Earthquakes are lethal natural disasters frequently burying people alive under collapsed buildings. Tracking entrapped humans from their unique volatile chemical signature with hand-held devices would accelerate urban search and rescue (USaR) efforts. Here, a pilot study is presented with compact and orthogonal sensor arrays to detect the breath- and skin-emitted metabolic tracers acetone, ammonia, isoprene, CO2, and relative humidity (RH), all together serving as sign of life. It consists of three nanostructured metal-oxide sensors (Si-doped WO3, Si-doped MoO3, and Ti-doped ZnO), each specifically tailored at the nanoscale for highly sensitive and selective tracer detection along with commercial CO2 and humidity sensors. When tested on humans enclosed in plethysmography chambers to simulate entrapment, this sensor array rapidly detected sub-ppm acetone, ammonia, and isoprene concentrations with high accuracies (19, 21, and 3 ppb, respectively) and precision, unprecedented by portable sensors but required for USaR. These results were in good agreement (Pearson's correlation coefficients ≥0.9) with benchtop selective reagent ionization time-of-flight mass spectrometry (SRI-TOF-MS). As a result, an inexpensive sensor array is presented that can be integrated readily into hand-held or even drone-carried detectors for first responders to rapidly screen affected terrain.
Earthquakes are lethal natural disasters frequently burying people alive under collapsed buildings. Tracking entrapped humans from their unique volatile chemical signature with hand-held devices would accelerate urban search and rescue (USaR) efforts. Here, a pilot study is presented with compact and orthogonal sensor arrays to detect the breath- and skin-emitted metabolic tracers acetone, ammonia, isoprene, CO2, and relative humidity (RH), all together serving as sign of life. It consists of three nanostructured metal-oxide sensors (Si-doped WO3, Si-doped MoO3, and Ti-dopedZnO), each specifically tailored at the nanoscale for highly sensitive and selective tracer detection along with commercial CO2 and humidity sensors. When tested on humans enclosed in plethysmography chambers to simulate entrapment, this sensor array rapidly detected sub-ppm acetone, ammonia, and isoprene concentrations with high accuracies (19, 21, and 3 ppb, respectively) and precision, unprecedented by portable sensors but required for USaR. These results were in good agreement (Pearson's correlation coefficients ≥0.9) with benchtop selective reagent ionization time-of-flight mass spectrometry (SRI-TOF-MS). As a result, an inexpensive sensor array is presented that can be integrated readily into hand-held or even drone-carried detectors for first responders to rapidly screen affected terrain.
Recent major earthquakes in
Mexico (2017), Italy (2017), and Nepal (2015) with thousands of deaths
demonstrated once more the severe destructive potential of natural
disasters. Earthquakes caused more than 780 000 deaths in the
past decade, and alarmingly, the number of deaths may increase given
progressing urbanization and vulnerability of most populous cities
located on fault-lines (e.g., Tokyo, Los Angeles, or Delhi).[1] Following an earthquake, many victims are entrapped
under collapsed buildings and need rapid help, because survival rates
drop dramatically within the first hours.[2] Indispensable for urban search and rescue (USaR) are canines with
their superior ability to sniff entrapped humans from their scent.
However, their availability and operational time are limited and they
are rather stress-sensitive.[3] Nowadays,
specialized equipment (Table S1) is also
available to support USaR teams, but these rely mostly on optical
and acoustic probes.[4] As a result, they
might not be suitable for rapid sweeping of large areas, especially
at limited visible access or with unconscious victims unable to give
acoustic signs.Chemical recognition of the unique volatile
signature[5,6] of humans could improve USaR tools by adding
a “third sense”,
similar to the canines sophisticated nose. Particularly promising
to serve as sign of life is the combined detection of breath- and
skin-emitted metabolic tracers like acetone, ammonia, and isoprene
originating from lipolysis,[7] protein metabolism,[8] and cholesterol biosynthesis,[9] respectively. In fact, recent studies[10−13] demonstrated that these biomarkers
rapidly accumulate near entrapped humans. The employed SRI-TOF-MS[11] is highly sensitive, selective, fast, and can
detect a large range of volatile compounds; however, it lacks portability,
is expensive, and requires trained personnel. Therefore, it can hardly
be used as portable detector for widespread distribution to first
responders. Some other methods can be miniaturized to portable devices,
for instance, membrane inlet mass spectrometry (MIMS)[12] or gas chromatography coupled with ion mobility spectrometry
(GC-IMS),[10] as was reviewed recently.[6,14,15] Both feature fast response times
of few minutes (GC-IMS with rapid multicapillary columns[10]) and highly sensitive, selective, and simultaneous
detection of various tracers. However, GC-IMS has limited dynamic
range[13] and further miniaturization, power,
and cost reductions may be difficult due to indispensable auxiliary
systems.Sensor arrays can be extremely compact,[16] inexpensive[17] and
are used already as
portable devices for indoor air quality,[18] food spoilage monitoring,[19] or medical
breath analysis.[20] Even drones or land
robots could carry these arrays to rapidly screen affected areas too
dangerous for first responders. Current devices are typically based
on a set of highly and broadly sensitive (thus barely selective) chemical
sensors mimicking the mammalian olfactory system[21] (thus frequently called E-noses) to discriminate odors
or detect single tracers in simplified laboratory gas mixtures (e.g.,
formaldehyde[22]). However, E-noses lack
the accuracy and robustness to sense metabolic tracers at relevant
low ppb concentrations[5] in complex mixtures
impeding their application in entrapped human detection (>870 compounds
exhaled and >530 emitted through skin[23]). This is primarily due to the broadly sensitive and rather collinear
nature of the applied sensors leading to low discrimination power
and susceptibility to environmental confounders,[16] omnipresent in USaR areas (e.g., from fires, leaked chemicals,
etc.).Here, we present a sensor array based on distinctly selective
gas
sensors for rapid tracking of entrapped humans (Figure a). It consists of three previously developed
tailor-made gas sensors, Si-doped WO3, Si-doped MoO3, and Ti-dopedZnO, featuring high sensitivity and selectivity
to the metabolic tracers acetone,[24] ammonia,[25] and isoprene,[26] respectively
(Figure b). These
sensors consist of nanostructured, highly porous metal-oxide films
(Figure d,e) that
are chemoresistive (i.e., resistance modulated upon interaction with
the target analytes) and offer high surface area to detect tracers
even at the lowest ppb concentrations. In fact, their lower limits
of detection (LOD, at signal-to-noise ratio = 3) are 2.9, 50.7, and
0.7 ppb for acetone,[24] ammonia,[25] and isoprene[26] at
90% RH, respectively, comparable to GC-IMS (30 ppb for acetone[10]). Also relatively high analyte concentrations
can be detected, e.g., 500 ppm of ammonia with similar MoO3 sensors.[27] Such sensing films are obtained
by direct deposition of flame-made nanoparticles on substrates (Figure c) forming finely
structured sensing networks,[28] as shown
exemplarily for Ti-dopedZnO (Figure e). Combined with commercial CO2 and RH
sensors, they result in an array with nearly orthogonal sensing characteristics
enabling superior discrimination power to accurately detect the chemical
signature of humans.
Figure 1
Experimental setup: (a) skin- and breath-borne volatiles
of entrapped
volunteers accumulate in a plethysmographic chamber. (b) The sensor
array consists of three chemoresistive sensors, Si-doped MoO3, Si-doped WO3, and Ti-doped ZnO to monitor ammonia, acetone,
and isoprene, respectively, together with commercial humidity and
CO2 sensors. Simultaneous SRI-TOF-MS measurements were
used for cross-validation. (c) Image of a single sensor. (d) The sensing
elements consist of highly porous and semiconductive films formed
by direct flame deposition of agglomerated/aggregated metal-oxide
nanoparticles, as shown by (e) top-view scanning electron microscopy
exemplarily for Ti-doped ZnO.
Experimental setup: (a) skin- and breath-borne volatiles
of entrapped
volunteers accumulate in a plethysmographic chamber. (b) The sensor
array consists of three chemoresistive sensors, Si-doped MoO3, Si-doped WO3, and Ti-dopedZnO to monitor ammonia, acetone,
and isoprene, respectively, together with commercial humidity and
CO2 sensors. Simultaneous SRI-TOF-MS measurements were
used for cross-validation. (c) Image of a single sensor. (d) The sensing
elements consist of highly porous and semiconductive films formed
by direct flame deposition of agglomerated/aggregated metal-oxide
nanoparticles, as shown by (e) top-view scanning electron microscopy
exemplarily for Ti-dopedZnO.In principle, this array analyses gas mixtures (here, human
volatile
emissions) with each sensor individually and response times <3
min (Figure S1, inset). The generated signals
are processed with a statistical model[22] to estimate tracer concentrations by combinatorial selectivity[21] with enhanced accuracy compared to single sensors
(Figure ). For acetone,
ammonia, and isoprene, a multivariate linear regression (MVLR) model[29] is applied (please see Methods in the Supporting Information) matching the linear response
characteristics of these sensors at sub-ppm analyte concentrations.[24−26] Note that these become nonlinear at higher concentrations which
can be addressed in the model. To determine model coefficients, the
measured data were separated into a “training” and an
independent validation set.
Figure 2
Sensor array concept: Gas mixtures containing
the breath and skin
emitted tracers are analyzed by each sensor individually and their
signals are converted by a statistical model[22] to analyte concentrations. This model is initially “trained”
with data of four volunteers and tested on five volunteers.
Sensor array concept: Gas mixtures containing
the breath and skin
emitted tracers are analyzed by each sensor individually and their
signals are converted by a statistical model[22] to analyte concentrations. This model is initially “trained”
with data of four volunteers and tested on five volunteers.Next, we applied the sensor array
to monitor volatile compounds
related to human chemical signatures (or body odor). Therefore, nine
volunteers (Table S2 for physiological
data) were enclosed individually in a plethysmographic chamber to
mimic entrapment conditions.[11] The testing
course for each volunteer lasted 120 min, first with only skin (0–60
min) followed by breath and skin (60–120 min) emissions into
the chamber. These emissions are investigated separately to better
understand the release pathways of target tracers. Figure shows the corresponding sensor
array estimated acetone (a), ammonia (b), isoprene (c), RH (d), and
CO2 (e) concentration profiles of five volunteers (with
individual colors and symbols) when measured every 20 min. Note that
the data of the other four randomly selected volunteers were used
for “training” of the MVLR model to achieve minimal
estimation errors at the smallest sample size (please see Figure S2 for errors at other sample sizes and Figure S3a–c for concentration profiles
of all volunteers). The room air (background) concentration range
for each tracer are indicated in gray in Figure .
Figure 3
Sensor array measurements of acetone (a), ammonia
(b), isoprene
(c), RH (d), and CO2 (e) concentrations of five volunteers
as a function of entrapment time. Skin only (0–60 min) followed
by skin and breath (60–120 min) emissions were studied separately.
In the case of volunteer no. 4 (circles), skin (only) emissions lasted
accidentally for 80 min. Room air (background) concentrations are
indicated in gray.
Sensor array measurements of acetone (a), ammonia
(b), isoprene
(c), RH (d), and CO2 (e) concentrations of five volunteers
as a function of entrapment time. Skin only (0–60 min) followed
by skin and breath (60–120 min) emissions were studied separately.
In the case of volunteer no. 4 (circles), skin (only) emissions lasted
accidentally for 80 min. Room air (background) concentrations are
indicated in gray.In a typical case (e.g.,
volunteer no. 7, diamonds in Figure ), acetone, isoprene,
and CO2 change only little during skin emission (0–60
min) while they increase significantly when also exhaled (60–120
min), as detected by the sensor array and consistent with SRI-TOF-MS
(Figure S3d,f). As a result, these tracers
can indicate human presence (breath and skin emissions) rather early
as their concentrations rapidly exceed background levels. Furthermore,
the concentration slopes (and thus emission rates) among the volunteers
vary significantly, especially for acetone and isoprene when emitted
from breath and skin simultaneously (Figure a,c, t > 60 min). This
is
expected due to biological variations of breath acetone[30] and isoprene[31] that
are caused, for instance, by different metabolic states. For volunteer
no. 5 (Figure a, squares),
higher acetone emissions should indicate intensified ketogenesis,[7] reasonable after 8 h of fasting prior to the
experiment and a likely case for victims after prolonged entrapment.
In fact, previous breath studies on fasting subjects revealed increasing
acetone levels during exercise and rest indicating enhanced fat oxidation,
as confirmed by a blood assay.[20] Despite
these individual differences, acetone, isoprene and CO2 concentrations are distinguished clearly from the background (Figure , gray-shaded) for
all volunteers after 120 min of entrapment, so human presence in the
plethysmographic chamber is recognized unambiguously.Finally,
it is worth discussing volunteer no. 4 (Figure , circles) who removed by mistake
the mask outlet after 80 min (instead of 60 min), so his phase of
only skin emissions lasted longer. The sensor array “recognized”
the prolonged skin emissions correctly. In fact, the increase in acetone
and isoprene concentrations was delayed (Figure a,c), in excellent agreement with the SRI-TOF-MS
(Figure S3d,f). This shows nicely how the
sensor array can pick up individual tracer concentration profiles,
even when deviating from the measurement protocol.On the other
hand, ammonia and RH increase significantly during
skin emission and differ from the background even after short entrapment.
Later, both tend to level off and ammonia may even decrease in some
cases (e.g., volunteer no. 4 and 7), as confirmed by SRI-TOF-MS (Figure S3e). This may be related to absorption
of hydrophilic ammonia in water films. In fact, water condensation
on the colder chamber walls was apparent at high RH (>80%). Only
for
volunteer no. 2 (Figure b, triangles), ammonia levels increase steadily, consistent with
slower rising RH levels (Figure d) that might be associated with his skinny physique
(lowest weight at normal height, Table S2). Note that tracer concentrations may be altered also by construction
materials, such as alumina that retains hydrophilic molecules,[32] or other background effects (e.g., fire or garbage)
possibly present in USaR environments. Nevertheless, ammonia is still
a promising human tracer due to its high skin emission rate and thus
rapid accumulation in the vicinity of a person.To cross-validate
the sensor array’s accuracy, all measured
concentrations are compared to SRI-TOF-MS. Figure shows the scatter plots of acetone (a),
ammonia (b), and isoprene (c) as measured by the sensor array and
SRI-TOF-MS for the five volunteers (35 samples). Both methods correlate
strongly for all analytes (Pearson’s correlation coefficients
≥0.9, p < 0.05, Table S2 for each volunteer) with outstanding accuracy and precision
(Figure d). Specifically,
the accuracies are 19, 21, and 3 ppb for breath- and skin-emitted
acetone, ammonia, and isoprene, respectively (Figure d, filled squares). This is remarkable considering
on one hand the sensor array’s simple, inexpensive, and compact
design compared to SRI-TOF-MS and on the other hand, the complexity
of the analyzed gas mixture with strong variation of composition and
conditions (e.g., RH from 28 to 90% or temperature from 19.5 to 27
°C, Figure S4). Also, it is significantly
better (mean errors 4–28 times lower) than single sensors (compare Figure S5b to Figure d and note different ordinate scale) likely
due to the higher discrimination power through the nearly orthogonal
array design. This highlights the potential of sensor arrays to detect
breath- and skin-emitted tracer signatures, relevant for entrapped
human detection.
Figure 4
Scatter plots indicating correlations between sensor array
and
SRI-TOF-MS for acetone (a), ammonia (b), and isoprene (c) along with
their corresponding Pearson’s correlation coefficients (r) and coefficients of determination (R2). (d) Box-and-whisker plot of sensor array estimation
errors. Medians and means are shown as lines and squares, respectively.
The boxes represent the first and third quartiles and whiskers indicate
the full ranges.
Scatter plots indicating correlations between sensor array
and
SRI-TOF-MS for acetone (a), ammonia (b), and isoprene (c) along with
their corresponding Pearson’s correlation coefficients (r) and coefficients of determination (R2). (d) Box-and-whisker plot of sensor array estimation
errors. Medians and means are shown as lines and squares, respectively.
The boxes represent the first and third quartiles and whiskers indicate
the full ranges.Note that there is a
mismatch between sensor array and SRI-TOF-MS
for acetone (Figure a) below 150 ppb and isoprene (Figure c) below 10 ppb. These deviations occur during the
skin-emission phase (0–60 min) as the sensor array estimates
higher acetone (Figure a) and isoprene (Figure c) concentrations than SRI-TOF-MS (Figure S 3d,f). Errors may be caused by sensor cross-sensitivities
to other compounds, for instance, the more than 530 skin-emitted volatiles[23] where less acetone and isoprene are released.
Furthermore, disaster environments may contain high concentrations
of hydrogen and CO and even humans exhale them at concentrations of
several ppm.[33,34] However, their interference seems
not that significant, as indicated by the strong correlations between
sensor array and SRI-TOF-MS for the target tracers (Figure a–c) and individual
volunteers (Table S2). This is consistent
with single Si-doped MoO3[25] sensors
that had shown no response to CO.Reliable detection of entrapped
humans requires multitracer detection
since single compounds are affected too easily by other sources (e.g.,
ammonia by RH in Figure b or CO2 by fire). Consequently, all tracers need to be
evaluated simultaneously for recognition of patterns indicative of
human presence. Therefore, the results were visualized by normalizing
the analyte concentration in the chamber (cc) to its background (cb) and associating
a color code to their ratios (cc/cb). The color map in Figure shows the evolution of the five volunteers
(average cc/cb) during entrapment. Most importantly, all tracers (except for RH)
stand out from the background (cc/cb > 4) and develop a distinct pattern after
120 min corresponding to a short entrapment in a typical USaR mission.
This pattern seems quite characteristic for humans as can be seen
from the rather similar color maps of individual volunteers in Figure S6. As a result, the on-site detection
of target tracers could act as an early indication of human presence
under the ruins of collapsed buildings though further validation under
field conditions is needed. Note that other tracers could be included
to enhance robustness by introducing additional distinctly selective
sensors into the modular array design.
Figure 5
Color map indicating
human detection by their skin (0–60
min) followed by breath and skin (60–120 min) emissions. For
each analyte, a detection score (cc/cb) is calculated representing the ratio of average
concentration in the background (cb) and
chamber air (cc) in the presence of five
volunteers.
Color map indicating
human detection by their skin (0–60
min) followed by breath and skin (60–120 min) emissions. For
each analyte, a detection score (cc/cb) is calculated representing the ratio of average
concentration in the background (cb) and
chamber air (cc) in the presence of five
volunteers.In summary, a novel sensor
array has been developed for rapid detection
of entrapped humans from their volatile compound emissions. By choosing
tailor-made and nanostructured, chemoresistive gas sensors with distinct
selectivities, this array featured nearly orthogonal sensing characteristics
resulting in unprecedented sensitivity, discrimination power, and
robustness against other breath- and skin-emitted compounds. This
facilitated the accurate detection of breath- and skin-emitted acetone,
ammonia, and isoprene concentrations even at the lowest ppb levels,
as confirmed by a benchtop SRI-TOF-MS. This is superior to conventional
sensor arrays that detect only response patterns without identifying
analytes. When finally applied on entrapped volunteers, the detector
recognized human presence and even distinct behavior (volunteer no.
4) by multitracer assessment. This pilot study indicates that such
sensor arrays could be quite effective during real USaR and should
be tested in collaboration with first responders. Therein, positioning
of (single and multiple) entrapped humans, effects of physiological,
pathological, and other conditions (e.g., injuries, dehydration, asphyxiation,
shock, cosmetics) and false positive alarms from external confounders
(e.g., leaked chemicals or fire) need to be considered. Finally, this
sensor array featured a compact size to be incorporated easily into
hand-held or even drone-carried detectors.
Authors: Patrik Spaněl; Kseniya Dryahina; Alžběta Rejšková; Thomas W E Chippendale; David Smith Journal: Physiol Meas Date: 2011-07-01 Impact factor: 2.833
Authors: J King; A Kupferthaler; K Unterkofler; H Koc; S Teschl; G Teschl; W Miekisch; J Schubert; H Hinterhuber; A Amann Journal: J Breath Res Date: 2009-06-09 Impact factor: 3.262
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Authors: Andreas T Güntner; Julia F Kompalla; Henning Landis; S Jonathan Theodore; Bettina Geidl; Noriane A Sievi; Malcolm Kohler; Sotiris E Pratsinis; Philipp A Gerber Journal: Sensors (Basel) Date: 2018-10-28 Impact factor: 3.576