Biomedical Engineering – From Theory to Applications

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Biomedical Engineering – From Theory to Applications
The digital hardware works as follows. Once data from analog hardware circuitry has been
amplified, filter, and shifted, the signal is sent to the ADC on the microcontroller. After the
signal has been sampled, the microcontroller then sends the digital signal to the Bluetooth
module via UART communication protocol. Then, the biomedical signal is transmitted
wirelessly through wireless Bluetooth module, utilizing the master-slave configuration.
4. ECG signal processing: A practical approach
As an example of biomedical signal processing in a transceiver device, in this section, ECG
signal analysis for real-time heart monitoring will be discussed. Following the discussion on
previous sections, this section particularly describes where real-time ECG monitoring using
hand-held devices, such as, smart phones or custom-designed health monitoring system.
ECG analysis is one of the very first areas of physiological measurement where computer
processing was introduced successfully. ECG has been widely used as the diagnostic
measurement for heart monitoring. Typically cardiologists used to interpret the ECG tracing
for identifying abnormalities related to function of heart. With the advancement in
biomedical signal processing, it is now reality that smart monitoring system can mimic the
rules cardiologists applies in order to monitor heart health in real time. Signal Processing
and machine learning techniques plays an important role in this purpose. Hence, this type of
smart devices would be useful in monitoring patient’s health in a more efficient way
(Laguna et al., 2005).
In the previous sections, we have described a low-cost real-time biomedical signal
transceiver/monitoring system which could also use ECG as one of the physiological
parameter to monitor health.
In the following sub-sections, we will discuss the underlying ECG signal processing
techniques used for identifying heart abnormalities. Typical steps are preprocessing of ECG,
wave amplitude and duration detection, heart rate calculation, ECG feature extraction
algorithms, and finally identifying the abnormalities. A typical block diagram is illustrated
in following Figure 9 (Neuman, 2010).
ECG
Sensors
Wireless
Transmitter
ADC
Wireless
Receiver
ECG Feature
Extraction
Abnormality
Detection
Display/Alarm
ECG
Filtering
QRS
Detector
Heart Rate
Calculation
Fig. 9. Block diagram of biomedical signal transceiver for real-time acquisition, processing
and heart condition monitoring system. The right portion of the system can be implemented
in smart phone or PDA for smart health monitoring.