WO2018096335A1

WO2018096335A1 - Apparatus comprising a nasal airflow sensing device and a computing system

Info

Publication number: WO2018096335A1
Application number: PCT/GB2017/053522
Authority: WO
Inventors: Terence Leung; Peter Andrews; Chia-Hung Li; Stephen Hope; Ian Mccutcheon
Original assignee: UCL Business Ltd
Current assignee: UCL Business Ltd
Priority date: 2016-11-24
Filing date: 2017-11-23
Publication date: 2018-05-31
Anticipated expiration: 2019-05-24
Also published as: GB201908932D0; GB2571882A; GB201619854D0

Abstract

Apparatus comprising: a nasal airflow sensing device comprising a first acoustic sensor and a second acoustic sensor configured to be fixed on opposing sides of a nose of an upright patient to acquire first and second acoustic signals respectively for acoustically monitoring airflow through the nose, the first and second acoustic sensors being configured to be fixed on opposing sides of the exterior of the nose so as not to interfere with the airflow through the nose of the patient, wherein the first acoustic signal is indicative of the airflow through the nasal cavity on the side of the nose to which the first acoustic sensor is fixed, the second acoustic signal is indicative of the airflow through the nasal cavity on the side of the nose to which the second acoustic sensor is fixed, and the first and second acoustic sensors pick up their respective acoustic signals from airflow through their respective nasal cavities with little or no cross-talk from the airflow through the other nasal cavity; and a computing system having a data link with the device for receiving and analysing the first and second acoustic signals, wherein the computing system is configured to analyse the first and second acoustic signals in the time domain to derive one or more parameters indicative of a condition of the nasal cavities.

Description

APPARATUS COMPRISING A NASAL AIRFLOW SENSING DEVICE AND A COMPUTING

SYSTEM

Field

The present invention relates to investigating the condition of the nasal cavities by acoustic sensing of nasal airflow during breathing, for example, to detect blockages or obstructions in the nasal cavities.

Background

The human nose is a major part of the human respiration system and is formed of an outer covering of skin (supported by bone and cartilage) defining two internal nasal cavities having openings (nostrils) exposed to the outer environment. The cavities are disposed to the left and right of the nasal septum, which forms a midline partition that defines two distinct cavities, left and right. During respiration, air enters and exits the human body through the nose upon inspiration/inhalation and expiration/exhalation respectively. The nasal cavities can be considered as extending upwards from the nostrils to the top of the nasal septum, where the left and right cavities then join together to form a single chamber.

Nasal blockage is one of the most common complaints encountered in ear, nose, throat (ENT) departments and also in general practice. Nasal blockages/obstructions can be broadly divided into two types: physiological or anatomical [1 ]. Assessment of nasal obstruction involves identifying the type of obstruction, which can lead to a decision on whether to administer a medical or surgical treatment; such an assessment can also be performed during and/or after administering medication or other treatment, in order to assess the progress of a patient.

Examples of potential treatments for nasal blockage include utilising a decongestant to improve the nasal airflow if an obstruction is caused by inflammatory responses [2]. Similarly, rhinitis which is an inflammation of the linings of the nasal cavities [3], or sinusitis, which is an inflammation of the sinuses [4], can both be treated using corticosteroids [5, 6]. If an obstruction persists after decongestant, this may indicate an anatomical obstruction, whereby surgical interventions may be required to alleviate the symptoms [1 ], e.g., though septorhinoplasty [7]. In addition, medication to reduce inflammation may not be effective, thus leading to possible surgical intervention; for example, functional endoscopic sinus surgery (FESS) can open up the ostia to treat sinusitis [8]. Anatomical conditions such as internal and external valve collapse (INVC and ENVC) or septal perforation may also require surgical intervention to correct the condition, e.g., by closing the septal perforation. Nasal polyps are another example of a cause of nasal blockage/obstruction which can be treated by medication

(e.g. steroids) or by surgical intervention if the former fails [9].

Currently many rhinologists use mainly subjective methods to qualitatively assess nasal blockage in their patients; this may then form the basis of their diagnosis and recommendations for appropriate treatments. In addition, questionnaire-based tests such as the Visual Analogue

Scale (VAS), which requires a patient to rank subjective feelings of various nasal related symptoms (e.g., blockage, pain, sense of smell, etc.) [10], are commonly used by rhinologists.

Other questionnaire based tests, such as the Nasal Obstruction Symptom Evaluation (NOSE)

[1 1 ] and the Sino-Nasal Outcome Test-22 (SNOT-22) or variations thereof [12, 13], are also used. These tests have been validated for use in planning or authorising certain subsequent procedures [10, 14-18].

Other methods may include physical examination using a speculum or endoscope or obtaining nasal misting patterns (also known as a misting test). The latter involves a patient exhaling onto a metal or similar surface to produce patterns of condensed water vapour from each nostril. Visual assessment is performed on the patterns to identify differences between nostrils. However, the misting test has been found to not correlate well with questionnaire based tests and its utility is considered limited, despite efforts to quantify the test [19-21 ].

With evidence-based medicine being the gold standard in the profession, there is a growing need for the use of more objective methods to quantify the nature and extent of nasal blockage [1 ]. Such objective (and quantitative) evidence is valuable (inter alia) for demonstrating the effectiveness of interventions, commissioning services, and also patient education [22].

There are a few existing nasal airflow assessment devices that provide objective measurements, including peak nasal inspiratory flow (PNIF) metering, acoustic rhinometry (AR) and rhinomanometry (RMM) which are considered to be well established in clinical settings. PNIF (sometimes referred to as nasal inspiratory peak flow, NIPF) measures the airflow rate during maximum nasal inhalation [23]. Normal and obstructive noses are distinguished based upon a threshold value; however, there have been reports that these results have only weak (or no) correlation with subjective questionnaire based tests [22, 24, 25]. In addition, the reliability of the test is dependent upon the patient's physical effort when inhaling, which of course can vary from breath to breath, as well as depending on the general health of the patient. AR involves sending acoustic pulses into the nasal cavity and measuring reflected pulses. This can then be used to provide a graph of the variation of the cross-sectional area of the nasal cavity with distance from the opening of the nose [2]. However, this test only analyses the structure of the nasal cavity and does not consider nasal function, because the patient does not breathe during the test [26]. Rhinomanometry (RMM) usually involves breathing into a face mask, typically while one nostril is blocked. This technique can be used to measure nasal airflow resistance (NAR) and healthy and obstructed noses are distinguished based on a cut-off threshold [27]. Other techniques such as nasal spirometry (or rhinospirometry) and nasal breathing sound (which involves placing a microphone under one nostril while the other is blocked) have also, less commonly, been used for nasal measurements, but mainly for research purpose.

In general, the above mentioned objective measurement techniques do not correlate strongly with the subjective tests. As the subjective tests are currently the most commonly used method of assessment, objective techniques that cannot provide a reliable assessment of nasal conditions will likely not be preferred by medical practitioners. Equally, patients may dispute the results of such measurements because the patients may give more weight to their own personal experience/feelings of the condition, rather than to such measurements, especially if the objectively measured data does not accurately reflect to the patient's own direct experience.

In addition, the current tests do not permit a patient to breathe normally during the assessment, for example, by requiring a patient to maximally exhale as in PNIF, or by inserting probes into the nasal cavity or in proximity of the nostril as in RMM and AR, which then alters the aerodynamics inside the nose considerably. These tests therefore may not fully reflect the nasal condition during normal breathing, and so may potentially lead to a misdiagnosis. Summary

The invention is defined by the appended claims.

One implementation provides an apparatus comprising: a nasal airflow sensing device comprising a first acoustic sensor and a second acoustic sensor configured to be fixed on opposing sides of a nose of an upright patient to acquire first and second acoustic signals respectively for acoustically monitoring airflow through the nose. The first and second acoustic sensors are configured to be fixed on opposing sides of the exterior of the nose so as not to interfere with the airflow through the nose of the patient, wherein the first acoustic signal is indicative of the airflow through the nasal cavity on the side of the nose to which the first acoustic sensor is fixed, the second acoustic signal is indicative of the airflow through the nasal cavity on the side of the nose to which the second acoustic sensor is fixed. The first and second acoustic sensors pick up their respective acoustic signals from airflow through their respective nasal cavities with little or no cross-talk from the airflow through the other nasal cavity. The apparatus further comprises a computing system having a data link with the device for receiving and analysing the first and second acoustic signals, wherein the computing system is configured to analyse the first and second acoustic signals in the time domain to derive one or more parameters indicative of a condition of the nasal cavities, e.g. whether normal or obstructed.

The present approach allows acoustic signals indicating airflow of the left and right nasal cavities to be obtained independently (and simultaneously). These signals may help a medical practitioner to identify, quantitatively, airflow differences between the nasal cavities, as well as characteristics of the airflow within each nasal cavity. Obstructions or anatomical conditions affecting the nose of the patient may be determined through such an analysis, wherein certain obstructions/anatomical conditions have certain recognisable acoustic signatures (or patterns) within the acoustic signals. Parameters can also be calculated and compared to provide quantitative evidence of the blockage/anatomical condition.

Also provided is a nasal airflow sensing device comprising a first acoustic sensor and a second acoustic sensor configured to be fixed on opposing sides of a nose of an upright patient to acquire first and second acoustic signals respectively for acoustically monitoring airflow through the nose.

Also provided is an apparatus for analysing measurements of nasal airflow, the apparatus comprising: means for acquiring first and second acoustic signals from first and second acoustic sensors respectively for acoustically monitoring airflow through respective sides of a nose without interfering with said airflow; and means for analysing the first and second acoustic signals in the computer system based on previous data acquired from patients with known nasal conditions.

As described herein, acoustic sensors may be placed on the external surface of the side of the nose; breathing sounds from both nostrils are measured separately by the respective sensors (but normally simultaneously for the two nostrils); and the measurement signals are then analysed to identify sound features which clinicians may use to diagnose a specific nasal pathology, such as chronic rhino sinusitis.

Brief Description of the Drawings

The invention is now described by way of example only with reference to the following drawings in which:

Figure 1A schematically represents in plan view a nasal sensing device for sensing acoustic signals of airflow in the right and left nasal cavities in accordance with some embodiments of the invention;

Figure 1 B schematically represents the nasal sensing device of Figure 1 A in cross section; Figure 2 schematically represents a nasal sensing system comprising the device of Figures 1 A and 1 B and further including a computer for performing analysis on the acoustic signals obtained from the device;

Figure 2A schematically shows a user wearing a nasal sensing device such as depicted in Figures 1A and 1 B;

Figure 3 schematically represents an example acoustic signal, shown in amplitude vs. time representation, obtained from a single acoustic sensor corresponding to the airflow through the left side nasal cavity of a (generally) healthy patient;

Figure 4A schematically represents example acoustic signals, shown in amplitude vs. time representation, obtained from left and right acoustic sensors respectively corresponding to the airflow through the left and right nasal cavities of the same patient as Figure 3;

Figure 4B schematically represents example acoustic signals, shown in amplitude vs. time representation, obtained from left and right acoustic sensors respectively corresponding to the airflow through the left and right nasal cavities of a patient suffering from right septal deviation respectively;

Figure 4C schematically represents example acoustic signals, shown in amplitude vs. time representation, obtained from left and right acoustic sensors respectively corresponding to the airflow through the left and right nasal cavities of a patient suffering from septal perforation respectively;

Figure 5A schematically represents, in an upper part, example acoustic signals, shown in amplitude vs. time representation, obtained from left and right acoustic sensors respectively corresponding to the airflow through the left and right nasal cavities of a patient suffering from external nasal valve collapse respectively and, in a lower part, spectrograms showing the frequency components of the respective left and right acoustic signals as a function of time;

Figure 5B schematically represents the spectrogram of the right acoustic signal in Figure

5A in a different colour scale;

Figure 6A schematically represents in plan view a nasal sensing device for sensing acoustic signals of airflow in the right and left nasal cavities individually in accordance some embodiments of the invention;

Figure 6B schematically represents the nasal sensing device of Figure 6A in cross section; and

Figure 7 schematically represents in plan view a nasal sensing device for sensing acoustic signals of airflow in the right and left nasal cavities individually in accordance with some embodiments of the invention.

Detailed Description Aspects and features of certain examples and embodiments of the present invention are described herein. Some aspects and features of certain examples and embodiments may be implemented conventionally and these are not described in detail in the interests of brevity. It will thus be appreciated that aspects and features of apparatus and methods discussed herein which are not described in detail may be implemented in accordance with any conventional techniques for implementing such aspects and features.

Figures 1A and 1 B show a schematic example of a nasal airflow sensing device 10 in accordance with some embodiments. This device can be used to measure the sound of a user breathing through the nose. Figure 1A shows the nasal airflow sensing device 10 in plan view as taken along line A-A in Figure 1 B, while Figure 1 B shows the nasal airflow sensing device 10 in cross-sectional view taken along line B-B in Figure 1A. The nasal airflow sensing device 10 can be considered as a strip which is designed to adhere across the bridge to provide acoustic monitoring of each nasal cavity (the portion of the strip denoted by dotted line M would typically lie across the bridge of the nose).

The nasal airflow sensing device 10 as shown in Figures 1A and 1 B comprises a right acoustic sensor 12R, a left acoustic sensor 12L, and a processing and transmission element 14 mounted on/in a flexible substrate 16. (The indication of left and right for the acoustic sensors 12L and 12R is intended to indicate the nasal cavity on which they are placed). The substrate 16 is formed of two layers, 16a and 16b, which together enclose and protect the acoustic sensor in a laminated arrangement. An adhesive layer 18 is provided on the underside of the substrate 16 for attaching the device 10 to the skin of a patient, specifically on the outer surface of the patient's nose. By way of example only, the device 10 may be about 4cm in length (i.e., left to right in Figure 1A), about 1 cm wide, and 1 -5 mm thick, however, this is only indicate, and other dimensions may be used as appropriate. It should also be understood that different sizes of the device may be utilised for different sized noses (children, adults, etc).

The adhesive layer 18 is formed from a dermatologically safe adhesive. In one implementation, adhesive layer 18 is formed from a double-sided tape having adhesive disposed both on the side facing the support layer 16a and also on the side facing towards the patient. A removable film (not shown) may be provided on the side of the adhesive layer 18 intended for contact with the patient's skin to protect the adhesive layer 18 until such a time as the device 10 is to be attached to the patient, at which point the removable film is removed. Generally speaking, the substrate 16 when attached to the patient's nose is aligned such that the right acoustic sensor 12R is positioned on the right hand side of the patient's nose, while the left acoustic sensor 12L is correspondingly positioned on the left hand side of the patient's nose. The physical position of the substrate 16 in relation to the height direction of the nose may be varied based on factors such as good acoustic coupling, good adherence to the skin, comport, etc. Note that the acoustic sensors are generally located away from the bridge of the nose, i.e. rather on the side walls of noise. This helps to ensure that each acoustic sensor picks up sound from its respective nasal cavity, however, there is little or no cross-talk, i.e. the left acoustic sensor does not pick up sound from the right nasal cavity, and vice versa. Although complete separation of the two channels is not possible, in practice the level of any cross-talk can be reduced to an acceptably low level, e.g. 20dB, preferably 30dB, preferably 40dB, preferably 50dB..

The acoustic sensors 12L and 12R in some implementations are piezoelectric film sensors. For example, the sensors 12L and 12R comprise polyvinylidene fluoride (PVDF) film sensors having a thickness of around ten to a few hundred microns, e.g., between 10 to 300 μηι, although other thicknesses are possible. However, any other suitable sensors may be used, e.g., condenser microphones, etc. The acoustic sensors 12L, 12R are configured to acoustically monitor/sense airflow within the nasal cavities by converting sound vibrations caused by airflow through the nasal cavities during breathing to electrical signals capable of being analysed, e.g., by a computer or data analysis software.

The processing and transmission element 14 provides processing and communications functionality for the device 10, for example receiving control commands from an external device, e.g. a personal computer, and/or for off-loading data to such an external device. More particularly, the processing and transmission element 14 has electrical connections (not shown) to the acoustic sensors 12L and 12R. The processing and transmission element 14 processes the acoustic signals received from the sensors for communication to an external device, which can be used as appropriate for analysis and display of the results. Such communication may be performed by a wired (e.g. USB) or wireless (e.g. Bluetooth or NFC) communications link. The processing and transmission element 14 may include memory for storing and/or buffering the received signals prior to transmission to the external device. Such a memory may be particularly useful if the device 10 is to be worn for an extended period (during which period, it may not maintain connectivity with a suitable external device. Although the processing and transmission element 14 is shown in Figures 1A and 1 B as an integral part of the device 10, i.e. included in the strip that is placed over the nose, in other implementations the processing and transmission device may be physically located outside the device, for example, in a separate wearable module worn around the neck or on the ear. This module would then have appropriate linkage - e.g. signal and, at least in some cases, power connections - to the acoustic sensors 12L and 12R.

In some cases, the device 10 may receive power over an external wired link, e.g. over a USB connection. In other cases, the device 10 may incorporated a small battery (not shown in the Figures). Another possibility is that the device 10 receives power from a separate battery pack, which is worn or held by the user.

Figure 2 shows a schematic functional-block representation of the overall system in accordance with some embodiments. This system includes left and right acoustic channels, each channel comprising a respective acoustic sensor, pre-amplifier, and filter. In particular, the right channel includes sensor 12R, pre-amp 20R and filter 22R, while left channel includes sensor 12L, pre-amp 20L and filter 22L. The system of Figure 2 further includes an analog-to- digital converter (ADC) 24 and a communication coupling 26, in this case a USB cable to a computer 28 running suitable data analysis software 30.

The signals from the acoustic sensors 12L, 12R are therefore amplified by corresponding pre-amplifiers 20L, 20R, and are then pass to corresponding filters 22L, 22R. These filters act as band pass filters, attenuating frequencies below a lower cut-off threshold, for example, 100Hz and attenuating frequencies above an upper cut-off threshold, for example, 10,000Hz or 20,000Hz (although other types of filter with different cut-off thresholds may be employed as appropriate in other implementations). The stop-band level (i.e. the signal rejection outside the pass-band) may be around -60dB but again although other values may be employed.

Once the acoustic signals have amplified and filtered to remove low frequency noise, they are passed to the ADC 24. In some embodiments, the ADC 24 is a two-channel ADC for separately converting each signal from the respective acoustic sensors. The ADC 24 converts the analogue signal to a digital signal for processing using conventional techniques, for example, using a sampling frequency of 44.1 kHz with 16 bits per sample (the same as for conventional CDs). It will be appreciated however that other devices may utilise different sampling schemes/rates, etc.

The converted digital signals are transferred from to the computer 28 via a USB cable

26. The USB cable 26 may be plugged into a USB socket on the device 10 itself, and correspondingly linked to the computer 28. Note that computer 28 may comprise any suitable system, e.g. a personal computer, server, a laptop, notebook, smartphone, tablet, smart watch etc. The data analysis software 30 may then be used to analyse the received digital signals as described in more below. The software 30 and computer 28 may also be used to display the digital signals such as each acoustic sensor as a function of time, any parameters derived from the acoustic signals, and/or an indication of a blockage or anatomical condition related to the specific acoustic signal or calculated parameters. Note that the computer 28 may not necessarily use its own display and may alternatively communicate with another display or monitor, e.g., a smart TV or other display device, to present the acoustic signals or parameters derived therefrom. The data analysis software 30 may also allow user input, e.g., from a medical practitioner, to alter the display of any of the above as desired, e.g., by changing the scale of any displayed graphs, by changing the colour scheme to help identify hidden features, etc. In addition, the medical practitioner might also utilise input to the software 30 (or some other software) for controlling the device 10, for example, by adjusting sensitivity, by programming a certain signal acquisition period, and so on.

The ADC 24 and USB link of Figure 2 will may be incorporated into the processing and transmission element 14 of Figures 1A and 1 B. The filters 22L, 22R may also be located in the processing and transmission element 14, as may be the pre-amplifiers 20L, 20R. Alternatively, at least the pre-amplifiers 20L, 20R, and optionally the filters 22L, 22R, may be located close to the sensors 12L, 12R (or may be integrated into the sensors). In some cases the filters may be omitted, with digital filtering being performed later, e.g. on computer 28.

It will be appreciated that the physical and electrical implementations shown in Figures 1A, 1 B and 2 are merely examples, and many variations will be apparent to the skilled person. For example, for device 10, the acoustic sensors might make direct contact with the skin to provide a strong acoustic coupling, while there may be acoustic shielding to prevent noise contamination from the environment (or from the other nostril). (It will be appreciated that many environmental noises may be picked up in both channels, which can then provide a mechanism for rejecting such noises, either electronically or computationally).

In many cases, the device 10 will acquire the two acoustic signals for each respective nasal passage simultaneously. This approach can be helpful for rejecting external background noise (common mode rejection), and also for looking for any difference between the acoustic signals for the two different nasal passages - which may be indicative of some anomalous condition in one of the nasal passages.

In some implementations, the device 10 may not be provided with any mechanism for fastening to the nose, rather such fastening is achieved by using separate tape or plasters (such as might commonly be used, for example, for attaching ECG monitors to the skin). A further possibility is to retain the acoustic sensors (and device 10) in position using a strap that goes round the back of the head. Alternatively, the acoustic sensors might be provided on a spectacles-like frame that rests on the nose. In some implementations, additional acoustic sensors may also be provided in other locations, such as immediately below the nose, close to the respective nostrils (this latter positioning has the advantage of receiving additional sound directly from the airflow rather than through the skin of the nose).

In general, the device 10 offers a non-intrusive way of obtaining the acoustic signals by placing the left and right acoustic sensors 12L, 12R at positions adjacent to the nasal cavities but on the outside (outer surface) of the nose, in contrast to certain known methods, such as RMM or AR. Accordingly, the patient's breathing can be performed normally to obtain the acoustic signals. Note also that the device 10 is used with the patient upright (sitting, exercising or standing) and awake (in contrast to some existing devices which are designed for use while the patient is lying down and asleep, e.g. to assess snoring or sleep apnoea, rather than to investigate nasal pathologies, etc).

As mentioned above, and as illustrated in Figure 2A, the device 10 comprises two sensors12L, 12R positioned on opposing sides of the patient's nose, to be able to output separate acoustic signals indicative of the breathing through each of the nasal cavities (and hence ultimately indicative of the condition of the nasal cavities). The device 10 is further provided with a cable or lead to communicate the acoustic signals from sensors 12R, 12L to an external system (not shown in Figure 2A), such as a computer 28 running data analysis software 30 as shown in Figure 2.

Although in some cases there may be a small amount of cross-talk within the two respective signals from sensors 12R and 12L (that is, the acoustic sensor may detect vibrations originating in the nasal cavity furthest from the acoustic sensor), the signal for each sensor is nevertheless generally dominated by vibrations originating from the nasal cavity closest to the acoustic sensor. Accordingly, each acoustic sensor 12L, 12R can output a signal indicative of the airflow within the respective closest nasal cavity. In addition, the data analysis software 30 may be configured to remove or reduce any remaining cross-talk from the measured acoustic signals by applying an appropriate algorithm (e.g. common mode rejection). This then allows the data analysis software 30 to extract or obtain the signal for each nasal cavity so as to help a medical practitioner determine conditions or blockages affecting the airflow through the nasal cavities.

Note that as shown in Figure 2A, the sensors 12R, 12L are positioned above the nostril outlets, and so do not disturb or distort the airflow into an out of the nose. Accordingly, the measured acoustic signals reflect the natural breathing of the subject, including (specifically) the interaction as the breathing airflow passes through the internal nasal cavities. As a result, the acoustic signals therefore provide direct information about the structure and pathology of these naval cavities.

Figure 3 is graph showing an example acoustic signal from acoustic sensor (such as sensor 12L) over a five second period caused by the airflow through the (left) nasal cavity. The graph shows the amplitude of the acoustic signal measured by the sensor (in arbitrary units) along the y-axis with respect to time along the x-axis. The acoustic signal shown is that from a healthy patient, i.e., a patient not suffering from a nasal blockage or the like.

Figure 3 shows complete breathing cycles, each cycle comprising a period of inspiration

(inhalation) followed by a period of expiration (exhalation). For the two periods of inspiration; the first is shown centred at around 1 second and the second is shown centred around 3.1 seconds. The duration of the first inspiration period is denoted T|_.L in Figure 3 (the L subscript indicates a value for the left nasal cavity; a subscript R is used to denote the right nasal cavity). In a similar manner, the first period of expiration is shown centred at around 1 .7 seconds and the second is shown centred at around 4.1 seconds. The duration of the first expiration period is labelled as T_E.i_ in Figure 3. Using a similar naming convention, the power of the left nasal inspiration may be labelled P|_.L and the power of the left nasal expiration may be labelled P_E.i_, etc. Note that the power P_LL is generally proportional to the square of the amplitude. As shown in Figure 3 the breathing follows a cycle of inspiration followed by expiration and so on. In Figure 3, the acoustic signal for the inhalation has a stronger peak (i.e., a greater amplitude) compared to the exhalation. Conversely, the expiration period is more prolonged than the inspiration period.

The system can be configured to detect (discriminate) automatically the inspiration and expiration periods such as marked in Figure 3. Thus the acoustic signal for the inspiration is generally shorter and more intense than the acoustic signal for the expiration, and with a relatively quiescent period following the latter before the next inspiration. This detection of inspiration and expiration may be performed independently on each of the left and right acoustic signals, with some form of averaging then potentially performed to provide a consistent demarcation on both channels. Alternatively (or additionally), the two acoustic signals may first be combined, and the detection of inspiration and expiration can then performed with respect to this combined signal.

The system can be configured to detect the respiration (breathing) rate, which may be measured, for example, as the inverse of the time interval between the start of two successive inspiration periods. For each breath (combination of inspiration and expiration) the system can determine the corresponding breathing rate. In practice, some form of (weighted) averaging or low pass filtering across multiple breaths may be performed to provide a more stable and accurate measurement of the breathing rate. It is also possible to obtain multiple samples of the breathing rate per breath - e.g. by detecting, for each breath, both the period from the start of inspiration to the start of inspiration for the previous breath, and also the period from the start of expiration to the start of expiration for the previous breath - which can then help to provide a more responsive (higher bandwidth) measurement of breathing rate.

The skilled person will appreciate that other techniques are available for determining the breathing rate. For example, the breathing rate might be measured based on finding a (quasi) periodicity in the overall acoustic signal such as shown in Figure 3, without necessarily identifying the constituent inspiration and expiration periods. The determination of the respiration rate may be performed independently on each of the left and right acoustic signals, with some form of averaging then potentially performed to provide a consistent demarcation on both channels, or alternatively (or additionally), the two acoustic signals may first be combined, and the determination of the breathing rate then performed with respect to this combined signal.

Figure 3 represents breathing in normal circumstances for a healthy patient. However, the shape and general form of the acoustic signal will vary depending upon how the patient is currently breathing - for example, a patient may be exercising, in which case the power of both inspiration and expiration is likely to be higher and the periods between inspiration and expiration for breaths are likely to be shorter.

The data analysis software 30 is configured to calculate certain parameters for the airflow in both the left and right nasal cavities as measured using the acoustic sensors 12L, 12R. Generally, acoustic signatures (i.e., specific patterns in the acoustic signals) can be used to identify airflow properties within the nasal cavities, which in turn may indicate specific conditions within the nasal cavities (or in the form of breathing by the patient). It has been found that certain conditions produce acoustic signals that have certain characteristics, which a medical practitioner can use to help identify the relevant condition.

In some cases, the acoustic signal(s) may be assessed by visual inspection. However, in order to provide a more objective and quantitative analysis, the data analysis software 30 is configured to calculate or derive certain specific parameters from the acoustic signals. Thus Figures 4A to 4C are examples of acoustic signals obtained for different patients and illustrate how certain parameters calculated from the acoustic signals may be used to identify underlying conditions that a patient might be suffering from.

Turning firstly to Figure 4A, this provides a pair of graphs showing a five second representation of left and right acoustic signals as separately measured by respective acoustic sensors. As with Figure 3, the graph shows the amplitudes of vibrations as measured by the sensors (in arbitrary units) along the y-axis with respect to time along the x-axis. The signals shown are again those from a healthy patient, i.e., a patient not suffering from a nasal blockage or the like. The acoustic signal on the left hand side of Figure 4A is the same as the acoustic signal shown in Figure 3, while the acoustic signal on the right hand side of Figure 4A is the corresponding acoustic signal as measured over the same time period by the right acoustic sensor 12R. As with Figure 3, the acoustic signals of Figure 4A show two breathing cycles. As Figure 4A represents a generally healthy patient, the acoustic signals from each nasal cavity are approximately similar in power. One can see from Figure 4A that the right acoustic signal (i.e., the right hand side of Figure 4A) has a slightly lower power level compared to the left acoustic signal. This is probably due to the "nasal cycle", a natural phenomenon in which the nasal cavities on both sides undergo alternating partial congestion and decongestion in a cyclic manner; each cycle typically lasts between 4 and 6 hours. Generally, for a healthy patient the ratio of the inspiration power to the expiration power for each nasal cavity should be roughly equal to or greater than one. In the left acoustic signal, the ratio of inspiration power P_LL to expiration power P_E.i_ can be represented as RPIE.L and is approximately equal to 3.1 for the first inspiration and the first expiration in the left hand side of Figure 4A. Note here that the ratio is considered between a given inspiration and the immediately following expiration. The ratio of inspiration power to expiration power for the right acoustic signal can similarly be represented as RPIE.R and is approximately equal to 4.9 for the first inspiration and the first expiration on the right hand side of Figure 4A. Note that the ratios RPIE.L and RPIE.R are obtained for inspirations and expirations occurring at substantially the same time in the right and left nasal cavities. Note that the second inspiration and expiration in the right acoustic signal have a power ratio RPIE.R of approximately 1 .5 to 2, which still satisfies the criteria of being "healthy" described above.

In addition to the power ratios RPIE.L or RPIE.R, which are ratios derived independently from each acoustic signal, the data analysis software 30 calculates the power ratios for inspirations or expirations between the acoustic signals. For example, the power ratio between the first inspiration in the left acoustic signal P_LL and the first inspiration in the right acoustic signal P_LR, denoted here as RPI.LR, is approximately 1 .3. Equally, the power ratio between the first expiration in the left acoustic signal P_E.L and the first expiration in the right acoustic signal PE R, denoted here as RPE.LR, is approximately 2.1 . For a healthy patient, these ratios should be around 1 .0 which intuitively can be understood to signify that the power (and thus the general airflow) in each nasal cavity are approximately the same. As mentioned above, the patient for Figure 4A was suffering from a mild cold which may explain the deviation of RPE.LR from 1 .0 in this particular case.

Typically, the inspiration period for a given patient for each acoustic signal (T|_.L and T|_.R) will be the same across multiple breaths, as will the expiration periods (T_{E L} and T_{E R}). Therefore it is also possible to define a ratio of the inspiration to expiration periods, RT|_.E. In Figure 4A, RTI.E is approximately 0.67. This parameter may also be used to determine if the patient's nasal breathing is normal based on a comparison of RT_LE to a pre-defined normal value (or range of normal values), which may be determined empirically.

Figure 4B is a pair of graphs showing a fifteen second representation of acoustic signals as measured by left and right acoustic sensors for a second patient (different to the patient of Figure 4A). Again, the acoustic signal from the left acoustic sensor 12L is shown on the left hand side of Figure 4B while the acoustic signal from the right acoustic sensor 12R is shown on the right hand side of Figure 4B. As with Figure 4A, the graph shows the signal amplitudes as measured by the sensors (in arbitrary units) along the y-axis with respect to time along the x- axis. Figure 4B shows acoustic signals which are significantly different from the acoustic signals shown in Figure 4A; specifically, the second patient (of Figure 4B) is suffering from right septal deviation, in which the bone in the middle of the nose is bent to the right causing a blockage in the right nasal cavity/nostril. Figure 4B shows approximately four complete breaths over a fifteen second period.

As would be expected, in such a condition the side of the nose containing the blockage (in this case the right nasal cavity) will produce a weaker sound (in terms of power) than the side of the nose without the blockage, because the airflow in the blocked side will be reduced. In Figure 4B, the ratio of inspiration power between inspirations at the same time in the left and right acoustic signals (i.e., RPI.LR) and the ratio of expiration power between expirations at the same time in the left and right acoustic signals (i.e., RPE.LR) are high. Specifically, RPI.LR is approximately 2.8 and RPE.LR is approximately 7.7. These high values signify that there is a large discrepancy in the power between the left and right acoustic signals. Specifically, the right acoustic signal has a much lower power than the left acoustic signal indicating a blockage in the right nasal cavity.

In addition to these parameters, the data analysis software 30 calculates the ratio of the inspiration to expiration power in both the left and right acoustic signals; in Figure 4B, RP|_{E L} is approximately 0.3 while RP|_E.R is approximately 0.9. This indicates that the expirations in the left acoustic signal are relatively stronger than the inspirations, which could be suggestive of patients suffering from septal deviation. The ratio of inspiration to expiration periods, RT_LE, in Figure 4B is approximately 0.7 which is not too dissimilar to Figure 4A.

Thus, for a patient suffering from septal deviation, values of RPI.LR and RPE.LR significantly greater than 1 could be in general considered as characteristic of such septal deviation.

Figure 4C is a pair of graphs showing a fifteen second representation of acoustic signals as measured by respective acoustic sensors for a third patient. Again, the acoustic signal from the left acoustic sensor 12L is shown on the left hand side of Figure 4C while the acoustic signal from the right acoustic sensor 12R is shown on the right hand side of Figure 4C. As with Figures 4A and 4B, the graph shows the signal amplitudes measured by the sensors (in arbitrary units) along the y-axis with respect to time along the x-axis. The third patient is suffering from septal perforation, in which there is a hole in the middle bone of the nose effectively joining the two nasal cavities to allow air to pass from one nasal cavity/nostril to the other. Figure 4C shows approximately five complete breaths over a fifteen second period.

It can be seen from the acoustic signals in Figure 4C that the right acoustic signal has relatively smaller inspirations compared to the inspirations in the left acoustic signal, while the left acoustic signal has relatively smaller expirations compared to the expirations in the right acoustic signal. The ratio of inspiration power between left and right acoustic signals, RPI.LR, is approximately 2. 6, while the ratio of expiration power between left and right acoustic signals, RPE.LR, is approximately 0.7. A high RPI.LR (higher than 1 ) and a low RPE.LR (lower than 1 ) may therefore be indicative of septal perforation (although this may be reversed, i.e., a low RPI.LR and a high RPE.LR, depending upon the actual physical airflow between nasal cavities). Generally speaking, a discrepancy between RPI.LR and RPE.LR can be considered as indicative of septal perforation.

In addition, the ratio of inspiration power to expiration power in the right acoustic signal, RPiE.R, is lower than 1 (approximately 0.4). Recall that for a healthy patient RPIE.R is greater than 1 . Thus, in Figure 4C, within the right acoustic signal, the expirations are substantially stronger than the inspirations, which again may act as an indicator of septal perforation, and certainly suggests that not all is well. Again, it should be understood that the ratio of inspiration power to expiration power in the left acoustic signal may also be lower than 1 for septal perforation depending upon the direction of any physical airflow within the nasal cavities. In Figure 4C, RPiE.L is approximately 1 .3 (which by itself may not be indicative of septal perforation). Thus, for a patient suffering with septal perforation, deviations in the values of RPI.LR and RPE.LR_, plus a low ratio of inspiration to expiration power in one of the signals, might be considered characteristic of such septal perforation.

From the above three examples in Figures 4A to 4C, it will be understood that the data analysis software 30 as described above is configured to calculate parameters from the two acoustic signals obtained from the respective nasal cavities. Certain conditions (i.e., healthy, septal deviation, septal perforation) have characteristic patterns (or acoustic signatures) which can be identified within the acoustic signals and the calculated parameters and subsequently quantified. Thus it is possible to identify certain conditions by assessing the calculated parameters, either manually or automatically, against predetermined thresholds or ranges for the conditions (the acoustic signatures). Consequently, calculating parameters from acoustic signals of the airflow though each nasal cavity enables blockages, anatomical conditions and the like to be identified using an evidenced-based technique.

In addition to the data analysis software 30 calculating parameters from the power or duration of the acoustic signals in the time domain, in some further implementations the data analysis software 30 is configured to identify aspects of the acoustic signal in the frequency domain. In other words, the data analysis software 30 is configured to determine individual frequency components of the acoustic signals, e.g., in the form of a spectrogram or power spectrum. For example, an unusual amount of power at relatively high frequencies might be indicative of airflow through a relatively small opening - e.g. a perforation of the septum (similar to the situation with heart sound analysis). In some cases, the data analysis might perform a combined time-frequency domain analysis. For example, the acoustic signals may be split into multiple (potentially overlapping) time sections, and for each time section, a power spectrum or similar is calculated. This then allows an investigation of the variation with time of the frequency (spectral) distribution of power in the acoustic signals, such as provided in Figures 5A and 5B.

Thus Figure 5A shows graphs of a fifteen second representation of acoustic signals as measured separately by the acoustic sensors for a fourth patient. The acoustic signal from the left acoustic sensor 12L is shown on the left hand side of Figure 5A while the acoustic signal from the right acoustic sensor 12R is shown on the right hand side of Figure 5A. As with Figures 4A to 4C, the graphs in the upper part of Figure 5A show the amplitudes of the noise (audio/acoustic) signals as measured by the sensors (in arbitrary units) along the y-axis with respect to time along the x-axis. The graphs in the lower portion of Figure 5A are spectrograms showing the frequencies of the measured acoustic signals (in Hertz) along the y-axis with respect to time along the x-axis. The intensity of power at a given frequency and time is then indicated in the form of a heat map, with the yellow (lighter) background being cooler, i.e. having less power, than the red (darker) areas at lower frequency.

Figure 5B is an enlarged representation of the spectrogram of the right acoustic signal of Figure 5A, with the colour scale changed to highlight features of interest, specifically "whistling", which indicates an abnormality in the airflow. In this case, the fourth patient of Figures 5A and 5B has external nasal valve collapse in both nostrils in addition to septal deviation to the right. External nasal valve collapse is a condition in which the nostrils/nasal cavities collapse inwards during inspiration. As with Figures 4A to 4C, various parameters are determined by the data analysis software 30 from the acoustic signals. For the fourth patient, it can be seen from the upper graphs in Figure 5A that the inspirations have a much lower power than the expirations (RPiE.L is approximately 0.2 and RPIE.R is approximately 0.4 - both are much lower than 1 ). In addition, the right acoustic signal has, generally, much less power than the left acoustic signal particularly with respect to the exhalations (RPI.LR is approximately 1 .7 and RP_E.LR is approximately 3.8; both noticeably larger than 1 ).

Additional information can be obtained from the spectrograms of the acoustic signals shown in Figures 5A and 5B. Thus referring now to the lower graphs (i.e. the spectrograms) in Figures 5A and 5B, it can be seen that for the expirations in particular there is power in a relatively high frequency component in the right acoustic signal. Figure 5B shows more clearly distinct frequency components (in the frequency range of about 5 to 10 kHz) as indicated by the arrows labelled "whistling". For the fourth patient, such whistling sounds are present in the right nasal cavity/nostril when breathing. These types of unusual sounds are produced by the disturbances of air within the nasal cavity due to the nature of the nasal blockage. Therefore, from the spectrograms of acoustic signals such as shown in Figures 5A and 5B, different frequency components of the acoustic signals can be identified and used to help investigate the patient's condition. For example, the duration and range of frequencies (as well as whether they are prominent in expiration or inspiration) can be used to quantify the degree of "whistling" in the acoustic signals.

It will be appreciated that the results shown in Figures 3, 4A, 4B, 4C, 5A, 5B, 6A and 6B represent preliminary data from a relatively small group of patients/subjects. Further investigations are planned to obtain additional clinical data and hence enhanced understanding of how the various nasal conditions impact the measured acoustic signals.

Figures 6A and 6B schematically show a nasal airflow sensing device 1 10 in accordance with some other embodiments. The device 1 10 of Figures 6A and 6B is similar to device 10 of Figures 1 A and 1 B, but with some differences as explained below. Figure 6A shows the nasal airflow sensing device 1 10 in plan view (i.e. from above) as taken along line A-A in Figure 6B, while Figure 6B shows the nasal airflow sensing device 1 10 in cross-sectional view taken along line B-B in Figure 6A.

The nasal airflow sensing device 1 10 comprises a right acoustic sensor 1 12R, a left acoustic sensor 1 12L, and a processing and transmission element 1 14 mounted on/in a flexible substrate 1 16. An adhesive layer 1 18 is also provided for attaching the device 1 10 to the skin of a patient, specifically on the outer surface of the patient's nose. The right and left acoustic sensors 1 12R, 1 12L are substantially the same as the right and left acoustic sensors 12R, 12L as described in conjunction with Figures 1A and 1 B, similar the adhesive layer 1 18 is substantially the same as adhesive layer 18 of Figures 1 A and 1 B.

The substrate 1 16 is substantially similar to the substrate 16 described above, with the exception that the substrate 1 16 additionally comprises one or more resilient members 1 1 1 which extend across the length of the substrate 1 16. As with substrate 16, the substrate 1 16 is configured to be applied to the nose of a patient and is formed from a flexible material allowing conformity of the substrate 1 16 to the contours of the nose of the patient. The resilient members 1 1 1 bias the substrate 1 16 towards a "flat" or "at rest" configuration, i.e., when not applied to the patient's nose but in a condition ready to do so. Providing these resilient members 1 1 1 can aid in opening the nasal cavities, as the substrate 1 16 pulls the outer surfaces of the patient's nose outwards. This can be used to help airflow through the nasal cavities, which may be advantageous for obtaining a clearer acoustic signal (and may also aid in distinguishing between blockages resulting from temporary conditions, e.g., colds, and anatomical conditions).

One difference of device 1 10 compared to device 10 is the additional presence of a cover layer 140 and a background acoustic sensor 142. Figure 1 B shows the cover layer 140 disposed on the side of the substrate 1 16 opposite the adhesive layer 1 18 and arranged to cover the background acoustic sensor 142. The cover layer 140 may be formed from the same or similar materials as the substrate. In some cases, the cover layer 140 may have a different size to the substrate 16, e.g. it may be sized so as to cover only the background acoustic sensor 142. The background acoustic sensor 142 is configured to measure the background acoustic noise in the vicinity of the device 1 10. The background acoustic sensor 142 is acoustically insulated, as far as is possible, from the nasal cavities such that the background acoustic sensor 142 does not acoustically monitor the airflow through the nasal cavities. The background acoustic sensor 142 is configured therefore to output an acoustic signal indicative of the background noise in the vicinity of the device 1 10 to the processing and transmission element 1 14 (or directly to a computer if the processing and transmission element 1 14 is not present). This then allows a background acoustic sensor 142 to be subtracted from the acoustic signals received from the left and right acoustic sensors 1 12L, 1 12R, which can help a more accurate analysis to be performed.

Although the background acoustic sensor 142 is shown in Figure 6 as an integral part of the device 1 10, i.e. included in the strip that is placed over the nose, in other implementations the processing and transmission device may be physically located outside the device, for example, in a separate wearable module worn around the neck or on the ear. A further possibility is that the background acoustic sensor 142 is placed on a separate stand or support which is positioned near to (but not attached to) the subject. As mentioned above, the output of such a background acoustic sensor 142 may then be passed to the processing and transmission element 1 14 or to an external computer system, depending upon where the background audio subtraction is to be performed.

Figure 7 is another example nasal airflow sensing device 210 in accordance with some embodiments. Figure 7 shows the nasal airflow sensing device 210 in plan view (i.e. from above). The device 210 comprises a first right acoustic sensor 212R, a first left acoustic sensor 212L, a second right acoustic sensor 252R, a second left acoustic sensor 252L, and a processing and transmission element 214 mounted on/in a flexible substrate 216.

The device 210 shown in Figure 7 primarily differs from the sensing devices 10 and 1 10 described above in the shape of the substrate 216, which is an approximate trapezium shape, and which is large enough to support a pair of sensors on each side, i.e. a pair of sensors 212R, 252R on the right, and a pair of sensors 212L, 252L on the right. It will be appreciated that having four sensors allows for four audio signals to be measured, and may provide additional information about the airflow through the nasal cavities. For example, comparing the acoustic signals from the first right acoustic sensor 212R and the second acoustic sensor 252R might help to identify the location of a nasal blockage in the right cavity. Although various embodiments have been described by way of example, the skilled person will be aware of various modifications of these embodiments. For example, the devices shown have been provided with left and right acoustic sensors 12L and 12R, joined by a substrate 16 in a single integrated device. This can help to ensure more consistent results (by more consistent positioning of the sensors), and also is convenient for applying to the patient. However, in other implementations, the two acoustic sensors 12L, 12R may be provided as respective, separate components (i.e. not integrated into a single unit or linked by a substrate). Each of the separate components can then be placed individually on the nose for acoustically monitoring a respective nasal cavities - that is, one sensor can be placed on the outer surface of the left side of the nose, while the other sensor can be independently placed on the outer surface of the right side of the nose. (In this implementation each part may be identified by a marking (such as an "L" or "R" symbol) in order to locate on the correct nostril). Such an implementation might be easier to use with patients whose nose has significant damage or sensitivity.

In addition, the above implementations derive certain parameters from the acoustic monitoring, and these are then available for comparison against standard ranges and thresholds in order to help a clinician identify a nasal problem, compare any change in condition from a previous measurement (e.g. to assess the effectiveness of a therapy, or the general improvement or decline of a patient), or more generally investigate the function and condition of the nose. However, other implementations may derive other (or additional) parameters, or adopt a different approach, to help the clinician with these tasks. For example, a principal component analysis (PCA) may be performed to identify the most important statistical parameters for characterising the acoustic airflow signals, and these parameters may then be provided to a clinician to analyse the results. A slight different approach would be to use a neural network or other artificial intelligence system, which could be trained on acoustic signals from patients with known (labelled) conditions. Such a system could then be used to detect and classify whether further acoustic signals matched these known conditions (or possibly represented a previously unencountered condition).

The skilled person will be aware of many additional implementations that fall within the scope of the appended claims. References

[1 ] Moore, M., Objective evidence for the efficacy of surgical management of the deviated nasal septum as a treatment for chronic nasal obstruction [MPhil Thesis]. April 2013,

Cardiff University.

[2] Chaaban, M. and J. P. Corey, Assessing nasal air flow: options and utility. Proc Am

Thorac Soc, 201 1 . 8(1 ): p. 70-8.

[3] Crobridge, R. and N. Steventon, Oxford Handbook of ENT and Head and Neck Surgery.

2 ed. 2010: Oxford University Press

[4] NHS. Sinusitis [Online]. 2015 13 May 2015 [cited 20 July 2015 20 July 2015]; Available from: http://www.nhs.uk/Conditions/Sinusitis/Pages/lntroduction.aspx.

[5] NHS. Treating allergic rhinitis [Online] 2014 19 March 2014 [cited 20 July 2015 20 July

2015];

Available from: http://www.nhs.uk/Conditions/Rhinitis-allergic/Pages/Treatment.aspx

[6] NHS. Treating sinusitis [Online] 2015 13 May 2015 [cited 20 July 2015 20 July 2015];

Available from: http://www.nhs.uk/Conditions/Sinusitis/Pages/Treatment.aspx.

[7] Nip, L, Analysis of Nasal Blockage Using Acoustic Sensors (iBSc Report), in UCL

Department of Medical Physics and Biomedical Engineering. 2015, University College London (UCL).

[8] Sinus Anatomy & Function [Online], [cited 2015 20 July 2015]; Available from: http://www.ohiosinus.com/patient-info/sinus-anatomy-and-function.

[9] Clarke, R., Lecture notes. Diseases of the ear, nose and throat 1 1 ed. 2014: Wiley-

Blackwell

[10] Rhee, J.S., et al., A systematic review of patient-reported nasal obstruction scores: defining normative and symptomatic ranges in surgical patients. JAMA Facial Plast Surg,

2014. 16(3): p. 219-25; quiz 232.

[1 1 ] Stewart, M.G., et al., Development and validation of the Nasal Obstruction Symptom

Evaluation (NOSE) scale. Otolaryngol Head Neck Surg, 2004. 130(2): p. 157-63.

[12] Casale, M., et al., Video-rhino-hygrometer: a new method for evaluation of nasal breathing after nasal surgery. Am J Rhinol Allergy, 2010. 24(6): p. 467-71 .

[13] Takhar, A.S., et al., Validation of the sino-nasal outcome test-23 in septorhinoplasty surgery. Rhinology, 2014. 52(4): p. 320-6.

[14] Manjunatha, R.G., et al., Piezoelectric sensing: Evaluation for clinical investigation of deviated nasal septum. Allergy Rhinol (Providence), 2013. 4(3): p. e140-50. [15] Dolan, R.W., Minimally invasive nasal valve repair: An evaluation using the NOSE scale.

Arch Otolaryngol Head Neck Surg, 2010. 136(3): p. 292-5.

[16] Mondina, M., et al., Assessment of nasal septoplasty using NOSE and RhinoQoL questionnaires. Eur Arch Otorhinolaryngol, 2012. 269(10): p. 2189-95.

[17] Phillips, P.S., et al., Functional and cosmetic outcomes of external approach septoplasty. Am J Rhinol Allergy, 201 1 . 25(5): p. 351 -7.

[18] Poirrier, A.L., et al., Is the Sino-Nasal Outcome Test-22 a suitable evaluation for septorhinoplasty? Laryngoscope, 2013. 123(1 ): p. 76-81 .

[19] Gertner, R., L. Podoshin, and M. Fradis, A simple method of measuring the nasal airway in clinical work. J Laryngol Otol, 1984. 98(4): p. 351 -5.

[20] Brescovici, S. and R. Roithmann, Modified Glatzel mirror test reproducibility in the evaluation of nasal patency. Braz J Otorhinolaryngol, 2008. 74(2): p. 215-22.

[21 ] Scadding, G., et al., Diagnostic tools in Rhinology EAACI position paper. Clin Transl

Allergy, 201 1 . 1 (1 ): p. 2.

[22] Andrews, P.J., et al., The need for an objective measure in septorhinoplasty surgery: Are we any closer to finding an answer? Clin Otolaryngol, 2015.

[23] Tsounis, M., et al., The clinical value of peak nasal inspiratory flow, peak oral inspiratory flow, and the nasal patency index. Laryngoscope, 2014. 124(12): p. 2665-9.

[24] Yepes-Nunez, J.J., et al., Assessment of nasal obstruction: correlation between subjective and objective techniques. Allergol Immunopathol (Madr), 2013. 41 (6): p. 397-

401 .

[25] Teixeira, R.U., et al., Peak nasal inspiratory flow evaluation as an objective method of measuring nasal airflow. Braz J Otorhinolaryngol, 201 1 . 77(4): p. 473-80.

[26] Clement, P.A., et al., Critical evaluation of different objective techniques of nasal airway assessment: a clinical review. Eur Arch Otorhinolaryngol, 2014. 271 (10): p. 2617-25.

[27] Bermuller, C, et al., Diagnostic accuracy of peak nasal inspiratory flow and rhinomanometry in functional rhinosurgery. Laryngoscope, 2008. 1 18(4): p. 605-10.

Claims

1 . Apparatus comprising:

a nasal airflow sensing device comprising a first acoustic sensor and a second acoustic sensor configured to be fixed on opposing sides of a nose of an upright patient to acquire first and second acoustic signals respectively for acoustically monitoring airflow through the nose, the first and second acoustic sensors being configured to be fixed on opposing sides of the exterior of the nose so as not to interfere with the airflow through the nose of the patient, wherein the first acoustic signal is indicative of the airflow through the nasal cavity on the side of the nose to which the first acoustic sensor is fixed, the second acoustic signal is indicative of the airflow through the nasal cavity on the side of the nose to which the second acoustic sensor is fixed, and the first and second acoustic sensors pick up their respective acoustic signals from airflow through their respective nasal cavities with little or no cross-talk from the airflow through the other nasal cavity;

and a computing system having a data link with the device for receiving and analysing the first and second acoustic signals, wherein the computing system is configured to analyse the first and second acoustic signals in the time domain to derive one or more parameters indicative of a condition of the nasal cavities.

2. The apparatus of claim 1 , wherein cross-talk is suppressed at a level of 20dB, preferably 30dB, preferably 40dB, preferably 50dB.

3. The apparatus of claim 1 or 2, wherein the first and second acoustic sensors include piezoelectric sensors.

4. The apparatus of any preceding claim, wherein the device further includes an amplifier for each of the first and second acoustic signals.

5. The apparatus of any preceding claim, wherein the device further includes a high pass filter for each of the first and second acoustic signals, wherein the high-pass filter preferably has a cut-off around 100Hz.

6. The apparatus of any preceding claim, wherein the device further includes a band-pass filter for each of the first and second acoustic signals, wherein the band-pass filter preferably has a pass-band between around 100Hz and around 20000 Hz.

7. The apparatus of any preceding claim, wherein the device further includes a data communication facility for passing the first and second acoustic signals to the computing system for analysis.

8. The apparatus of claim 7, wherein said data communication facility is a USB connection or a wireless link.

9 The apparatus of any preceding claim, further comprising a background acoustic sensor configured to acquire an acoustic signal indicative of background noise in the vicinity of the patient.

10. The apparatus of any of the preceding claims, wherein the device comprises a flexible elongated substrate supporting the first and second acoustic sensors adjacent opposite ends of the elongated substrate, wherein the substrate is configured, in use, to span across the bridge of the nose from one side to the other side.

1 1 . The apparatus of claim 10, wherein the substrate is provided, on one surface thereof, with adhesive for fixing the device to the nose.

12. The apparatus of claim 10 or 1 1 , wherein the device is provided with resilient members extending between the opposite ends of the substrate to bias the substrate towards a flat configuration such that, when the device is fixed to the nose, the device tends to expand the nasal cavities of the nose.

13. The apparatus of any preceding claim, wherein the parameters include one or more of: duration of inhalation;

duration of exhalation;

power of inhalation;

power of exhalation;

and wherein said parameters are derived separately for each side of the nose.

14. The apparatus of claim 13, wherein the parameters further include the ratios of:

duration of inhalation to duration of exhalation;

power of inhalation to power of exhalation;

and wherein said parameters are derived separately for each side of the nose.

15. The apparatus of any preceding claim, wherein the parameters further include ratios formed by comparing corresponding parameters derived separately for each side of the nose.

16. The apparatus of any preceding claim, wherein the parameters further include parameters based on frequency domain analysis of the first and second acoustic signals.

17. The apparatus of claim 16, wherein the parameters include parameters indicating the variation with time of a power spectral distribution of the first and second acoustic signals.

18. The apparatus of any preceding claim, wherein the apparatus is configured to link properties or parameters of the first and second acoustic signals to potential nasal conditions.

19. The apparatus of any preceding claim, wherein the apparatus is configured to acquire the first and second acoustic signals simultaneously.

20. The apparatus of claim 19, wherein analysing the first and second acoustic signals in the time domain includes comparing, for at least one point in time, the first acoustic signal, or a parameter derived therefrom, with the simultaneously acquired second acoustic signal, or a parameter derived therefrom.

21 . The apparatus of any preceding claim, wherein the apparatus is configured to distinguish between nasal inhalation and nasal exhalation.

22. The apparatus of any preceding claim, wherein the apparatus is configured to determine a respiration rate.

23. A method of performing a measurement of nasal airflow comprising:

fixing a first acoustic sensor and a second acoustic sensor on opposing sides of a nose of an upright patient;

acquiring first and second acoustic signals from the first and second acoustic sensors respectively for acoustically monitoring airflow through the nose, the first and second acoustic sensors being fixed on opposing sides of the exterior of the nose so as not to interfere with the airflow through the nose of the patient, wherein the first acoustic signal is indicative of the airflow through the nasal cavity on the side of the nose to which the first acoustic sensor is fixed, the second acoustic signal is indicative of the airflow through the nasal cavity on the side of the nose to which the second acoustic sensor is fixed, and the first and second acoustic sensors pick up their respective acoustic signals from airflow through their respective nasal cavities with little or no cross-talk from the airflow through the other nasal cavity;

transmitting the first and second acoustic signals to a computer system;

and the computing system receiving and analysing the first and second acoustic signals, wherein the computing system analyses the first and second acoustic signals in the time domain to derive one or more parameters indicative of a condition of the nasal cavities.