# Chronic Obstructive Pulmonary Disease Warning in the Approximate Ward Environment
## 4 Monitoring Breathing and Its Analysis
### Monitoring Abnormal Breathing  
In the last two sections we explained the coughing pattern and normal breathing pattern for COPD patients. We used the C-Band sensing technique and compared the results with the wearable sensor data. We performed the experiment in the same way as we performed the normal breathing experiment; a person imitating a COPD patient was asked to breathe abnormally for a period of 60 s. Through this we collected the raw WCI from all 30 subcarriers with 600 WCI packets. This is shown in Figure 14.  
Figure 11: Normal breathing pattern after filtration.  
Figure 12: Raw WCI for normal breathing using C-Band.  
Figure 13: Filtered WCI for normal breathing using C-Band.  
Now the CFR for all 30 subcarriers are shown in Figure 15. This shows the raw CFR for all 30 subcarriers for the period of 60 s.  
After filtration we obtain the reliable signal for all 30 subcarriers, as shown in Figure 16.  
We also monitored the abnormal breathing with the HKH-11C breathing sensor, like in the previous section. Multiple people imitated the abnormal breathing, wore the respiratory sensor and inhaled and exhaled the air for a period of 60 s. Figure 17 shows the raw abnormal breathing pattern obtained from the digital respiratory sensor.  
Figure 16: Filtered CFR for abnormal breathing.  
Figure 14: Raw WCI for abnormal breathing.  
Figure 15: The CFR of all subcarriers for abnormal breathing.  
The filtered breathing pattern for abnormal breath is shown in Figure 18.  
The person in the above case imitated the abnormal breathing tracked by the digital respiratory sensor. The breathing sensor behaves as the primary indicator in the above-mentioned case without showing any periodicity. So according to the above Figures 17 and 18 we can see the non-periodicity in the amplitude for both raw and filtered data. This non-periodicity indicates the abnormal breathing pattern.  
We also analyzed the data using C-Band utilizing the subcarrier number 21. Figure 19 shows the raw WCI obtained from C-Band. The advantage of using the wireless channel information is that we can choose one or multiple frequency channels for particular applications. The applications can be human intrusion detection, human activity recognition, gait identification and breathing pattern. For each application, specific subcarrier(s) provide the desired information. After examining all 30 frequency channels received for monitoring the breathing pattern of a COPD patient, the subcarriers #7, 19 and 21 gave us the coughing and breathing waveforms. The remaining frequency carriers did not deliver adequate information when the method was implemented in different geometrical locations/experimental settings. We have tested the system in six different locations and at five places the subcarriers #7, 19 and 21 gave us the desired results.  
We performed the filtration on the raw WCI obtained from C-Band. After careful examination we concluded that both the waveforms obtained from C-Band and respiratory sensor are almost identical with maximum power level of 18 dB (relative power). In our case we have mentioned the relative power expressed in dB as, \(H=Y-X\), where \(X\) is the transmitted signal and \(Y\) is the received signal. The filtered WCI for abnormal breathing is shown in Figure 20.  
Figure 19: Raw WCI for abnormal breathing using C-Band.  
Figure 17: Abnormal breathing pattern from digital respiratory sensor.  
Figure 18: Abnormal breathing pattern after filtration.