Implementation of Gyro Accelerometer Sensor for Measuring Respiration Based on Inhale and Exhale with Delphi Interface

Accelerometer sensor is widely employed in respiration studies for its ability to detect changes in position and speed. However, there is a lack of research focusing on the optimal placement of this sensor to achieve accurate respiration measurements. This study aims to investigate and analyze the ideal positioning of the gyro accelerometer sensor for precise respiration detection. To achieve this, a design is proposed that utilizes an Arduino Nano as a microcontroller to process signals and derive respiration values from three gyro accelerometer sensors. The obtained respiration signals and values are transmitted to a PC via Bluetooth and visualized through a Delphi application, enabling a comprehensive comparison of the signals from the three sensors. The main contribution of this research lies in studying the impact of gyro accelerometer sensor placement on respiration detection, ultimately identifying the most suitable sensor location. The analysis reveals that the overall error values obtained from the module are promising, with the highest error recorded at 2.06% when the sensor is positioned at the stomach and chest (sensor position 3). This result validates the feasibility of using gyro accelerometer sensors for respiration detection and provides valuable insights for future studies in this domain. However, it is important to acknowledge certain limitations in this research. During respondent movement or walking, noise is observed in the signal, which may affect the accuracy of respiration measurements. These limitations highlight the need for further investigation into refining the sensor placement and signal processing techniques to mitigate noise and enhance overall accuracy. In conclusion, this study emphasizes the significance of gyro accelerometer sensors in respiration detection and addresses the dearth of research regarding their optimal placement. By presenting the error analysis of three sensor positions, the study establishes a foundation for more precise and reliable respiration measurement techniques. Future efforts should concentrate on overcoming the limitations identified in this research, thereby advancing the potential of gyro accelerometer sensors for a wide range of respiration applications, such as monitoring respiratory health and sleep patterns