Our Key Services

  • Develop the proprietary optical biosensor utilizing MAPIS technology and AI-powered neural network deep learning algorithm, under the guidance of industry professionals and professors from the University of Toronto

 

  • Advance the biosensor’s applications in wearable devices and focus on non-invasive blood glucose monitoring.

 

 
 
 
 

MAPIS technology for subcutaneous tomography

 

  • Light (560nm, 960nm and 1400nm) is emitted from the periphery of the sensor into the subcutaneous tissue and scattered in the skin or subcutaneous tissue.
  • Part of the scattered light will pass through the imaging pinhole array and project onto the image sensor for imaging.
  • Any object point under the skin will have an image point in multiple pinhole image spots, after algorithm stitching and enhancement processing, a complete target image is obtained.
 
 
 
 

MAPIS technology in wearable devices

  • Different from the point measurement method in PPG technology, the MAPIS technology can obtain subcutaneous three-dimensional images or two-dimensional images at different depths.
  • The typical image size can reach more than 200*200 pixels, which is equivalent to measuring 40,000 points at the same time. Therefore, we can use more advanced algorithms, such as differential or gradient calculation, or introduce deep learning algorithms to eliminate the interference of many environmental factors (temperature, humidity, skin color, etc.) and obtain more accurate and stable measurement results (heart rate, blood oxygen and blood glucose, etc) than PPG technology.
  • The chipset module size is 15mm*15mm*0.3mm, which can be integrated in wearable devices in US$20.



  

   


 
 
 
 
 

MAPIS technology for non-invasive blood glucose monitoring

  • MAPIS technology achieves tomography in an extremely low-cost and portable method, and combines the processing of blood glucose absorption peak signals at NIR wavelengths (1400nm) to achieve non-invasive blood glucose monitoring;