# Unobtrusive Vital Sign Monitoring in Automotive Environments--A Review
## 9 Sensor Fusion  
As described in Section 8, the measurement of physiological signals in a car can be a difficult challenge due to motion artifacts not only induced by the vehicle but also the driver himself. This is even more pronounced, when using unobtrusive sensor techniques. By applying sensor fusion, some parts of this challenge might be mitigated. The term sensor fusion here stands for the use of multiple sensors at different locations or the use of different sensor modalities at the same time or a combination of both.  
Applying sensor fusion would allow  
* artifact compensation, e.g., by utilizing adaptive filtering with one sensor serving as the noise signal.
* source separation, for example by applying algorithms based on statistical dependencies between the signals (like independent component analysis).
* coverage rate enhancement, e.g., by utilizing multiple sensors measuring the same vital sign and, therefore, increasing the probability that this vital sign is obtainable at a point in time.  
As mentioned before, in 2015, [PERSON] and colleages from RWTH Aachen University have demonstrated that fusing unobtrusive measurements indeed improves coverage and robustness of vital sign estimation ([PERSON] et al., 2015). In their experimental setup, the authors actually fused camera-based (web cam for BCG and PPG) information and one-dimensional signal information (BCG in a seat).  
Two years later, these authors further demonstrated ([PERSON] et al., 2015) that the fusion of multiple signals (PPG, BCG, cECG, MI) can further improve vital sign estimation of seated subjects, in particular when motion artifacts are present.  
Since the assessment and evaluation of several driver states like stress level, sleepiness or emotions require a variety of different physiological indicators, sensor fusion seems mandatory for driver state estimation. Several studies about driver state estimation have been conducted, using measurement setups with conventional, i.e., obtrusive, mainly electrode-based, sensors ([PERSON] et al., 2016).  
Already in 2009, [PERSON] et al. from Seoul National University and some other research organisations in Korea proposed to combine several unobtrusive sensing modalities in the car ([PERSON] et al., 2016). In particular,the authors presented a demonstrator (a test vehicle called the _U-car_) in which they simultaneously measured cECG in the backrest of the seat, ECG, PPG and galvanic skin response (GSR) in the steering wheel and respiration using a piezoelectric sensor in the seat belt. Their concept is shown in Figure 16.  
In a small study involving \(n=4\) young healthy volunteers, driver stress levels were assessed during night driving, cold environment, hot environment, noisy environment, narrow alleys and with simultaneous mental loads (arithmetic operations). For quantification, both heart rate variability (HRV) indices as well as pulse arrival time (PAT) were measured.  
A similar system was presented by [PERSON] et al. in 2010 [30] and 2012 [31]. The system comprises two electrodes for ECG measurement, two GSR electrodes and two newly designed IDAT microsensors. All devices are built into the steering wheel. The IDAT sensors integrate an inter-digital array (IDA) [190] and a temperature sensor (T) into one small device and can be used for the measurement of skin temperature, GSR and heart pulse. The system also includes a pressure sensor integrated into the seat measuring respiration, heart pulse and driver weight. In addition, a camera-based emotion recognition system was integrated, but no results were presented. While this system incorporates several sensors for the same modality, sensor fusion still needs to be demonstrated.