography image libraries, people in more fields can also easily apply electrical impedance tomography equipment to haptics Perception, gesture recognition, and in the health field are mostly used in sports medicine and home care. These scenarios show the market potential of low-cost development of electrical impedance tomography equipment.
  But for now, designing wearables remains a challenge: Since everyone has nuances in their muscles and bones, being able to personalize wearables to match individual muscles is a big challenge.
  Recently, the MIT Computer Science and Artificial Intelligence Laboratory released a new toolkit that allows users to independently design health-sensing devices that can detect muscle movement, lowering the threshold for designing and manufacturing wearable devices. The paper was finally published at ACM UIST 2021, the top international conference in the field of computer human-computer interaction.

  This toolkit (EIT-kit) is an electrical impedance tomography toolkit that supports users at different stages of EIT device development. The kit includes: (1) a 3D editor for custom monitoring imaging settings and electrode distribution settings; (2) a newly designed EIT sensing board that supports different measurement settings and provides adjustable AC Inject current to improve signal quality; (3) a microcontroller library that automatically calibrates the signal and facilitates data collection; (4) an image reconstruction library that supports mobile devices to visualize data on devices such as cell phones.

  The “EIT-kit” 3D editor allows users to enter EIT device parameters and export them to a 3D printer for assembly. Zhu Junyi, the principal investigator of the project and a PhD candidate at MIT CSAIL, said.
  Using electrical impedance tomography, a device made from the kit can measure internal conductivity to tell if muscles are activated or relaxed. While most wearable devices can only sense motion, bioelectrical impedance tomography devices can sense actual muscle activity. The team built a prototype that sensed muscle strain and tension in subjects’ thighs, allowing them to monitor muscle recovery after injury. In the article they also show other uses, such as gesture recognition, distracted driving detection, etc.

  Currently, the team is working with Harvard Medical School and Massachusetts General Hospital to use the devices to help patients rehabilitate.
  Zhu Junyi said that its scientific research goals and targets are to develop rapid functional prototyping technology and new sensing technologies and apply them to the field of personal health. “I believe that in the future, everyone will be able to personalize devices capable of health monitoring and interactive sensing according to their body size and needs.”

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