Occupancy Estimation from Blurred Video: A Multifaceted Approach with Privacy Consideration.

Building occupancy information is significant for a variety of reasons, from allocation of resources in smart buildings to responding during emergency situations. As most people spend more than 90% of their time indoors, a comfortable indoor environment is crucial. To ensure comfort, traditional HVAC systems condition rooms assuming maximum occupancy, accounting for more than 50% of buildings' energy budgets in the US. Occupancy level is a key factor in ensuring energy efficiency, as occupancy-controlled HVAC systems can reduce energy waste by conditioning rooms based on actual usage. Numerous studies have focused on developing occupancy estimation models leveraging existing sensors, with camera-based methods gaining popularity due to their high precision and widespread availability. However, the main concern with using cameras for occupancy estimation is the potential violation of occupants' privacy. Unlike previous video-/image-based occupancy estimation methods, we addressed the issue of occupants' privacy in this work by proposing and investigating both motion-based and motion-independent occupancy counting methods on intentionally blurred video frames. Our proposed approach included the development of a motion-based technique that inherently preserves privacy, as well as motion-independent techniques such as detection-based and density-estimation-based methods. To improve the accuracy of the motion-independent approaches, we utilized deblurring methods: an iterative statistical technique and a deep-learning-based method. Furthermore, we conducted an analysis of the privacy implications of our motion-independent occupancy counting system by comparing the original, blurred, and deblurred frames using different image quality assessment metrics. This analysis provided insights into the trade-off between occupancy estimation accuracy and the preservation of occupants' visual privacy. The combination of iterative statistical deblurring and density estimation achieved a 16.29% counting error, outperforming our other proposed approaches while preserving occupants' visual privacy to a certain extent. Our multifaceted approach aims to contribute to the field of occupancy estimation by proposing a solution that seeks to balance the trade-off between accuracy and privacy. While further research is needed to fully address this complex issue, our work provides insights and a step towards a more privacy-aware occupancy estimation system.

Dynamic Arctangent Center-Tracking Method for Respiratory Displacement Monitoring of Subjects in Arbitrary Positions.

Accurate continuous measurement of respiratory displacement using continuous wave Doppler radar requires rigorous management of dc offset which changes when a subject changes distance from the radar measurement system. Effective measurement, therefore, requires robust dynamic calibration which can recognize and compensate for changes in the nominal position of a subject. In this paper, a respiratory displacement measurement algorithm is proposed which can differentiate between sedentary and non-sedentary conditions and continuously adapt to provide long-term monitoring of a subject's sedentary respiration. Arctangent demodulation is an effective means of quantifying continuous displacement using a quadrature Doppler radar, yet it depends on accurate identification of dc offset and dc information contributions in the radar I-Q arc with the subject in a particular position. The dynamic calibration method proposed here is demonstrated to differentiate between sedentary and non-sedentary conditions for six subjects to produce accurate sedentary respiration measurements even when the subject arbitrarily changes position, once the appropriate thresholds are established for the measurement environment.

Doppler radar remote sensing of respiratory function.

Doppler radar remote sensing of torso kinematics can provide an indirect measure of cardiopulmonary function. Motion at the human body surface due to heart and lung activity has been successfully used to characterize such measures as respiratory rate and depth, obstructive sleep apnea, and even the identity of an individual subject. For a sedentary subject, Doppler radar can track the periodic motion of the portion of the body moving as a result of the respiratory cycle as distinct from other extraneous motions that may occur, to provide a spatial temporal displacement pattern that can be combined with a mathematical model to indirectly assess quantities such as tidal volume, and paradoxical breathing. Furthermore, it has been demonstrated that even healthy respiratory function results in distinct motion patterns between individuals that vary as a function of relative time and depth measures over the body surface during the inhalation/exhalation cycle. Potentially, the biomechanics that results in different measurements between individuals can be further exploited to recognize pathology related to lung ventilation heterogeneity and other respiratory diagnostics.

Unobtrusive occupancy and vital signs sensing for human building interactive systems.

Cognitive buildings use data on how occupants respond to the built environment to proactively make occupant-centric adjustments to lighting, temperature, ventilation, and other environmental parameters. However, sensors that unobtrusively and ubiquitously measure occupant responses are lacking. Here we show that Doppler-radar based sensors, which can sense small physiological motions, provide accurate occupancy detection and estimation of vital signs in challenging, realistic circumstances. Occupancy was differentiated from an empty room over 93% of the time in a 3.4 m × 8.5 m conference room with a single sensor in both wall and ceiling-mounted configurations. Occupancy was successfully detected while an occupant was under the table, visibly blocked from the sensor, a scenario where infrared, ultrasound, and video-based occupancy sensors would fail. Heart and respiratory rates were detected in all seats in the conference room with a single ceiling-mounted sensor. The occupancy sensor can be used to control HVAC and lighting with a short, 1-2 min delay and to provide information for space utilization optimization. Heart and respiratory rate sensing could provide additional feedback to future human-building interactive systems that use vital signs to determine how occupant comfort and wellness is changing with time.

Identification of COVID-19 Type Respiratory Disorders Using Channel State Analysis of Wireless Communications Links.

One deadly aspect of COVID-19 is that those infected can often be contagious before exhibiting overt symptoms. While methods such as temperature checks and sinus swabs have aided with early detection, the former does not always provide a reliable indicator of COVID-19, and the latter is invasive and requires significant human and material resources to administer. This paper presents a non-invasive COVID-19 early screening system implementable with commercial off-the-shelf wireless communications devices. The system leverages the Doppler radar principle to monitor respiratory-related chest motion and identifies breathing rates that indicate COVID-19 infection. A prototype was developed from software-defined radios (SDRs) designed for 5G NR wireless communications and system performance was evaluated using a robotic mover simulating human breathing, and using actual breathing, resulting in a consistent respiratory rate accuracy better than one breath per minute, exceeding that used in common medical practice.Clinical Relevance-This establishes the potential efficacy of wireless communications based radar for recognizing respiratory disorders such as COVID-19.

Separation of Respiratory Signatures for Multiple Subjects Using Independent Component Analysis with the JADE Algorithm.

Respiration monitoring using microwave Doppler radar has attracted significant interest over the last four decades due to its non-invasive and non-contact form of measurement. However, this technology is still not at the level of practical implementations in healthcare due to motion artifacts and interference from multiple subjects within the range of the Doppler radar sensor. Most reported results in literature focus only on single subject measurements because when multiple subjects are present there are interfering respiration signals which are difficult to separate as individual respiration signals. This paper investigates the feasibility of separating respiratory signatures from the multiple subjects. We employed a new approach using Independent Component Analysis (ICA) with the Joint Approximate Diagonalization of Eignematrices (JADE) algorithm to achieve this for closely spaced subjects, and the system is also capable of estimating Direction of Arrival (DOA) for well-spaced subjects. Experimental results demonstrated that the ICA-JADE method can separate respiratory signatures from two subjects one meter apart from each other at a distance from the radar of 2.89 meters. The separated respiratory pattern closely correlates with reference chest belt respiration patterns, and the mean square error is approximately 11.58%. Concisely, this paper clearly demonstrates that by integrating ICA with the JADE algorithm in a Doppler radar physiological monitoring system, multiple subjects can be monitored simultaneously.

Wrist-worn heartbeat monitoring system based on bio-impedance analysis.

In this paper, a bio-impedance analysis (BIA) based wrist-worn heartbeat monitoring system is proposed. The system is able to estimate heart rate from a subject's wrist with only four electrodes. The design is achieved with a standard BIA device and off-the-shelf components for signal conditioning. The measured heartbeat-related impedance signal is compared with a reference heart rate signal obtained from piezoelectric finger pulse transducer. The BIA results agree with the reference, which validates the feasibility of the proposed system. To the best of our knowledge, this is the first reported BIA heartbeat monitoring system in the wristband configuration.

Packet radar spectrum recovery for physiological signals.

Packet Doppler radar is investigated for extracting physiological signals. System on Chip is employed as a signal source in packet mode, and it transmits signals intermittently at 2.405 GHz to save power. Reflected signals are demodulated directly by spectral analysis of received pulses in the baseband. Spectral subtraction, using data from an empty room, is applied to extract the periodic movement. It was experimentally demonstrated that frequency of the periodic motion can be accurately extracted using this technique. Proposed approach reduces the computation complexity of the signal processing part effectively.

Considerations for integration of a physiological radar monitoring system with gold standard clinical sleep monitoring systems.

A design for a physiological radar monitoring system (PRMS) that can be integrated with clinical sleep monitoring systems is presented. The PRMS uses two radar systems at 2.45 GHz and 24 GHz to achieve both high sensitivity and high resolution. The system can acquire data, perform digital processing and output appropriate conventional analog outputs with a latency of 130 ms, which can be recorded and displayed by a gold standard sleep monitoring system, along with other standard sensor measurements.

A data efficient method for characterization of chameleon tongue motion using Doppler radar.

A new technique is described for study of the study of high velocity animal movements using a continuous wave Doppler radar operating at 24 GHz. The movement studied was tongue projection kinematics during prey capture by the lizard Chamaeleo Jacksonii. The measurements were verified with a high speed video reference, recorded at 1000 frames per second. The limitations and advantages of both the methodologies are compared and tongue speeds of 3:65 m/s were observed. These results show a useful application of radar to augment visual sensing of biological motion and enable the use of monitoring in a wider range of situations.

Non-contact displacement estimation using Doppler radar.

Non-contact Doppler radar has been used extensively for detection of physiological motion. Most of the results published to date have been focused on estimation of the physiological rates, such as respiratory rate and heart rate, with CW and modulated waveforms in various settings. Accurate assessment of chest displacement may take this type of monitoring to the new level, by enabling the estimation of associated cardiopulmonary volumes, and possibly pulse pressure. To obtain absolute chest displacement with highest precision, full nonlinear phase demodulation of the quadrature radar outputs must be performed. The accuracy of this type of demodulation is limited by the drifting received RF power, varying dc offset, and channel quadrature imbalance. In this paper we demonstrate that if relatively large motion is used to calibrate the system, smaller motion displacement may be acquired with the accuracy on the order of 30 µm.

Non-contact Doppler radar monitoring of cardiorespiratory motion for Siberian sturgeon.

This paper presents the first reported use of Doppler radar to remotely sense heart and ventilation rates of fish. The Radar reported 35 to 40 BPM heart rate and 115 to 145 BPM ventilation rates for Siberian Sturgeon, with agreement from a video reference. Conventional fish vital signs measurements require invasive surgery and human handling--these are problematic for large scale monitoring, for measuring deep sea fish, and other situations which preclude human interaction with each individual subject. These results show a useful application of radar to augment existing cardiovascular and ventilatory activity sensing techniques and enable monitoring in a wider range of situations.

Parametric study of antennas for long range Doppler radar heart rate detection.

This research presents results obtained from long range measurements of physiological motion pertaining to human cardiac and respiration activity. A pulse pressure sensor was used as reference to verify the results from radar signals. A motion detection and grading algorithm was used to detect the presence of heart rate. In addition to showing that human heart rate and respiration can be measured at distances of 21 and 69 meters respectively, the effect of antenna size, radiation pattern and gain on the range of the radar has also been studied.

A new algorithm for detection of heart and respiration rate with UWB signals.

Proposed is a detection algorithm for physiological monitoring with Ultra Wide Band (UWB) radar. This new algorithm is based on detection of movement energy in a specified band of frequency using wavelet and filter banks. One of the advantages of this algorithm is its ability to detect heart and respiration rates of a subject in an environment containing other motion. The heart movement is detected with the accuracy of 95% and respiration with the 100%. This algorithm has a repeatability of 93% which is a significant characteristic of the method.

Activity monitoring and motion classification of the lizard Chamaeleo jacksonii using multiple Doppler radars.

We describe a simple, non-contact and efficient tool for monitoring the natural activity of a small lizard (Chamaeleo jacksonii) to yield valuable information about their metabolic activity and energy expenditure. It allows monitoring in a non-confined laboratory environment and uses multiple Doppler radars operating at 10.525 GHz. We developed a classification algorithm that can differentiate between fidgeting and locomotion by processing the quadrature baseband signals from the radars. The results have been verified by visual inspection and indicate that the tool could also be used for automated monitoring of the activities of reptiles and other small animals.

Feasibility assessment of Doppler radar long-term physiological measurements.

In this paper we examine the feasibility of applying doppler radar technique for a long-term health monitoring. Doppler radar was used to detect and eliminate periods of significant motion. This technique was verified using a human study on 17 subjects, and it was determined that for 15 out of 17 subjects there was no significant motion for over 85% of the measurement interval in supine positions. Majority of subjects exhibited significantly less motion in supine position, which is promising for sleep monitoring, and monitoring of hospitalized patients.

DC coupled Doppler radar physiological monitor.

One of the challenges in Doppler radar systems for physiological monitoring is a large DC offset in baseband outputs. Typically, AC coupling is used to eliminate this DC offset. Since the physiological signals of interest include frequency content near DC, it is not desirable to simply use AC coupling on the radar outputs. While AC coupling effectively removes DC offset, it also introduces a large time delay and distortion. This paper presents the first DC coupled IQ demodulator printed circuit board (PCB) design and measurements. The DC coupling is achieved by using a mixer with high LO to RF port isolation, resulting in a very low radar DC offset on the order of mV. The DC coupled signals from the PCB radar system were successfully detected with significant LNA gain without saturation. Compared to the AC coupled results, the DC coupled results show great advantages of less signal distortion and more accurate rate estimation.

System-on-chip based Doppler radar occupancy sensor.

System-on-Chip (SoC) based Doppler radar occupancy sensor is developed through non contact detection of respiratory signals. The radio was developed using off the shelf low power RF CC2530 SoC chip by Texas Instruments. In order to save power, the transmitter sends signal intermittently at 2.405 GHz. Reflected pulses are demodulated, and the baseband signals are processed to recover periodic motion. The system was tested both with mechanical target and a human subject. In both cases Doppler radar detected periodic motion closely matched the actual motion, and it has been shown that an SoC based system can be used for subject detection.

Pulse pressure monitoring through non-contact cardiac motion detection using 2.45 GHz microwave Doppler radar.

The use of a Continuous Wave (CW) quadrature Doppler radar is proposed here for continuous non-invasive Pulse Pressure monitoring. A correspondence between the variation in systemic pulse and variation in the displacement of the chest due to heart is demonstrated, establishing feasibility for the approach. Arctangent demodulation technique was used to process baseband data from radar measurements on two test subjects, in order to determine the absolute cardiac motion. An Omron digital Blood pressure cuff was used to measure the systolic and diastolic blood pressures from which the pulse pressure was calculated. Correlation between pulse pressure and cardiac motion was observed through changes induced due to different postures of the body.

Noise and range considerations for close-range radar sensing of life signs underwater.

Close-range underwater sensing of motion-based life signs can be performed with low power Doppler radar and ultrasound techniques. Corresponding noise and range performance trade-offs are examined here, with regard to choice of frequency and technology. The frequency range examined includes part of the UHF and microwave spectrum. Underwater detection of motion by radar in freshwater and saltwater are demonstrated. Radar measurements exhibited reduced susceptibility to noise as compared to ultrasound. While higher frequency radar exhibited better signal to noise ratio, propagation was superior for lower frequencies. Radar detection of motion through saltwater was also demonstrated at restricted ranges (1-2 cm) with low power transmission (10 dBm). The results facilitate the establishment of guidelines for optimal choice in technology for the underwater measurement motion-based life signs, with respect to trade offs involving range and noise.