Solution to Medical Monitors Unmanned Functional Test

Solution brief

Many companies carry out product functional testing (FVT), it is difficult to do automation, and even difficult to break through the status quo of the island of test 

stations, it is difficult to achieve continuous flow. Manual testing has many drawbacks: such as inefficiency, omission of wrong test occurs from time to time, the risk

of personnel turnover and human resources costs rise.


Dihuge "unmanned functional testing solution for product functions based on AI vision", based on deep migration learning + automation technology, realises 

unmanned/automated functional testing of products with screens, completely replaces manual testing, and improves testing efficiency, accuracy and stability. 

In addition, the system is equipped to work continuously in hazardous environments without breaks, stops, or interruptions, surpassing human capabilities.


Representative case: Medical monitoring instrument product function testing, such as screen quality inspection, screen display product function flow testing, 

audio testing, air pressure testing, and so on.



Solution function

Unmanned functional testing of products integrates the processes of process testing, voiceprint recognition, and appearance testing, replacing human hands with mechanical arms and human brains with AI-based intelligent modules to achieve unmanned functional testing according to the set process, recording the test results of each link, and performing statistical analysis.

Bright spot

Introducing deep learning technology and image processing technology into the industrial process to improve detection efficiency, save manpower, improve the data collection process, and complete the statistical analysis based on the data to feed the control of the processing process.
  • Highly intelligent and automated: integration of AI vision technology, AI voice technology, automated testing technology
  • High accuracy: Deep learning neural network-based algorithms with high accuracy for display physical characteristics, OCR recognition, waveform detection, and key symbol positioning.
  • Highly adaptable: Deep learning neural network-based algorithms are highly adaptable to difficult detection of complex backgrounds and waveforms.

Application scenario

Product case

Medical monitoring instruments of many kinds, wide range of applications, the working principle is generally through the sensor sensing a variety of physiological changes, after the signal amplification and converted into data, data analysis software for processing, and finally in the display of the functional modules to show, as well as the corresponding alarms. The more and stronger the functions of the monitoring instrument, the more and more testing content is required for the factory quality control link, the higher the requirements, such as screen quality control, screen display of the equipment function flow testing, audio testing, airway pressure testing, etc.. Dihuge's "AI vision-based unmanned testing solution for product functions", based on deep migration learning + automation technology, achieves unmanned/automated functional testing of products with screens, completely replaces manual testing, and improves testing efficiency, accuracy, and stability.
  • Scene diagram of unmanned testing site for medical monitors

  • Scene diagram of unmanned testing site for medical monitors

  • Scene diagram of unmanned testing site for medical monitors