## 2 Materials and Methods
### Spatial Multi-Dimensional Pulse Wave Signal Processing Method
Since Algorithm II also uses magnitude as an indicator, the reference point is concentrated on sensor 2 at both A and position B positions. Thus, there is some difference between the processing results of Algorithm II and the standard input signal. Subject to the test data of sensor 2, Algorithm II has different calculations at position A and position B. The effect of Algorithm II is very similar to that of Algorithm I. The processing of Algorithm III takes advantage of the spatial characteristics of the array sensors to extract as much commonality and retain all valid data information as possible. First, at position A, algorithm III considers the acquisition results of sensor 1, sensor 2, and sensor 3. Algorithm III was linearly adjusted to obtain a waveform that was as similar as possible to the standard input signal. Finally, linear synthesis ensures that there is not much energy lost during the processing of Algorithm III. As a result, Algorithm III's processing is much closer to the standard input signal, both in waveform shape and energy. The same standard input signal at different positions ensures that Algorithm III's results are also nearly similar. Compared to Algorithm I and Algorithm II, Algorithm III has good robustness at position A and position B.

Figure 6: Schematic diagram of sensor contact between SPVG and PAWS at test location A and B. ## 5 Conclusions

A one-dimensional pulse wave signal extracted from a spatial multi-dimensional signal collected by a pressure-based sensor array is beneficial for disease diagnosis. However, the existing methods have some shortcomings, and the processing results in the multiple acquisition process are not the same. Therefore, this paper proposes a novel multi-dimensional composition method based on time series similarity. The new method includes filtering, effective waveform screening, linear adjustment, and linear synthesis to obtain stable results under different test regions. Design a simulated pulse wave acquisition experiment composed of PAWS and SPVG, which is repeated tests in different positions to verify three algorithms' performance. The experimental results show that the proposed method can virtually reproduce the standard input waveform well and has the right consistency and stability. In summary, the new method is a suitable replacement for the previous method, thus providing physicians with a better basis for pulse wave diagnosis. We will continue to improve the algorithm's reliability by adopting a more refined modeling approach in future work. We also believed that this work would help in the promotion of pulse-wave-assisted diagnosis. ## 6 Patents

The works presented in this paper are subject to pending China and international patents filed by the Institute of Microelectronics of Chinese Academy of Sciences (IMECAS) in China (201910570914.4, 201910570913.X, PCT/CN2019/093154, and PCT/CN2019/093156). **Author Contributions:** Conceptualization, H.Z. ([PERSON]), and Y.Z. ; data curation, [PERSON] ([PERSON]); formal analysis, [PERSON] ([PERSON]), J.Z., S.Z., and Y.Z. ; funding acquisition, H.Z. ([PERSON]); investigation, H.Z. ([PERSON]), methodology, H.Z. ([PERSON]), and Y.Z. ; project administration, Y.Z., and H.Z. ([PERSON]); resources, Y.Z., J.Z., [PERSON] ([PERSON]); algorithm, H.Z. ([PERSON]); software, H.Z. ([PERSON]), X.G., and C.C. ; supervision, H.Z. ([PERSON]); validation, [PERSON] ([PERSON]), J.Z., C.C., X.G., S.Z., and Y.Z. ; visualization, H.Z. ([PERSON]), and C.C. ; writing--original draft, [PERSON] ([PERSON]); writing--review and editing, [PERSON] ([PERSON]), Y.Z., and H.Z. ([PERSON]). All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the National Science and Technology Major Project (NO. 2018 ZX01031201, 2018 ZX09201011). **Conflicts of Interest:** The authors declare no conflict of interest. ## References

* (1) [PERSON]; [PERSON]; [PERSON] Heart rate measurement and electrical pulse signal analysis for subjects span of 20-80 years.