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Design and Evaluation of a MEMS Magnetic Field Sensor-Based Respiratory Monitoring and Training System for Radiotherapy.

Yoonjin OhYoung-Jin JungSang Hyoun ChoiDong Wook Kim
Published in: Sensors (Basel, Switzerland) (2018)
The patient's respiratory pattern and reproducibility are important factors affecting the accuracy of radiotherapy for lung cancer or liver cancer cases. Therefore, respiration training is required to induce respiration regularity before radiotherapy. However, the need for specialized personnel, space, and time-consuming training represent limitations. To solve these problems, we have developed a respiratory monitoring and training system based on a micro-electro-mechanical-system (MEMS) magnetic sensor. This system consists of a small attaching magnet, a sensor, and a breathing pattern output device. In this study, we evaluated the performance of the signal measurement in the developed system based on the various respiratory cycles, the amplitudes, and the position angles of the magnet and the sensor. The system can provide a more accurate breathing signal graph with lower measurement error and higher spatial resolution than conventional sensor methods by using additional magnet. In addition, it is possible the patient to monitor and train breathing himself by making it easy to carry and use without restriction of time and space.
Keyphrases
  • early stage
  • virtual reality
  • locally advanced
  • radiation therapy
  • radiation induced
  • case report
  • respiratory tract
  • mental health
  • palliative care
  • high speed
  • squamous cell carcinoma
  • high resolution
  • machine learning