| 英文摘要 |
Purpose: According to the research, the population of chronic diseases is increasing year by year. Therefore, the demand for measuring vital signs using sphygmomanometers, blood glucose meters and lipid profile machines is also increasing. However, the traditional manual recording method may cause transcription errors and most of the devices on the market that have storage or transmission functions are too expensive. In addition, these medical devices use seven-segment display digits to display the measurement results. The seven-segment display digit contains the discontinuous field and quite different from the printed numbers that may easily cause poor Optical Character Recognition (OCR). Thus, we develop a system which can automatically segment and identify seven-segment display digits.
Methods: In this paper, we propose using GAN to label the discontinuous fields of seven-segment display digits area and using the GAN-based SSD (Seven Segment Digits) Segmentation algorithm to automatically adjust the direction of the images. Then, use a famous OCR tool to recognize the digit value in the image of seven-segment display digits and automatically record the value to complete the monitoring of the systolic blood pressure, diastolic blood pressure and pulse.
Results: The experiment result shows that the relevant performance indicators for evaluating trained/ tested model are used. Finally, the accuracy of the test stage is 94.5%, the precision is 98.4%, the sensitivity is 90.9%, and the specificity is 98.4%. The recognition accuracy rate is 99%.
Conclusion: As discussed above, the method proposed in this paper can effectively improve the success rate of the seven-segment display digits recognition. Further, improving and reducing the steps of image pre-processing to reduce the time spent on overall recognition. |
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