Plethysmographic Sensor Design for Real-time and Remote Body Hemodynamic Monitoring – A New Approach for Early Shock Detection

The recent studies show that in order to detect the early signs of developing a clinical shock, many hemodynamics parameters should be continuously monitored especially in the intensive care units and the operation rooms. These parameters are: the heartbeat rate, respiration rate, blood oxygen saturation, blood flow velocity and the blood pressure.

In this thesis, a noninvasive, cheap, compact and easy to use sensor for a real-time monitoring is designed, programmed and tested to monitor these body hemodynamics parameters and predict the chances of developing a clinical shock.

The sensor is based on the photoplethysmography principle where the diffuse reflectance signal from the area under interest of the body is detected. Briefly, the sensor consists of a photodiode which collects the diffused reflected light from the tissue that shinned by using two wavelengths, 660 nm and 940 nm, emitted by two LEDs. The LEDs are operating alternatively and driven by a TTL signal. The output current of the photodiode is amplified and converted into a voltage by using a trans-impedance amplifier.

For a purpose of reducing the generated noise by the electrical components, ideal filters are applied by coupling the output signal of the amplifier to a computer by using Data Translation DT9816 module. The acquired signals by the computer are post-processed by using a LabView®2012 code to present, calculate and estimate the desired body hemodynamics parameters.

The PPG waveform and the respiration rate are presented after filtering out the noise. Additionally, the heartbeat rate is calculated by using two different approaches, the FFT approach and by counting the pulses and calculating the intervals between them. The SpO2 value is also calculated by using two approaches of estimating the ratio of variations in the acquired signals from the two wavelengths. Besides that, the PTT is estimated and the pulse period is calculated in order to estimate the blood flow velocity and the blood pressure.


The heartbeat rate, SpO2 and the blood pressure results of the designed sensor were tested by comparing them with results of instruments, as reference, which are normally used in hospitals in order to verify the quantification and the reproducibility of the sensor results. This investigation has been done by applying the sensor and the reference instruments on 21 different healthy subjects. The output results of this investigation show that the sensor results of measuring the heartbeat rate and the SpO2 were very close to the results obtained from the reference instrument with a very low and close standard deviation values to what the reference instrument has. Additionally, the blood pressure values were also very close to the reference values with an advantage of monitoring the blood pressure in a real-time without disturbing the subjects and with an acceptable standard deviation values according to the AAMI.

The heartbeat rate, SpO2 level and the blood pressure parameters are used in order to predict the clinical shock. This has been done by calculating predicted values, out of the previous values, with a range of tolerance and compares it with the new measured value. When the heartbeat rate is rising and the SpO2 level and the blood pressure are falling, a chance of developing a clinical shock is expected.

The results of this work have shown promising results for noninvasive and real-time monitoring of the body hemodynamic parameters that are used in the detection of early signs of the clinical shock development. It was shown that the hardware unit and software algorithm were successfully designed. The PPG waveform can be presented by using this sensor and extract many of the body hemodynamic parameters such as respiration rate, heartbeat rate, blood oxygen saturation, blood flow velocity and blood pressure out of it.


Additionally, it was shown that the output results of the sensor were very close to the reference values. The maximum absolute difference (MAD) between the mean values of the sensor and the values from the reference instrument was 2.6 Beat/min while the maximum absolute difference of the standard deviation of the heartbeat rate values was 2.6029 Beat/min. Regarding the SpO2 measurements, the MAD of the mean values from the sensor and the reference was 3.711 % with a 2.3766 % for the standard deviation error. Finally, the MAD of the mean values was 4.1 mmHg with a 6.8505 mmHg for the standard deviation error.



In order to improve the results and reduce the standard deviation values, the motion artefacts should be reduced. The sensor should be fixed to the body in a way that reduces the motion artefacts but also without disturbing the subject. Many shapes of the sensor probe can be used, according to the studied area of the body, where the clip shape, which is normally used in the pulse oximeter, can be used to attach the sensor to one of the fingers or by using a rubber band for the arms and legs areas. More compact design of the current probe can be made to attach the sensor to the rest of the body areas since the effect of the motion artefacts is low in these areas. Additionally, the prediction of the clinical shock development can be improved by applying it in the Labview code in order to predict in online mode and optimize the used approach of defining prediction tolerance.