Radar-Based, Simultaneous Human Presence Detection and Breathing Rate Estimation
| Autor: | Dov Wulich, Nir Regev |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Respiratory rate
Computer science 0211 other engineering and technologies presence detection TP1-1185 02 engineering and technology spectral-estimation Biochemistry Article vital signs Analytical Chemistry law.invention Respiratory Rate Heart Rate law Statistics 0202 electrical engineering electronic engineering information engineering Humans Electrical and Electronic Engineering Radar Instrumentation Aged Monitoring Physiologic 021101 geological & geomatics engineering micro-Doppler Chemical technology Estimator Spectral density estimation Signal Processing Computer-Assisted 020206 networking & telecommunications Atomic and Molecular Physics and Optics Noise occupancy detection Likelihood-ratio test Breathing Algorithms respiration Energy (signal processing) |
| Zdroj: | Sensors Volume 21 Issue 10 Sensors, Vol 21, Iss 3529, p 3529 (2021) Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| Popis: | Human presence detection is an application that has a growing need in many industries. Hotel room occupancy is critical for electricity and energy conservation. Industrial factories and plants have the same need to know the occupancy status to regulate electricity, lighting, and energy expenditures. In home security there is an obvious necessity to detect human presence inside the residence. For elderly care and healthcare, the system would like to know if the person is sleeping in the room, sitting on a sofa or conversely, is not present. This paper focuses on the problem of detecting presence using only the minute movements of breathing while at the same time estimating the breathing rate, which is the secondary aim of the paper. We extract the suspected breathing signal, and construct its Fourier series (FS) equivalent. Then we employ a generalized likelihood ratio test (GLRT) on the FS signal to determine if it is a breathing pattern or noise. We will show that calculating the GLRT also yields the maximum likelihood (ML) estimator for the breathing rate. We tested this algorithm on sleeping babies as well as conducted experiments on humans aged 12 to 44 sitting on a chair in front of the radar. The results are reported in the sequel. |
| Databáze: | OpenAIRE |
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