Kaohsiung Medical University / Prof. Kuang-I Cheng

 Pain Points Solved 

• Conventional continuous arterial pressure monitoring requires arterial catheterization, which is invasive and carries a risk of infection.
  
• Existing blood pressure waveform prediction techniques are often limited by prediction latency and insufficient accuracy, making them unsuitable for real-time clinical applications.
• Clinical physiological monitoring devices are complex to operate, increasing the workload of medical staff as well as personnel and consumable costs.

 Technology Introduction 

This invention utilizes a composite model based on a temporal convolutional neural network (TCN) to compute and generate continuous arterial pressure waveforms within a 1-second future window using electrocardiogram (ECG) waveforms, blood oxygen saturation (SpO₂) waveforms, and physiological data. The system’s predictions comply with the standards set by the British Hypertension Society (BHS) and the Association for the Advancement of Medical Instrumentation (AAMI). It can be applied for real-time monitoring of continuous arterial blood pressure during surgeries or in critical care settings. The system offers advantages such as non-invasiveness, reduced risk of blood infections, decreased medical personnel and consumables, and improved patient comfort during treatment.

 Application Examples 

• Applied in surgical procedures or critical care settings to estimate continuous arterial blood pressure waveforms within a 1-second future window using real-time ECG and SpO₂ signals.
  
• The system can be integrated into existing physiological monitoring systems to provide continuous and non-invasive arterial blood pressure information.
• The system supports clinical decision-making and patient safety monitoring, improving treatment efficiency and enhancing patient comfort.

 Related Links 

None

 Patent Name and Number 

TW I845056

 Industry-Academia / Tech Transfer Partner 

None

 Honors and Awards  

None

 Technical Contact  

Mr. Hung, Assistant Manager

Kaohsiung Medical University 
Tel: +886 7-3121101 ext. 2360
Email: R121084@kmu.edu.tw