Human Remote Sensing - Human Spectral Imaging - Remote Biometrics


Thermal Sensing with Long-Wave Infrared (LWIR) 


Figure 1: Thermal sensing/imaging with LWIR. Image produced with a Specim LWIR hyperspectral imager. (From Wikipedia - CC BY-SA 3.0,




Figure 2: Thermal sensing/imaging with LWIR and pseudocolorization. From Wikipedia - by NASA/IPAC.




Thermal Sensing with Long-Wave Infrared - Remote Thermal Fingerprint based on skin emissivities



Figure 3: Thermal sensing/imaging with LWIR (8-14 μm) - Evaluation of "Human Thermal Fingerprint at Long Distance" by the military (From "Wired" archives - slide 13).




Thermal facial recognition using skin vasculature thermal imprint


Use of blood vessels/capillaries located just under the skin of the face
Possibility to be performed in the dark and below cover (e.g. mask)





Thermal imaging as a biometric approach


Pedestrian Detection
Face Segmentation, Ear Detection, Eye Detection
Hand Geometry Feature Extraction
Fingerprint recognition





Infrared depth detection: face recognition, motion detection, heart rate detection


Infrared depth detection technology, which can be considered as infrared LiDAR, consists of an infrared emitter which projects a grid of infrared dots on a scene/face and an infrared sensor which calculates distance/depth. It was originally used for motion detection for the game console Kinnect Xbox by Microsoft/PrimeSense. Kinnect 2.0 could perform face recognition and heart rate measurement. In 2017, Apple incorporated infrared depth detection technology in its iPhone X camera with the purpose of advanced face recognition. It consists of 30.000 infrared dots directed towards the subject's face to create a 3D full animated mesh.





Remote respiratory monitoring with thermal imaging


Nostrils have different temperatures on inhalation and exhalation. By monitoring their temperature one can determine the frequency of inhalation and exhalation and thereby the respiratory rate.





Sensing of Human Gait (cf. walking) with Doppler RADAR



Figure 4:  "The Spectrogram and Cadence Frequency of a Walking Human" pdf - p.20





Figure 5: Doppler RADAR-measured gait. From “Radar Technology For Acquiring Biological Signals” - G. Greneker (




Micro-Doppler Radar Signatures for Intelligent Target Recognition


#AutomaticTargetRecognition #AutomaticGaitRecognition


Defence R&D Canada (p15-16)


When the radar transmits an electromagnetic signal to a target, the signal interacts with the target and then returns to the radar. The change in the properties of the returned signal reflects on the characteristics of the target.


When the target is moving, the carrier frequency of the returned signal will be shifted due to Doppler effect. The Doppler frequency shift can be used to determine the radial velocity of the moving target. If the target or any structure on the target is vibrating or rotating in addition to target translation, it will induce frequency modulation on the returned signal that generates sidebands about the target's Doppler frequency. This modulation is called the microDoppler (m-D) phenomenon.


The m-D phenomenon can be regarded as a characteristic of the interaction between the vibrating or rotating structures and the target body. If the target undergoes a vibration or rotation, then the Doppler frequency shift generated by the vibration or rotation is a time-varying function and imposes aperiodic time-varying modulation onto the carrier frequency.


The modulation contains harmonic frequencies that depend on the carrier frequency, the vibration or rotation rate, and the angle between the direction of vibration and the direction of the incidentwave. While the Doppler frequency induced by the target body is constant, the m-D due to a vibrating or rotating structure of the target is a function of dwell time.


The micro-Doppler effect was originally introduced in laser systems, but it can also be observed in microwave radar systems. The fundamental research of the m-D phenomenon in radar is a relatively unexplored and untested area [5]. Micro-Doppler radar signatures of battlefield engine are caused by vibration. In many cases, a target or any structure on the target may have vibrations or rotations that are referred to as micro-motion dynamics. For example, vibrations generated by a vehicle engine may be detected from the surface vibration of the vehicle.


From the m-D signature of engine vibration signals, one can further distinguish a gas turbine engine of a tank from a diesel engine of a bus. Vehicles produce their own types of m-D signature as do helicopters. Therefore, the m-D effect can be used to identify specific types of battlefield targets and determine their movement and engine speed.




Obtaining radar signatures of personnel is another important application of m-D. The human walking gait is a complex motion behaviour that comprises different movements of individual body parts. Since September 11, Automatic Gait Recognition (AGR) technology is growing in significance. Because gait recognition technology is so new, researchers are assessing its uniqueness and methods by which it can be evaluated. Various computer vision and ultrasound techniques have been developed to measure gait parameters [26-29]. Real-Time AGR radar systems have recently been recognized as advantageous solutions for detecting, classifying and identifying human targets at distances in all light and weather conditions. Radar has certain advantages over electrooptical (EO) systems and video cameras in that it can penetrate into clothes, does not require light, and operates in fog and other low-visibility weather conditions. However, radar-based recognition is such a novel approach that much fundamental research has yet to be done in this area. The radar sends out a signal and then measures the echo that contains rich information about the various parts of the moving body.


There are different shifts for different body parts, because they are moving at different velocities. For example, a walking man with swinging arms may induce frequency modulation of the returned signal and generate sidebands about the body Doppler.



Classification of micro-Doppler signatures of human motions using log-Gabor filters




Interesting book




Laser monitoring of chest wall displacement - GaAs laser

(~ 870 nm)


(Future studies for infant ventillation)


T. Kondo, T. Uhlig, P. Pemberton, and P.D. Sly, “Laser monitoring of chest wall displacement, “European Respiratory Journal, vol. 10, pp. 1865-1869, 1997


Excerpt from Amy Diane Droitcour’s thesis (2006):


In the study by T.Kondo et al “a laser sensor was used to measure anterioposterior chest wall motion. This is a non-contact measurement, offering no resistance to respiration and no tactile stimuli, which should ensure a noninvasive measurement of respiration that does not alter the respiratory pattern. The laser monitor measures the distance between the chest wall and the sensor, and obtains a respiratory waveform by plotting the change in distance over time. The laser monitor can track rapid changes in lung volume with almost no lag. They propose a monitor with multiple laser sensors so that they can monitor multiple points on the chest, and better model the volumes of respiration.”


Helpful resource on Lasers:


Laser Therapy – Physiotherapy cf.


@infobook tweet






Calculating tidal volume (volume of air displaced during respiration) by magnetometers measuring displacement of body surfaces (sternum, abdomen etc)


Excerpt from Amy Diane Droitcour’s thesis (2006):


“In magnetometer measurements, one coil is driven by an oscillator to produce a weak magnetic field, while other coils are attached to the skin on the thorax and abdomen. The coils on the skin pick up the magnetic field and can determine their position in the field. Magnetometers are susceptible to rotational movement, which creates artifacts [98]. Magnetometers were used to measure the anterio-posterior motion of the rib cage and abdomen [98], and to measure displacement between the abdomen and the sternum [110]. In [110], two transmitter coils operating at two different frequencies are placed near the spine at the sternal level and on the abdomen. Two receiving coils are also placed on the body: one tuned to both frequencies is placed on the sternum to measure the sternal-umbilical displacement and the rib cage anterio-posterior displacement. The other is tuned only to the frequency of the abdominal transmitter and measures the anterior-posterior abdominal displacement. With these three measurements, after calibration, respiratory volume can be estimated using a three-degree-of-freedom model.”


References below  (both available upon subscription)

[98] J Med Eng Technol. 1983 Sep-Oct;7(5):217-23.

Using body surface movements to study breathing.

Gribbin HR.


[110] Chest. 2002 Aug;122(2):684-91.

Tidal volume and respiratory timing derived from a portable ventilation monitor.

McCool FD1, Wang JEbi KL.


Excerpts from [110]: The device consists  of  a  flowmeter,  transmitter,  and receiver  circuitry. Schematic of the magnetometer device depicting coil placement is shown below. Two transmitter coils (yellow and black) oscillate at 8.97 KHz  and  7.0  KHz,  respectively.  The  red  receiver  coil  is tuned to both frequencies, and the green receiver coil is tuned only to 7.0 KHz. The received signals are processed as three channels by three detection circuits. Dual functionality of the second receiver coil  eliminates  the  need  for  a  third  pair  of  coils,  thereby simplifying design and decreasing power needs.





Figure (modified) from reference [110] mentioned above.