Radar-Based Multi-Person Non-Contact Vital Signs Monitoring
Background:
Non-contact vital signs monitoring (NCVSM) of multiple individuals, such as respiration and heartbeat, has been investigated in recent years due to the rising cardiopulmonary morbidity, the risk of disease transmission, patient discomfort and heavy burden on medical staff. Frequency Modulated Continuous Wave (FMCW) radars have shown great promise in meeting these needs. However, contemporary techniques for NCVSM via FMCW radars, are based on simplistic models and present difficulties in coping with noisy environments containing multiple objects.
Sparsity-Based Multi-Person Localization and NCVSM
We developed an extended model for multi-person NCVSM via FMCW radar. By utilizing the sparse nature of the modelled signals in conjunction with human-typical cardiopulmonary features, we present accurate localization and NCVSM of multiple individuals in a cluttered scenario, using only a single channel. Specifically, we provide a joint-sparse recovery (JSR) mechanism to localize humans in a noisy environment and develop a robust method for NCVSM called VSDR (for vital signs based dictionary recovery), which uses a dictionary-based approach to search for the rates of respiration (RR) and heartbeat (HR) over high-resolution grids corresponding to human cardiopulmonary activity.
Fig. 1. Block diagram of the proposed approach for multi-person NCVSM via SISO FMCW radar, which yields accurate estimates of RR and HR by exploiting the sparse composition of the input data in accordance with human cardiopulmonary properties, using only a single channel.
The proposed approach was developed for SISO, SIMO and MIMO configurations.
SISO – single-input-single-output
SIMO – single-input-multiple-output
MIMO – multiple-input-multiple-output
Results
The advantages of our method are illustrated through comprehensive experiments as well as simulated data.
Experimental analsis:
Simulated analysis:
The simulated trials combine the proposed model with in-vivo data of 30 monitored individuals. We demonstrate accurate human localization in a noisy scenario that includes both static and vibrating objects and show that our VSDR approach outperforms existing NCVSM techniques, based on several statistical metrics.
A. Multi-Person Localization in Cluttered Scenarios
Scenario #1:
Multiple objects located at different radial distances – using a SISO setup
Fig. 2. Multi-person localization by the setup of Table I, for SNR = 0[dB]. (a) The Range vs. Slow-Time map. The row-wise intensities correspond to the DC component and the reflections of Table I 's objects. (b) Several localization techniques based on the average power [4], the std estimate [5] and the proposed JSR [1]. Only JSR localization properly detects the subjects in the given scenario.
Scenario #2:
Multiple objects located at the same radial distance but at different angles – using a SIMO setup
Fig. 3. Multi-person localization by the setup of Table 1 that includes equidistant targets, for SNR=0 [dB]. Only the proposed JSR method properly detects the humans in the given scenario.
B. Multi-Person NCVSM.
Fig. 4. Simultaneous NCVSM of 3 subjects given their thoracic vibrations, w.r.t. known references, SNR=0 [dB].
Rows: 3 different subjects. Columns: Extracted thoracic vibrations for a given time interval, proposed VSDR [1], FFT w/ ZP, FFT w/o ZP and Phase-Reg. The VSDR estimates are the closest to the reference estimates for both RR and HR.
• In terms of performance, the VSDR outperforms the other compared methods in 4 different metrics, for any examined SNR case.
• Specifically, In the more challenging task of HR monitoring, the gap between the VSDR and the other techniques is prominent.
Fig. 5. Median NCVSM performance of the proposed VSDR [1] compared to other techniques vs. SNR. Rows: HR, RR. Columns: SR - 2 bpm, PCC, MAE, RMSE.
Hardware
We developed a dedicated hardware phantom that simulates multi-person thoracic displacements through which realistic experiments for NCVSM using radars can be performed. The phantom reduces the need for human trials and enables proper calibration of the suggested algorithms.
Our demonstration platform consists of (1) a vibration generator for imitating thoracic displacements, (2) flat circular metal plates (24 cm diameter), (3) a radar sensor, located up to 2 meters from the phantom, and (4) a dedicated experimental setup.
Scenario #1:
Hardware phantom for single-person NCVSM via radar
Graphical User Interface:
Scenario #2:
Hardware phantom for multi-person NCVSM via radar.
Graphical User Interface
• Example of localization and NCVSM of 3 people simultaneously:
• Two equidistant targets located approximately at 1 [m] from the radar and +-10 [deg]. The third target is located approximately at 1.1 [m] from the radar and +25 [deg] .
• The operator can choose between a trial of sinusoids or human thoracic vibrations as well as determining the frame rate and duration of the trial.
References:
[1] Y. Eder and Y. C. Eldar, "Sparsity-Based Multi-Person Non-Contact Vital Signs Monitoring via FMCW Radar," IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 6, pp. 2806-2817.
[2] Y. Eder, Z. Liu and Y. C. Eldar, "Sparse Non-Contact Multiple People Localization and Vital Signs Monitoring Via FMCW Radar,"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece 2023, pp. 1-5.
[3] S. Schellenberger, K. Shi, T. Steigleder, A. Malessa, F. Michler, L.Hameyer, N. Neumann, F. Lurz, R. Weigel, C. Ostgathe, and A. Koelpin,“A dataset of clinically recorded radar vital signs with synchronised reference sensor signals", Scientific data, vol. 7, no. 1, pp. 1–11, 2020.
[4] M. Alizadeh, G. Shaker, J. C. M. D. Almeida, P. P. Morita and S. Safavi-Naeini, "Remote Monitoring of Human Vital Signs Using mm-Wave FMCW Radar" IEEE Access, vol. 7, pp. 54958-54968, 2019.
[5] G. Sacco, E. Piuzzi, E. Pittella, and S. Pisa, "An FMCW radar for localization and vital signs measurement for different chest orientations", Sensors, vol. 20, no. 12, pp. 3489, 2020.
Videos:
ICASSP22 Hardware Demo: Contactless Vital Signs - YouTube.
Sparsity-Based Multi-Person NCVSM Using Radar - YouTube.
ICASSP 2023 IEEE International Conference on Acoustics, Speech and Signal Processing: