Book contents
- Frontmatter
- Contents
- Contributors
- 1 Implantable Wireless Medical Devices for Gastroesophageal Applications
- 2 Embedded Wireless Device for Intracranial Pressure Monitoring
- 3 Wireless Intracranial Pressure Systems for the Assessment of Traumatic Brain Injury
- 4 Microwave Biosensors for Noninvasive Molecular and Cellular Investigations
- 5 Wearable Radar Tag Systems for Physiological Sensing/Monitoring
- 6 Physiological Radar Sensor Chip Development
- 7 Noise- and Interference-Reduction Methods for Microwave Doppler Radar Vital Signs Monitors
- 8 Biomedical Applications of UWB Technology
- Index
- References
5 - Wearable Radar Tag Systems for Physiological Sensing/Monitoring
- Frontmatter
- Contents
- Contributors
- 1 Implantable Wireless Medical Devices for Gastroesophageal Applications
- 2 Embedded Wireless Device for Intracranial Pressure Monitoring
- 3 Wireless Intracranial Pressure Systems for the Assessment of Traumatic Brain Injury
- 4 Microwave Biosensors for Noninvasive Molecular and Cellular Investigations
- 5 Wearable Radar Tag Systems for Physiological Sensing/Monitoring
- 6 Physiological Radar Sensor Chip Development
- 7 Noise- and Interference-Reduction Methods for Microwave Doppler Radar Vital Signs Monitors
- 8 Biomedical Applications of UWB Technology
- Index
- References
Summary
Introduction
One limitation with Doppler radar is that for vital sign monitoring, any torso movement by the subject will affect the measurements. Other limitations include interference from moving objects or people in the vicinity and an inability to detect multiple targets. These issues arise due to the fact that a continuous-wave (CW) radar motion-detecting system is not inherently selective and will detect any motion in its field of view. Various solutions have been proposed for this, such as the use of multiple antennas with blind source separation (BSS) techniques to identify multiple respiration signatures [2,36] and use of two and four radars to cancel body sway [12,38]. BSS techniques are very effective in identifying multiple motion signatures but cannot associate those signatures with a particular source, leading to ambiguity in the interpretation of results. A good solution still does not exist for identification of a subject from the environmental clutter and making the Doppler radar system selective.
Bringing selectivity to the radar implies introducing ways to ensure that the motion signals obtained correspond to the desired source. By rejecting clutter motion and detecting the physiologic motion of a subject, we are implementing the first stage of selectivity. The only way to resolve targets without placing any circuit on them is by spatial resolution and range. Spatial resolution can be brought to the radar through coherent detection using pulse Doppler radar. This principle is used in synthetic aperture radars (SARs) and inverse synthetic aperture radars (ISARs) [33]. In order to achieve good resolution, we would have to use millimeter-wave signals and associated circuitry and would still have ambiguities in the range. Spatial resolution can also be obtained through multiple-input, multiple-output (MIMO) systems and BSS techniques, but the sources of motion would still remain ambiguous. Range can also be calculated using frequency-modulated continuous-wave (FMCW) radars, but then Doppler processing would become more challenging. The resolution provided by FMCW radar is also limited by the bandwidth of frequencies used.
Introducing modulation at the source of motion may allow more flexible solutions compatible with the current Doppler radar system. The way to achieve selectivity would be to have some form of modulated backscatter from the subject and no modulated backscatter from other objects, similar to radiofrequency identification (RFID) systems. Although RFID technology is mature and easily available, it is difficult to apply to motion-sensing applications.
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- Medical and Biological Microwave Sensors and Systems , pp. 154 - 171Publisher: Cambridge University PressPrint publication year: 2017