Computer vision-aided mmWave communications for indoor medical healthcare.

Comprehensive and exceedingly precise centralized patient monitoring has become essential to advance predictive, preventive, and efficient patient care in contemporary healthcare. Millimeter-wave (mmWave) technology, boasting high-frequency and high-speed wireless communication, holds promise as a viable solution to this challenge. This paper presents a new approach that combines mmWave communication and computer vision (CV) to achieve real-time patient monitoring and data transmission in indoor medical environments. The system comprises a transmitter, a reflective surface, and multiple communication targets, and utilizes the high-frequency, low-latency features of mmWave as well as CV-based target detection and depth estimation for precise localization and reliable data transmission. A machine learning algorithm analyses real-time images captured by an optical camera to identify target distance and direction and establish clear line-of-sight links. The system proactively adapts its transmission power and channel allocation based on the target's movements, guaranteeing complete coverage, even in potentially obstructive areas. This methodology tackles the escalating demand for high-speed, real-time data processing in modern healthcare, significantly enhancing its delivery.

Point spread function degradation model of a polarization imaging system for wide-field subwavelength nanoparticles: publisher's note.

This publisher's note corrects the author listing in Appl. Opt.59, 7114 (2020).APOPAI0003-693510.1364/AO.397357.

Point spread function degradation model of a polarization imaging system for wide-field subwavelength nanoparticles.

We propose a comprehensive point spread function (PSF) degradation model, which considers multiple factors consisting of degradation of specimen retardant sampling and polarization angularly anamorphic sampling, to indicate the image degradation characteristics of polarization imaging systems. First, a one-layer optical coherence tomography (OCT) model was established to express the retardancy of medium-loading specimens. Then, a PSF degradation model of angularly anamorphic polarization sampling was deduced through the retrieval of Stokes parameters. Finally, maximum a posteriori probability (MAP) was adopted to assess the distribution of the proposed model. Hypothesis testing using actual data and numerical simulations demonstrated that the error of the system followed an asymmetric generalized Gaussian distribution (AGGD). Finite-difference time-domain (FDTD) simulation results and an actual imaging experiment demonstrate the consistency of the proposed model and the degradation characteristics of the PSF, which provide support for the improved accuracy and enhanced image quality of the optical field retrieval of nanoparticles.