**3. Examples of applications**

While remote sensing is not currently used for medical and health care applications in everyday life, several studies have been conducted. This section discusses the following

Remote Sensing for Medical and Health Care Applications 485

Fig. 2. Sample data of a compact microwave radar output (A) showing a cyclic oscillation that corresponds to cardiac oscillations measured by ECG (B) (Suzuki et al., 2008).

Cross-Correlation

Fig. 3. Example of remote sensing in health care. (A) In both non-contact and contact (ECG) measurements, the LF of a subject (reflecting sympathetic activation) exhibits a peak during

The prototype device in this example consists of a compact 24 GHz microwave Doppler radar (8 5 3 cm) attached to the back of a chair. The low-frequency/high-frequency (LF/HF) components of the HRV (which reflects the sympathovagal balance) of eight volunteers were determined by a prototype system using the maximum entropy method (MEM). The change in the LF and LF/HF components measured by a remote sensor was consistent with that measured by a contact electrocardiography sensor. It is very difficult to extract R-R intervals of heartbeats sufficiently accurately to calculate the HRV; this is thought to be because inaccuracies were introduced due to the microwave radar being susceptible to noise. However, measuring HRV by adopting MEM, which enables HRV to be estimated rapidly, stably, and accurately, was demonstrated to be successful for the first

audio stimulation. (B) Cross-correlation of the LF between non-contact and contact



Time lag (sec)

Contact Non-contact

(A) (B)

time.

LF (msec2

)

0 60 120 180 240 300 360 Time (sec)

measurements of the same subject (Suzuki et al., 2008).

Audio Stimuli

typical examples of remote sensing in medical and health care settings: (1) monitoring daily health and mental stress by estimating changes in the autonomic nervous system (ANS); (2) welfare and health care for the elderly; and (3) medical diagnosis such as screening of patients with infections.

#### **3.1 Measurement of ANS**

To determine stress levels when driving or operating equipment, a 24 GHz compact microwave radar was used to perform remote measurements of the heart rate variability (HRV) under autonomic activation induced by a stressful sound and foods (Suzuki et al., 2008, Gotoh et al., 2009). Changes in the ANS (sympathovagal balance) can be monitored by measuring the HRV. This variability is used as an index of mental stress.

For examples, when an animal is attacked, its sympathetic nervous system spontaneously prepares for fight or flight by elevating the heart rate and increasing the blood pressure and body temperature. In contrast, when it is in a relaxed state, the parasympathetic nervous system is activated, and the opposite phenomena occur. Such processes are constantly in equilibrium in daily life (Akselrod et al., 1981, Derrick,1988).

Sympathovagal balance can be monitored by measuring variations in the heartbeat interval, and the degree of mental stress can be determined. This index is used for diagnosing psychological disorders and as well as the condition of circulatory organs. Moreover, many approaches for measuring the HRV are used in psychology (Vincent et al., 1996), occupational health (Miyake, 2001, Princi et al., 2005), and ergonomics research (Sirevaag et al., 1993, Gould et al., 2009). An estimation technique has been medically established. Thus, if electrocardiograms (ECG) can be replaced by a remote sensing method that allows simple and accurate monitoring in everyday life, mental stress can be assessed at any time and in any place.

Fig. 1. Prototype chair equipped with a non-contact microwave radar system to monitor mental stress in workers (Suzuki et al., 2008).

typical examples of remote sensing in medical and health care settings: (1) monitoring daily health and mental stress by estimating changes in the autonomic nervous system (ANS); (2) welfare and health care for the elderly; and (3) medical diagnosis such as screening of

To determine stress levels when driving or operating equipment, a 24 GHz compact microwave radar was used to perform remote measurements of the heart rate variability (HRV) under autonomic activation induced by a stressful sound and foods (Suzuki et al., 2008, Gotoh et al., 2009). Changes in the ANS (sympathovagal balance) can be monitored by

For examples, when an animal is attacked, its sympathetic nervous system spontaneously prepares for fight or flight by elevating the heart rate and increasing the blood pressure and body temperature. In contrast, when it is in a relaxed state, the parasympathetic nervous system is activated, and the opposite phenomena occur. Such processes are constantly in

Sympathovagal balance can be monitored by measuring variations in the heartbeat interval, and the degree of mental stress can be determined. This index is used for diagnosing psychological disorders and as well as the condition of circulatory organs. Moreover, many approaches for measuring the HRV are used in psychology (Vincent et al., 1996), occupational health (Miyake, 2001, Princi et al., 2005), and ergonomics research (Sirevaag et al., 1993, Gould et al., 2009). An estimation technique has been medically established. Thus, if electrocardiograms (ECG) can be replaced by a remote sensing method that allows simple and accurate monitoring in everyday life, mental stress can be assessed at any time and in

Fig. 1. Prototype chair equipped with a non-contact microwave radar system to monitor

mental stress in workers (Suzuki et al., 2008).

measuring the HRV. This variability is used as an index of mental stress.

equilibrium in daily life (Akselrod et al., 1981, Derrick,1988).

patients with infections.

**3.1 Measurement of ANS** 

any place.

Fig. 2. Sample data of a compact microwave radar output (A) showing a cyclic oscillation that corresponds to cardiac oscillations measured by ECG (B) (Suzuki et al., 2008).

Fig. 3. Example of remote sensing in health care. (A) In both non-contact and contact (ECG) measurements, the LF of a subject (reflecting sympathetic activation) exhibits a peak during audio stimulation. (B) Cross-correlation of the LF between non-contact and contact measurements of the same subject (Suzuki et al., 2008).

The prototype device in this example consists of a compact 24 GHz microwave Doppler radar (8 5 3 cm) attached to the back of a chair. The low-frequency/high-frequency (LF/HF) components of the HRV (which reflects the sympathovagal balance) of eight volunteers were determined by a prototype system using the maximum entropy method (MEM). The change in the LF and LF/HF components measured by a remote sensor was consistent with that measured by a contact electrocardiography sensor. It is very difficult to extract R-R intervals of heartbeats sufficiently accurately to calculate the HRV; this is thought to be because inaccuracies were introduced due to the microwave radar being susceptible to noise. However, measuring HRV by adopting MEM, which enables HRV to be estimated rapidly, stably, and accurately, was demonstrated to be successful for the first time.

Remote Sensing for Medical and Health Care Applications 487

Respiratory Signal

> Cardiac Signal

Fig. 4. Example of remote sensing using non-contact vital sign sensors to monitor a

The advantage of monitoring without direct touch and without removing clothing is useful and appealing in the medical field as it is not burdensome to patients and it can reduce the risk of secondary infection. There is also growing interest in the fields of health, life science,

In another trial, a new screening system was developed to conduct rapid screening (<5 s) of passengers who may have infectious diseases such as severe acute respiratory syndrome (SARS) or pandemic influenza at quarantine stations. This system enables medical inspection by measuring heart and respiratory rates, as well as body temperature by infrared thermography (Matsui et al., 2009, 2010). A similar system is already being tested at the quarantine station at Naha Airport for domestic flights and at Narita International Airport in Tokyo. The results demonstrate the efficacy of the concept and the system. The system even detected a patient with influenza whose fever was reduced by antifebrile medication. This finding is important as it demonstrates that the parameters

Microwave Doppler radar antenna in the ceiling attached

Microwave Doppler radar antenna

under the floor embedded

hibernating black bear at Ueno Zoo, Tokyo (Suzuki et al., 2009).

**3.3 Screening and medical examination of influenza patients** 

Night-vision camera

1.68m

and engineering.

A/D Board

TV monitor

Controller

PC/ Analyzing System

HDD2 HDD1

Network router

Backup

LAN

#### **3.2 Elderly care**

The next examples were monitoring of the elderly, infants and also animals using a microwave radar, especially focused respiratory monitoring (Li et al., 2009, Suzuki et al.,2009).

There is a real need to reduce the physical and mental work load of care workers and also to immediately detect sudden changes in the condition of a bedridden elderly person, both at home and in hospitals, because nighttime activity of persons with dementia increases the risk of injury and disrupts the sleep patterns of caregivers. Moreover, care of the elderly will increasingly be undertaken by family members at home as the population continues to age. Therefore, devices for long-term monitoring of the elderly that do not interfere with activities of daily life are required.

Various approaches have been proposed in recent years. Rowe (Rowe et al., 2009) proposed a night monitoring system that alerts caregivers when care recipients leave their beds and that tracks them as they move about the house during the night. In addition, another study compared the effects of a self-care and medication compliance device, which was linked to a web-based monitoring system, with the effects of conventional care alone on compliance with recommended self-care behavior (Artinian et al., 2003). Demiris (Demiris et al., 2009) investigated elderly behavior using a video and image processing system while carefully addressing privacy concerns. Another study proposed a non-restrictive, non-invasive vital sign measurement system for measuring heartbeat and respiration to monitor health status at home or in hospitals and nursing facilities (Tanaka et al., 2002). Systems for nursing care should meet the following requirements: (1) monitoring of activity and vital signs must not be a burden for the elderly; (2) accurately monitor changes in physical condition of the patient; and (3) when the physical condition of a patient rapidly changes, the system should promptly notify a doctor or nursing caregiver.

A prototype system using microwaves has been developed and has been applied for monitoring elderly in a nursing home. Although still a trial, the system can effectively perform real-time monitoring and it can acquire SAS respiratory data.

In addition, a baby also monitor using same technology has recently been demonstrated (Li et al., 2009). The baby monitor integrates a low-power Doppler radar that can detect minute movements induced by breathing. If no movement is detected within 20 s, an alarm goes off.

Using same type of sensing devices, respiratory activity of a hibernating black bear has been monitored at a Zoo (Suzuki et al., 2009). Ueno Zoological Gardens in Tokyo made plans to assist a Japanese black bear to enter hibernation, because the bear showed extremely slow movements in winter. Moreover, the staff wanted visitors to understand this instinctive behavior of bears as occurs in the wild. The bear's condition during hibernation must be carefully observed to avoid the risk of long-term fasting. Therefore, to observe the physiological condition of the bear during hibernation, about 3 months, a microwave radar system was set up in the hibernation booth. As a result, the respiratory rate decreased while the bear was entering hibernation, and became extremely low at approximately 2 bpm and showed almost no change. Additionally, a trend similar to a circadian rhythm in the changes of respiratory rate was observed.

The next examples were monitoring of the elderly, infants and also animals using a microwave radar, especially focused respiratory monitoring (Li et al., 2009, Suzuki et

There is a real need to reduce the physical and mental work load of care workers and also to immediately detect sudden changes in the condition of a bedridden elderly person, both at home and in hospitals, because nighttime activity of persons with dementia increases the risk of injury and disrupts the sleep patterns of caregivers. Moreover, care of the elderly will increasingly be undertaken by family members at home as the population continues to age. Therefore, devices for long-term monitoring of the elderly that do not interfere with

Various approaches have been proposed in recent years. Rowe (Rowe et al., 2009) proposed a night monitoring system that alerts caregivers when care recipients leave their beds and that tracks them as they move about the house during the night. In addition, another study compared the effects of a self-care and medication compliance device, which was linked to a web-based monitoring system, with the effects of conventional care alone on compliance with recommended self-care behavior (Artinian et al., 2003). Demiris (Demiris et al., 2009) investigated elderly behavior using a video and image processing system while carefully addressing privacy concerns. Another study proposed a non-restrictive, non-invasive vital sign measurement system for measuring heartbeat and respiration to monitor health status at home or in hospitals and nursing facilities (Tanaka et al., 2002). Systems for nursing care should meet the following requirements: (1) monitoring of activity and vital signs must not be a burden for the elderly; (2) accurately monitor changes in physical condition of the patient; and (3) when the physical condition of a patient rapidly changes, the system should

A prototype system using microwaves has been developed and has been applied for monitoring elderly in a nursing home. Although still a trial, the system can effectively

In addition, a baby also monitor using same technology has recently been demonstrated (Li et al., 2009). The baby monitor integrates a low-power Doppler radar that can detect minute movements induced by breathing. If no movement is detected within 20 s, an

Using same type of sensing devices, respiratory activity of a hibernating black bear has been monitored at a Zoo (Suzuki et al., 2009). Ueno Zoological Gardens in Tokyo made plans to assist a Japanese black bear to enter hibernation, because the bear showed extremely slow movements in winter. Moreover, the staff wanted visitors to understand this instinctive behavior of bears as occurs in the wild. The bear's condition during hibernation must be carefully observed to avoid the risk of long-term fasting. Therefore, to observe the physiological condition of the bear during hibernation, about 3 months, a microwave radar system was set up in the hibernation booth. As a result, the respiratory rate decreased while the bear was entering hibernation, and became extremely low at approximately 2 bpm and showed almost no change. Additionally, a trend similar to a circadian rhythm in the changes

perform real-time monitoring and it can acquire SAS respiratory data.

**3.2 Elderly care** 

activities of daily life are required.

promptly notify a doctor or nursing caregiver.

alarm goes off.

of respiratory rate was observed.

al.,2009).

Fig. 4. Example of remote sensing using non-contact vital sign sensors to monitor a hibernating black bear at Ueno Zoo, Tokyo (Suzuki et al., 2009).

#### **3.3 Screening and medical examination of influenza patients**

The advantage of monitoring without direct touch and without removing clothing is useful and appealing in the medical field as it is not burdensome to patients and it can reduce the risk of secondary infection. There is also growing interest in the fields of health, life science, and engineering.

In another trial, a new screening system was developed to conduct rapid screening (<5 s) of passengers who may have infectious diseases such as severe acute respiratory syndrome (SARS) or pandemic influenza at quarantine stations. This system enables medical inspection by measuring heart and respiratory rates, as well as body temperature by infrared thermography (Matsui et al., 2009, 2010). A similar system is already being tested at the quarantine station at Naha Airport for domestic flights and at Narita International Airport in Tokyo. The results demonstrate the efficacy of the concept and the system. The system even detected a patient with influenza whose fever was reduced by antifebrile medication. This finding is important as it demonstrates that the parameters

Remote Sensing for Medical and Health Care Applications 489

To use this technique in medical fields and daily life, aspects such as non-contact measurement and the non–removal of clothing need to be addressed. Data obtained by remote sensing must be more reliable and accurate than those measured by conventional electrode-based methods. Furthermore, a new index for diagnosing disease is required. Most studies of remote sensing using microwaves only measure the heart rate. However, the heart rate alone has limited diagnostic value; the heart rate only provides information about the tachycardia or bradycardia. It is hoped that such a system will be able to measure

In conclusion, research on remote sensing using microwaves is still in its infancy, but it appears promising not only for medical and health care, but also for other fields such as

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for monitoring cardiac and respiratory activity by microwaves are effective. In the future, remote sensing using microwaves is anticipated to attract more interest in the medical field.

Fig. 5. Example of remote sensing for medical diagnosis; non-contact monitoring for screening systems at airport quarantine stations (Matsui et al., 2009).

#### **4. Topics for future investigation**

Remote sensing of biomedical parameters has been described by focusing on monitoring using microwave radar and examples of medical and health care applications have been presented. Microwave-based remote sensing offers the following advantages: movement of an object can be detected from a distance, it means "remotely", and microwaves can pass through many materials (notable exceptions are metals and water). Thus, such systems will enable health care workers to measure motion of a body surface through clothing from a distance.

The most serious obstacle to practical applications of this technology is the need to reduce the effects of noise and artifacts. Vibrations on the body surface caused by heartbeat are quite small (with amplitudes of about 0.1–0.2 mm), whereas motions of arms and the abdomen are much larger. Additionally, movement of the person being monitored while conducting every day activities and data from other body motion will generate noise. The effect of multipass reflection should also be considered. One study performed simultaneous measurements of the vital signs of two people, but it is difficult to apply this technology to real-world applications.

To use this technique in medical fields and daily life, aspects such as non-contact measurement and the non–removal of clothing need to be addressed. Data obtained by remote sensing must be more reliable and accurate than those measured by conventional electrode-based methods. Furthermore, a new index for diagnosing disease is required. Most studies of remote sensing using microwaves only measure the heart rate. However, the heart rate alone has limited diagnostic value; the heart rate only provides information about the tachycardia or bradycardia. It is hoped that such a system will be able to measure parameters for diagnosing cardiovascular disease.

In conclusion, research on remote sensing using microwaves is still in its infancy, but it appears promising not only for medical and health care, but also for other fields such as ergonomics research.

#### **5. References**

488 Remote Sensing – Applications

for monitoring cardiac and respiratory activity by microwaves are effective. In the future, remote sensing using microwaves is anticipated to attract more interest in the medical

100cm

Fig. 5. Example of remote sensing for medical diagnosis; non-contact monitoring for

Remote sensing of biomedical parameters has been described by focusing on monitoring using microwave radar and examples of medical and health care applications have been presented. Microwave-based remote sensing offers the following advantages: movement of an object can be detected from a distance, it means "remotely", and microwaves can pass through many materials (notable exceptions are metals and water). Thus, such systems will enable health care workers to measure motion of a body surface through clothing from a

The most serious obstacle to practical applications of this technology is the need to reduce the effects of noise and artifacts. Vibrations on the body surface caused by heartbeat are quite small (with amplitudes of about 0.1–0.2 mm), whereas motions of arms and the abdomen are much larger. Additionally, movement of the person being monitored while conducting every day activities and data from other body motion will generate noise. The effect of multipass reflection should also be considered. One study performed simultaneous measurements of the vital signs of two people, but it is difficult to apply this technology to

screening systems at airport quarantine stations (Matsui et al., 2009).

10cm

Microwave radar

Microwave radar

for monitoring cardiac activity

Infrared thermograhy for measuring body temparature

for monitoring respiratory activity

200~ 300cm

30~ 40cm

**4. Topics for future investigation** 

distance.

real-world applications.

field.


Remote Sensing for Medical and Health Care Applications 491

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**22** 

*Canada* 

**Demonstration of Hyperspectral Image** 

Airborne hyperspectral imagers have been available from various providers for many years and their performance keeps improving. On the other hand, space-based hyperspectral sensors have only been available from few exploratory missions such as NASA Hyperion on EO-1 (Pearlman et al, 2003) and ESA CHRIS on Proba (Cutter et al, 2003). In recent years, there have been many civilian space missions being planned in different countries (Buckingham & Staenz, 2008), as well as military space demonstrations (Cooley et al, 2006). Given the increase in potential space-based hyperspectral sensors, Defence R&D Canada (DRDC), which is part of the Canadian department of National defence, began in 2005 a project to demonstrate the military utility of space-based reflective hyperspectral imagery (0.4-2.5 microns) to the Canadian Forces (CF). The project is called HYperspectral iMage

Before the HYMEX project, DRDC had been conducting and sponsoring R&D in the area of hyperspectral image exploitation for a number of years to explore its various possibilities (Davenport & Ressl, 1999; Sentlinger et al, 2003; Webster et al, 2006). The focus of this work was on military target detection applications. In parallel with these activities, the Canadian remote sensing community has also been active in developing hyperspectral applications for various civilian applications related to forestry, agriculture, fisheries, mineral exploration and environmental monitoring (Buckingham et al, 2002). Many hyperspectral techniques developed for civilian applications can be applied to military applications such as terrain

Building on previous efforts at DRDC and with support from Canadian industry, academic institutions and other government departments, the HYMEX project identified a set of

This chapter presents an overview of the project, beginning with a description of its main activities (Section 2.0), including field trials, data analysis and algorithms evaluation and the development of an image exploitation software. Then, for each application areas, target detection (Section 3.0), land mapping (Section 4.0) and marine mapping (Section 5.0), we

applications and related algorithms to be demonstrated to the Canadian Forces.

EXploitation (HYMEX) and ended its activities in 2010 (Ardouin et al, 2007).

**1. Introduction** 

characterization.

**Exploitation for Military Applications** 

Vincent Roy1, Yves Van Chestein1 and Anthony Faust2

Jean-Pierre Ardouin1, Josée Lévesque1,

*1Defence R&D Canada, Valcartier 2Defence R&D Canada, Suffield* 

of a subject in bed via a pneumatic method.IEEE Trans Biomed Eng, 52(12), pp.2100-2107.

Zhou, Q., Liu, J., Host-Madsen, A., Boric-Lubecke, O., Lubecke, V. (2006) Detection of multiple heartbeats using Doppler radar," IEEE ICASSP 2006 Proceedings, 2, pp.1160-1163.
