Recent progress in the design and clinical development of electronic-nose technologies

Figures & data

Table 1 Electronic-nose device types, sensor characteristics, detection mechanisms, advantages, and disadvantages

E-nose type	Sensor sensitivity	Sensitive component	Detection mechanism	Response times (seconds)	Advantages	Disadvantages	References
Calori metric	10–100 ppm	Pellistor, catalytic	Temperature or	2–10	High specificity for oxidized	High temperature operation, only sensitive	12,13
(catalytic bead)		bead	heat change		compounds, low cost, sensor stability	to oxygen–containing compounds, risk of catalyst poisoning
Carbon nanofiber	<~20 ppm	Graphene nanotubes with various coatings	Electrical resistance change	2–4	Good absorptive capacity, large surface area–to–volume ratio	Fabrication and manufacturing difficulties, high cost, low precision	14–17
Conducting	0.1–100 ppm	Doped aromatic	Electrical resistance	10–90	Ambient temperature,	Sensitive to humidity and temperature,	18–21
polymer		polymers	change		inexpensive	sensor life limited by oxidation
Metal oxide	5–500 ppm	Inorganic metal	Electrical resistance	5–35	Low cost, moderate sensitivity,	High temperature operation and power	22–24
semiconductors		oxides	change		rapid sensor recovery, long sensor life	consumption, sensitive to humidity
Optical	<~10 ppb	Photodiode	Optical changes	<10	Very high sensitivity, capable of identifying individual compounds in mixtures, long sensor life, insensitive to environment	Very complex, high cost, expensive to operate, low portability (due to difficulty of miniaturization)	25–27
Quartz crystal micro balance	1 ng	Organic or inorganic films	Mass change (frequency shift)	~10	Very high sensitivity, good precision, diverse sensor range	Complex circuitry, poor signal–to–noise ratio, sensitive to humidity and temperature	28–31
Surface acoustic wave	1 Pg	Organic or inorganic films	Mass change (frequency shift)	~10	Ultrahigh sensitivity, wide range of gases detected	Complex circuitry, temperature sensitive (unstable at high temperatures)	32–34

Table 2 Recent applications of electronic-nose devices in clinical practice

Applications	Organ system	Detection	E-nose model system	Sensor type and number	References
Disease diagnosis	Blood	Pathogen (Salmonella)	DR-ADF SiO2-TiO2 biosensor	MOS-BS	37
	Blood	Malaria	Experimental CNF on NMBs	CNF-BS	38
	Breast	Cancer	BreathLink (GC + SAW)	SAW 1	39
	Colon	Cancer	Cyranose 320	CP 32	40
	Foot	Microbial infections	Cyranose 320	CP 32	41
	Lung	Cancer	Many types: gold nanoparticles, CP, MOS, SAW	Various	42
	Lung	Asthma, CF, COPD, TB	Bloodhound 114 Cyranose 320 MOSES II e-nose	CP I4 CP 32 MOS 8, QMB 8	43
	Ovaries	Cancer	SnO2, TiO2 Figaro TGS2600-series	MOS 16	44
	Prostate	Cancer	ChemPro 100i	IMS 1	45
	Upper airway	OSAS	Cyranose 320	CP 32	46
	Urinary	Pathogens	IMS Cell-e-nose	IMS 8, MOS 6	47
Drug use	Mouth	Alcohol (ethanol)	Experimental SnO2/ZnO core-shell nanorods	MOS	48
	Skin	Marijuana (Cannabis)	Experimental SnO2	MOS 3	49
Hazardous gas	Lungs	CO, no2, nh3, so2	In2O3−, SnO2−, CNT-based FETs	FET	50
exposure
Organ failure	Kidney	Ammonia breath analysis	TGS 2602	MOS I	51
Patient ID	Body	Human odors	Experimental TGS (Tagushi) e-nose	MOS 5	52
Physiological	Body fluids	Health parameters	CardioMEMS, others	MEMs	53
		Antioxidant capacity	TGS 2602 EC biosensor	ECB	54
		Urea buildup	Silica-gel SiO2NPs biosensor	SG-BS	55
Toxin exposure	Body fluids	Mercury poisoning	Experimental ISE	EC	56

Abbreviations: BS, biosensor (experimental technology); CF, cystic fibrosis; CNF, carbon nanofiber; CNT, carbon nanotube; COPD, chronic obstructive pulmonary disease; CP, conducting polymer; EC, electrochemical; ECB, electrochemical biosensor; FETs, field-effect transistors; GC, gas chromatography; IMS, ion mobility spectrometry; ISEs, ion-selective electrodes; MEMs, microelectromechanical systems; MOS, metal oxide semiconductor; NMB, carbon nanofiber forests grown on glass microballoons; OSAS, obstructive sleep apnea syndrome; QMB, quartz microbalance; SAW, surface acoustic wave; SG-BS, silica gel biosensor; TB, tuberculosis; ID, identification; e-nose, electronic-nose.

Table 3 Research studies utilizing electronic-nose instruments to detect human diseases via biomarkers in the human breath

Diseases	Location	N	Research hospital or clinic location	Sensor type and number	Reference
ARDS-MPM	Lung	78	St vincent and Prince of wales Hospital, Sydney, Australia	CP 32	59
Asthma	Lung	40	Leiden University MC, Leiden, the Netherlands	CP 32	60
		51	Instituto Dermopatico deli’ immacolata, Rome, italy	QMB 8	61
Asthma-COPD	Lung	90	Academic MC Amsterdam, Haga Teaching Hospital, The Hague; Albert Schweitzer Hospital, Dordrecht, the Netherlands	CP 32	62
		100	Academic MC Amsterdam, Haga Teaching Hospital, The Hague; Albert Schweitzer Hospital, Dordrecht, the Netherlands	CP 32	63
		44	University of New South Wales, Sydney, Australia	CP 32	64
Cancer	Lung	62	C. Forlanini Hospital, Rome, italy	QMB 8	65
		135	Cleveland Clinic, Ohio, USA	CP 32	66
		143	Cleveland Clinic, Ohio, USA	CM 36	67
		92	C. Forlanini Hospital, Rome, italy	QMB 8	68
		229	Cleveland Clinic, Ohio, USA	CM 36	69
COPD	Lung	43	Phillips University, Marburg, Germany	CP 32	70
COPD-cancer	Lung	30	Leiden University MC, Leiden, the Netherlands	CP 32	71
Endocarditis (infective)	Heart	78	Osaka University, Osaka, Japan	MOS 6	72
iPA	Lung	53	University of Amsterdam, Amsterdam, the Netherlands	CP 32	73
MPM	Lung	39	University of Bari Aldo Moro, Bari, italy	CP 32	74
Pneumonia	Lung	400	Department of Anesthesia, University of Pennsylvania, Philadelphia, PA, USA	BS	75
TB	Lung	46	Cranfield University, Silsoe, Bedfordshire, UK	CP 14	76
		134	Cranfield University, Silsoe, Bedfordshire, UK	CP 14	77
		279	University of Santo Tomas, Manila, Philippines;
			De La Salle University Hospital, Cavite, Philippines; Homerton University Hospital, London, UK; Hinduja Hospital, Mumbai, india	SAW 1	78
URTI	Respiratory tract	NS	University of Pennsylvania Medical Center, Philadelphia, PA, USA	CP 32	79
VAP	Lung	25	University of Pennsylvania, Philadelphia, PA, USA	CP 32	80
		38	University of Pennsylvania, Philadelphia, PA, USA	CP 32	75
		44	University of Pennsylvania, Philadelphia, PA, USA	CP 32	81

Note: Adapted from Wilson AD. Advances in electronic-nose technologies for the detection of volatile biomarker metabolites in the human breath. Metabolites. 2015;5: 140–163,³⁵ originally published in the MDPI open access journal Metabolites.

Abbreviations: MC, Medical Center; ARDS, acute respiratory distress syndrome; COPD, chronic obstructive pulmonary disease; IPA, invasive pulmonary aspergillosis; MPM, malignant pleural mesothelioma; TB, tuberculosis; URTI, upper respiratory tract infections; VAP, ventilator-associated pneumonia; NS, not specified; BS, biosensor (experimental technology); CM, calorimetric; CP, conducting polymer; MOS, metal oxide semiconductor; QMB, quartz microbalance; SAW, surface acoustic wave.