## 4 Experiment Results
### On-the-Road Testing of HR and RR
Figure 11 shows the histogram of the error rates when the participants are sitting in the passenger seat while the car is driving on the highway. The participants are asked to not move their heads during the measurements to suppress active head motion. Since there is less road roughness and fewer distractions from traffic signs/lights or pedestrians on the highway, we did not observe significant degradation of the HR measurement success rate. Figure 12 shows the Bland-Altman plot for the HR measurements under the same conditions. The mean deviation for the motion-compensated case is 0.13 BPM (absolute mean deviation at 5.8 BPM) and the 95% of deviation within \(\pm\)22 BPM from the average deviation. When motion compensation is not used, the success rate drops to 34% while the mean deviation increases to \(-\)19 BPM (absolute mean deviation at 20.5 BPM). Figures 13 and 14 show the error rate distribution as well as the Bland-Altman plot for the HR measurements when the participants drive the vehicle on the highway. Because the participants need to turn their heads occasionally to check traffic or change lanes, these head motions translate into large motion artifacts that add further complexity to HR measurements. Even though such motions only last for a few seconds, they could still induce motion artifacts that are large enough to disrupt the HR measurements. With the depth-based motion compensation enabled, the HR measurements success rate is 71.9 (absolute mean deviation: 7.7 BPM), while the success rate with no compensation is only 13.6 (absolute mean deviation: 25 BPM). From Figure 14, we can see more of the wrong HR readings clustered at the bottom of the graph, which are the results of the additional motion artifacts from the driver's motion. We will discuss potential ways of mitigating such outliers later in the discussion section. **Testing on Local Road:**  
When testing the CVSM system on the local road, we observe the same performance improvement brought by the depth-based motion compensation. Figures 15 and 16 show the error rate as well as the Bland-Altman plot for HR measurements for the local road and participants in the passenger seat scenario. Because both the road surface condition (roughness, potholes) and the traffic (number of stop signs, number of cars) are much worse compared to the highway scenario, the success rate degradation for the HR measurements is also more severe. With the participants sitting on the passenger seat, the success rate is 66% (absolute mean deviation 8.4 BPM) with motion compensation and only 22% (absolute mean deviation 22 BPM) for HR measurements without motion compensation. When the participants move on to drive on the local road, we see similar HR measurement degradation (10%) as the highway scenario (Figures 17 and 18). With motion compensation, the success rate of the HR measurements is 56% (absolute mean deviation 10.5 BPM) when depth-based motion compensation is used and only 12% (absolute mean deviation 25 BPM) when the depth-based motion compensation is not used. **RR Measurements on Highway:**  
In this study, RR is also measured on participants while driving on the highway. Figure 19 shows typical respiration motion acquired on the chest region compared with the reference chest belt on the highway. The ToF camera measures a typical chest wall depth change of \(\pm\)2 mm, with the pattern matching the pressure change measured by the reference respiration belt. Figure 20 shows the distribution of the deviation of RR measurements from the reference respiration monitoring belt. The mean deviation from the reference reading is found to be \(-\)1.4 BPM with a total of 71% of measurements falling within the error of  
Figure 16: Bland–Altman plot of HR measurements when participants sit in the passenger seat on local road conditions with motion compensation (**left**) and without motion compensation (**right**). Figure 17: HR measurement error rate when participants drive on a local road with motion compensation (**left**) and without motion compensation (**right**).