THE REAL-TIME VIZUALIZATION OF PNEUMOGRAM SIGNALS

Summary

The real-time visualization of pneumogram signals is described in this contribution. The device created provides simultaneous measurement of pneumogram and voice. The sampled signals are transmitted to PC software in real time via USB bus, which makes it possible to show the curves from the sampled signals in real-time. In addition, data archiving and printing functions are integrated into the software. Since pneumography is one of the oldest methods to provide information about the technique of respiration, it will be possible for doctors in phoniatric practice to use the created device and programmed application for patient diagnosis. Listed in the results is an example of the recordings acquired from the designed device.

Keywords:
pneumography, pneumogram, phoniatry, diagnostics, real-time signal processing, visualization

Introduction

The central focus of this article is the pneumogram acquisition method. Pneumography is one of the oldest methods to provide information about respiration during speaking and singing. A pneumogram consists of the person's voice, the movements of the chest and the movements of the abdominal wall. Pneumography curves are used to measure the respiratory rate, to detect pathological phenomena and to calculate the ratio between the time of inspiration and expiration. Further, the asymmetry and relationship between the curves of the chest movements and abdominal wall are evaluated with this method.

Currently, the pneumography method is not very widespread and is not used in medical practice, having been replaced by pneumotachography (there is no equipment manufacturer in the present market). However, the pneumography method is more suitable for diagnostic purposes, because it provides direct information about the muscle movements participating in the respiration process. Pneumography is also used in cases when a voice teacher needs to gain information about the pupil's breathing technique.

In this article, we have presented a design for a device that is used to capture the pneumography signals. This paper also focuses on description of a PC application that visualizes and records signals in real time. Real-time visualization is necessary, because the measuring sensors have to be correctly set up before the measuring process. Visualization allows for control of the correctness of the record. Listed in the results are the recordings acquired via the designed solution. The design of the device construction is based on descriptions which are specified in references [1].

The hardware description of the designed device

The block diagram in Fig. 1 provides an outline of the hardware solution. A 32-bit microprocessor from ATMEL AT91SAM7S64 [7], which has a maximum clock frequency of 55 MHz, was used for the implementation. The selected type of microprocessor contains all the required peripherals and is easily accessible on the market. The inputs of the device are connected to a pair of strain gauges and a microphone. The signals from the strain gauges are amplified by instrumentation amplifiers [3]. All signals are adjusted to the desired voltage range of the input A/D converter. An electrets microphone, which is commonly used in computer technology, is used to record the voice.

The sampling frequency is set at 500 Hz and the A/D converter has 10-bit resolution; since the voice recording is used only to detect the voice's presence, this sampling frequency is therefore sufficient. Connection to a PC interface is provided by USB. As this device operates in the USB HID class, such as a keyboard or mouse, no installation of additional drivers is required. The firmware of the microprocessor was created in the programming language C.

The construction of the sensor used for measuring is presented in Fig. 2. The SS5LB BIOPAC [5] sensors used to measure the tension of the strap, inside of which are piezoresistive strain gauges. Similar types of measurement sensors are used, for example, in polysomnography. In an appropriate construction, the sensor should not restrict the test subject, because doing so would affect the measured signal. The sensor sensitivity must be sufficient to register observed pathological phenomena such as hard voice beginnings. 

The final device design is shown in Fig. 3. The device has two inputs for the tension sensors connection and one input for the microphone connection. Potentiometers are used to set the signal offset of the strain gauges. The control LEDs are used for signaling 'power on' and 'recording '.

The PC application for signal visualization

The block diagram in Fig. 4 provides a description of the functionally designed PC application used for visualization, archiving and further processing of acquired data. First, the data received via USB are converted back from the data transmission format. Nonlinearity was found by measuring the transfer characteristics of the sensor, and the correction table which was calculated from the measured transfer characteristics, was implemented to compensate for nonlinearity. The next block in the diagram serves to compensate the speed streams of the measured and visualized data by selecting and storing data from the queue (FIFO). Implemented in the application is a digital filtering real-time algorithm. The IIR high-pass filter is implemented to remove base line wander, and the FIR low-pass 200th order moving average filter is implemented to eliminate the interference. The following block in the diagram is used to set the display scale. The change of the scale in the time axis is provided by signal decimation. Visualization is performed by rendering each pixel in the graphic userinterface component PictureBox [6], a simple solution that is nonetheless suitable for this application. The application is programmed in the programming language CSharp and is inspired by the design described in reference [4].

The flowchart displayed in Fig. 5 describes the section of the algorithm which ensures the visualization and archiving of data. The greatest problem is to display visualization of the continuous signal curves without having to depend on the performance of the PC. The signal drawing is performed by invoking the timer events. After invoking the event, the conditions of a sufficient number of samples in the queue are evaluated. If the condition is true, the visualization continues. The rendering of more samples at the same time is used to ensure sufficient dynamism of the process. The number of samples plotted in the same time depends on the decimation factor, which can set how the decimated data should be handled when the decimation is applied. It is possible to select only one sample and discard the other or select a sample with maximum value or calculate the average of all decimated samples. Also described in the diagram is the method of storage for archiving and printing.

Shown in Fig. 6 is the design of the graphic user interface. The application includes buttons which provide controlling the recording and inserting information tags on activity during the measurement. The application also allows the user to set options of archiving, printing, using the correction tables, filtration and background color.

Results of the measurements

Fig. 7 shows the results of the measurement acquired by means of the designed and realized solutions.

The recordings contains the signal of the voice, chest and abdominal activity, along with the tags providing information on activity during the measurement and tags in time interval 1s. During the recording, it is important to record the correct location of the sensor and the setting of the strap tension.

Conclusion

This article provides a basic description and guide to the use of pneumography. In addition, the article provides a description of a hardware and software solution designed to measure the pneumogram. The created device will be used for diagnosing voice disorders in phoniatrics clinics. Though the device has been tested in cooperation with phoniatric specialists, it has yet to be used in clinical practice.

Suggestions on how to improve the device will be known after more experiences with its use will be attempted, along with implementation of the device in actual clinical practice. Other improvements will include the creation of a database of patient records for better handling of the acquired data.

Ing. Jan Sedlák

Department of Circuit Theory

Faculty of Electrical Engineering

Czech Technical University in Prague

Technicka 2, 166 27, Prague, Czech Republic

E-mail: sedlaj15@fel.cvut.cz

Phone: +420 728 760 701