Cardiography is an indispensable element of health care. However, the accessibility of at-home cardiac monitoring is limited by device complexity, accuracy, and cost. We have developed a real-time algorithm for heart rate monitoring and beat detection implemented in a custom-built, affordable system. These measurements were processed from seismocardiography (SCG) and gyrocardiography (GCG) signals recorded at the sternum, with concurrent electrocardiography (ECG) used as a reference. Our system demonstrated the feasibility of non-invasive electro-mechanical cardiac monitoring on supine, stationary subjects at a cost of $100, and with the SCG–GCG and ECG algorithms decoupled as standalone measurements. Testing was performed on 25 subjects in the supine position when relaxed, and when recovering from physical exercise, to record 23,984 cardiac cycles at heart rates in the range of 36–140 bpm. The correlation between the two measurements had r² coefficients of 0.9783 and 0.9982 for normal (averaged) and instantaneous (beat identification) heart rates, respectively. At a sampling frequency of 250 Hz, the average computational time required was 0.088 s per measurement cycle, indicating the maximum refresh rate. A combined SCG and GCG measurement was found to improve accuracy due to fundamentally different noise rejection criteria in the mutually orthogonal signals. The speed, accuracy, and simplicity of our system validated its potential as a real-time, non-invasive, and affordable solution for outpatient cardiac monitoring in situations with negligible motion artifact.

We propose an all-silicon design of a multi-band transverse-magnetic-pass (TM-pass) polarizer. The device is based on one-dimensional gratings that work under different regimes that depend on the polarization. With a tapered structure, it is revealed that the operation bandwidth can be extended by multiplexing the diffraction in O-band and the reflection in S-, C-, and L-bands for the transverse-electric (TE) mode. By simulation, we achieve a 343 nm device bandwidth with insertion loss (IL) < 0.4 dB and polarization extinction ratio (PER) > 20 dB. The operation wavelength range covers commonly-used optical telecommunication bands including the O-, S-, C-, and L- bands. Experimental results also show IL < 1.6 dB and PER > 20 dB from 1265 nm to 1360 nm corresponding to the O-band, and from 1500 nm to 1617 nm that corresponds to the C-band. The device is a single-etched design on the standard 220 nm silicon-on-insulator (SOI) with silicon oxide cladding. Such a simple and compatible design paves the way for developing practical multi-band silicon photonic integrated circuits.

Objective: We present a novel seismocardiography (SCG) -based approach for real-time cardio-respiratory activity measurement called the Autocorrelated Differential Algorithm (ADA). Methods: Measurements were performed on ten male subjects in the supine position for three 7-minute-long sets each, corresponding to 14,619 heartbeats. The ADA utilized temporal variations, windowing, and autocorrelation to produce physiological measurements corresponding to heart rate (HR), and left ventricular ejection time, and estimations of respiration rate, volume, and phase. The versatility of the ADA was investigated in two contexts: physical exertion and heart rate variability. Results: The accuracy of HR measurements at a sampling frequency of 200 Hz resulted in a correlation coefficient (r 2 ) of 0.9808 when compared with a manual annotation of all datasets. Its reproducibility was tested on externally obtained SCG and electrocardiography datasets, which produced an r 2 of 0.8224. The accuracy and computational time was also characterized for different sampling frequencies to quantify performance. The recommended sampling frequency is 200 Hz corresponding to a computation time of 0.05 s per instantaneous measurement using a standard desktop computer. Conclusion: The ADA delivered real-time SCG measurements with a refresh rate that was dependent on the computational time per measurement, which could be decreased by lowering the sampling frequency. Significance: The presented algorithm offers a novel tool towards real-time physiological monitoring in clinical and everyday scenarios.

Wearable sensing has become a vital approach to cardiac health monitoring, and seismocardiography (SCG) is emerging as a promising technology in this field. However, the applicability of SCG is hindered by motion artifacts, including those encountered in practice of which the strongest source is walking. This holds back the translation of SCG to clinical settings. We therefore investigated techniques to enhance the quality of SCG signals in the presence of motion artifacts. To simulate ambulant recordings, we corrupted a clean SCG dataset with real-walking-vibrational noise. We decomposed the signal using several empirical-mode-decomposition methods and the maximum overlap discrete wavelet transform (MODWT). By combining MODWT, time-frequency masking, and nonnegative matrix factorization, we developed a novel algorithm which leveraged the vertical axis accelerometer to reduce walking vibrations in dorsoventral SCG. The accuracy and applicability of our method was verified using heart rate estimation. We used an interactive selection approach to improve estimation accuracy. The best decomposition method for reduction of motion artifact noise was the MODWT. Our algorithm improved heart rate estimation from 0.1 to 0.8 r-squared at −15 dB signal-to-noise ratio (SNR). Our method reduces motion artifacts in SCG signals up to a SNR of −19 dB without requiring any external assistance from electrocardiography (ECG). Such a standalone solution is directly applicable to the usage of SCG in daily life, as a content-rich replacement for other wearables in clinical settings, and other continuous monitoring scenarios. In applications with higher noise levels, ECG may be incorporated to further enhance SCG and extend its usable range. This work addresses the challenges posed by motion artifacts, enabling SCG to offer reliable cardiovascular insights in more difficult scenarios, and thereby facilitating wearable monitoring in daily life and the clinic.

We propose two designs of low‐loss and temperature‐insensitive single‐mode waveguide crossing on silicon‐on‐insulator (SOI) platform with 415‐nm operation bandwidth covering all optical communication bands. Both designs are enabled by subwavelength grating (SWG) modeled as an anisotropic metamaterial. The initial design applies straight SWG as the lateral cladding of the waveguide crossing to minimize the refractive index contrast and reduce the insertion loss (IL), but needs a relatively long taper. An improved design is then proposed where the curved SWG is introduced to replace the straight SWG to decrease the taper length and improve the performance. The waveguide crossing with the improved design achieves a calculated maximum IL of 0.229 dB and maximum crosstalk of −35.6 dB over a 415‐nm wavelength range from 1260 nm to 1675 nm. The proposed devices are fabricated and characterized. Measured results of the improved design show a maximum IL of 0.264 dB and maximum crosstalk of −30.9 dB over a 230‐nm wavelength range including O‐, C‐, and L‐bands, which accord well with the simulation. Low temperature sensitivity has also been demonstrated in both simulations and experiments.