ABSTRACT
Doppler radar physiological sensing has been studied for non-contact detection of vital signs including respiratory and heartbeat rates. This paper presents the first micrometer resolution Wi-Fi band Doppler radar for sub-millimeter physiological displacement measurement. A continuous-wave Doppler radar working at 2.4GHz is used for the measurement. It is intended for estimating small displacements on the body surface resulting from physiological activity. A mechanical mover was used as target, and programmed to conduct sinusoidal motions to simulate pulse motions. Measured displacements were compared with a reference system, which indicates a superior performance in accuracy for having absolute errors less than 10µm, and relative errors below 4%. It indicates the feasibility of highly accurate non-contact monitoring of physiological movements using Doppler radar.
Subject(s)
Doppler Effect , Physiology/methods , Radar , Humans , Time FactorsABSTRACT
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.
Subject(s)
Signal Processing, Computer-Assisted , Computer Simulation , Humans , Models, Biological , Monitoring, Physiologic , Movement , RadarABSTRACT
In this paper, an off-the-shelf DC motor is modified into a chest belt and used to successfully measure circumference change on a mechanical chest model, while simultaneously harvesting significant power. Chest circumference change can provide information on tidal volume, which is vital in assessing lung function. The chest circumference change is calculated from the motor's voltage output. Calculated values are within 0.95mm of measured circumference changes, with a standard deviation of 0.37mm. The wearable motor can also harvest at least 29.4µW during normal breathing.
Subject(s)
Biosensing Techniques , Electromagnetic Phenomena , Lung/physiology , Respiration , Thorax/physiology , Algorithms , Anthropometry , Clothing , Electric Power Supplies , Humans , Monitoring, Physiologic/methods , Respiratory Physiological Phenomena , Signal Processing, Computer-Assisted , Stress, Mechanical , Tidal VolumeABSTRACT
The movements of the torso due to normal breathing could be harvested as an alternative, and renewable power source for an ultra-low power electronic device. The same output signal could also be recorded as a physiological signal containing information about breathing, thus enabling self-powered wearable biosensors/harvesters. In this paper, the selection criteria for such a biosensor, optimization procedure, trade-offs, and challenges as a sensor and harvester are presented. The empirical data obtained from testing different modules on a mechanical torso and a human subject demonstrated that an electromagnetic generator could be used as an unobtrusive self-powered medical sensor by harvesting more power, offering reasonable amount of output voltage for rectification purposes, and detecting respiratory effort.
Subject(s)
Biosensing Techniques/methods , Electromagnetic Phenomena , Respiration , Biosensing Techniques/instrumentation , Electronics , Humans , Renewable Energy , Torso/physiologyABSTRACT
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.
Subject(s)
Monitoring, Physiologic/methods , Monitoring, Physiologic/standards , Radar , Sleep/physiology , Doppler Effect , Feasibility Studies , Humans , Polysomnography , Signal Processing, Computer-AssistedABSTRACT
Recent biosensors can measure respiratory rate non-invasively, but limits patient mobility or requires regular battery replacement. Respiratory effort, which can scavenge mW, may power the sensor, but requires minimal sensor power usage. This paper demonstrates feasibility of respiratory rate measurement by using a comparator instead of ADC. A low-power system-on-chip can implement respiratory rate detection and wireless data transmission with a total power consumption under 82 µW. This approach produces significant power savings, and transmission uses under 30% of total power consumption.
Subject(s)
Diagnosis, Computer-Assisted/instrumentation , Monitoring, Ambulatory/instrumentation , Respiratory Rate/physiology , Signal Processing, Computer-Assisted/instrumentation , Spirometry/instrumentation , Wireless Technology/instrumentation , Electric Power Supplies , Equipment Design , Equipment Failure Analysis , Humans , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
Wearable health and fitness monitoring systems are a promising new way of collecting physiological data without inconveniencing patients. Human energy harvesting may be used to power wearable sensors. In this paper, we explore this zero-net energy biosensor concept through sensing and harvesting of respiratory effort. An off the shelf servo motor operation in reverse was used to successfully obtain respiratory rate, while also demonstrating significant harvested power. These are the first reported respiratory rate sensing results using electromagnetic generators.
