Driving is one of the activities that takes a significant part of a person’s time, that is why monitoring vital signs is useful for the wellness of the occupants of the vehicle. One of the vital signs that provides more information about the state of the person, is the functional breathing. Compared to other vital signs indicators, breathing is more sensitive to cardiovascular events, emotional stress, physical exertion, or fatigue induced by long time driving, seen as variations in chest and abdomen elongation modes. Functional monitoring is a tool that can transcend, from measurement and detection to emotional changes through feedback of sounds, images, or videos to the driver. In this regard, this work proposes an imaging radar system to generate a topographic map with elongation modes of the driver’s chest and abdomen, at 120 GHz. Numerical simulations have been deployed in order to reconstruct the image from the receiver signal in the radar using spatial convolution.
Furthermore, a metronome has been used to calibrate the radar for elongations measuring with respect to time, and finally, the system has been tested experimentally in an adult person, to generate a preliminary topographic map that allows matching the chest elongation modes to breathing patterns.This work was supported by the Spanish “Comision Interministerial de Ciencia y Tecnologia” (CICYT) under projects TEC2016-78028-C3-1-P and MDM2016-O6OO; Catalan Research Group 2017 SGR 219; and ”Secretaría Nacional de Educación Superior, Ciencia, Tecnología e Innovación” (SENESCYT) from the Ecuadorian government.Peer ReviewedObjectius de Desenvolupament Sostenible::3 - Salut i BenestarPostprint (published version

Aguasca Solé, Alberto

Jofre Roca, Lluís

López Montero, María José

Romeu Robert, Jordi

English

UPCommons. Portal del coneixement obert de la UPC

In-Cabin 120 GHz Radar System for FunctionalHuman Breathing Monitoring in a 3D ScenarioMarı́a J. López(1), A. Aguasca(1), J. Romeu(1), L. Jofre-Roca(1)maria.jose.lopez.montero@upc.edu, alberto.aguasca@upc.edu,romeu@tsc.upc.edu , luis.jofre@upc.edu(1)Dept. of Signal Theory and Communications, Universitat Politècnica de Catalunya - BarcelonaTech,Barcelona 08034, SpainAbstract—Driving is one of the activities that takes a sig-nificant part of a person’s time, that is why monitoring vitalsigns is useful for the wellness of the occupants of the vehicle.One of the vital signs that provides more information aboutthe state of the person, is the functional breathing. Comparedto other vital signs indicators, breathing is more sensitive tocardiovascular events, emotional stress, physical exertion, orfatigue induced by long time driving, seen as variations inchest and abdomen elongation modes. Functional monitoringis a tool that can transcend, from measurement and detection toemotional changes through feedback of sounds, images, or videosto the driver. In this regard, this work proposes an imagingradar system to generate a topographic map with elongationmodes of the driver’s chest and abdomen, at 120 GHz. Numericalsimulations have been deployed in order to reconstruct the imagefrom the receiver signal in the radar using spatial convolution.Furthermore, a metronome has been used to calibrate the radarfor elongations measuring with respect to time, and finally, thesystem has been tested experimentally in an adult person, togenerate a preliminary topographic map that allows matchingthe chest elongation modes to breathing patterns.I. INTRODUCTIONSeveral studies support the idea that many traffic accidentcan be prevented by early recognition of abnormal vital signs.Cardiovascular events, emotional stress, physical exertion, orfatigue induced by long time driving can cause the driver tolose concentration on the road. Compared to other vital signsindicators, breathing is more sensitive to alterations in thecondition of the subject and is a key predictor of unfavorableepisodes such as drowsiness, fatigue, or emotional stress [1].Lately, some studies are focused in breathing monitoring[2], [3], which has provoked the emergence of numerouscommercial wearable devices, such as wrist bands, cheststraps, or compression garment, but these may not be practicalin all situations because continued skin contact can causediscomfort to the subject. In contrast, non-contact monitoringis a non-invasive procedure explored in the recent years,as in [4], [5], and it is this area where radar has attractedconsiderable attention, as presented in [6]–[8]. Even thoughadvances in non-contact breathing monitoring has improvemarkedly, these methods provide incomplete information onchest wall and abdominal motion. Information from chestand abdomen motion is equally important as information onlung volumes, because variations can be caused by airwaysaffection, muscle weakness or stress. As presented in [9], it ispossible going beyond technology, to offer people a state ofcomfort according to his state of health, moods like anxietycan be reduced by a positive feedback. It is then possible touse the motion of chest and abdomen to determine the stateof the driver.With this goal, this paper introduces the term elonga-tion modes to refer to the variations of movement in thechest and abdomen, and presents (i) a novel radar-basedmethod for measuring elongations modes of human chestand abdomen, to build a topographical map, that allows todetermine the driver status according to breathing patterns; (ii)numerical simulations to characterise the system and establishthe optimal beamwidth of the radar that enables appropriateelongation modes measuring for in-cabin passengers; (iii) acalibrated radar system to deploy preliminary measurementsof elongation modes.On the basis of the findings presented in this paper, futurework will be focused on using elongation modes to feedbackthe driver with visual or audible signals that enhance the in-cabin comfort.II. THEORETICAL BACKGROUNDA. Types of breathingThere are different types of breathing that require a differentprocess to allow for inspiration and expiration.• Eupnea: it occurs at rest, diaphragm and external inter-costals must contract. Normal breathing rate in an adultperson, between 12 and 16 breaths per minute.• Diaphragmatic breathing: it is also known as deep breath-ing, the diaphragm relaxes, air passively leaves the lungs.Breathing rate is 7 breaths per minute.• Costal breathing: as the intercostal muscles relax, airpassively leaves the lungs. It is also known as shallowbreathing.• Hyperpnea: occurs during exercise or actions that requirethe active manipulation of breathing. It is also known asforced breathing, inspiration and expiration both occurdue to muscle contractions.B. Breathing patternsChest and abdominal movements, from a medical point ofview, can be labeled according to the site where the greatestrange of motion take place. A interesting work is presentedin [10], they study respiratory movements in a group of 50men and 50 women aged between 20 and 69 years. Theyinstructed subjects to breathe normally, deeply and slowly.The chest and abdomen have been divided into six sections,the right- and left sides of abdominal (LA, RA), upper thoracic(LUTh, RUTh) and lower thoracic (LLTh, RLTh). Results ofmeasurements are shown in Tables I and II.From the findings of [10], is established that respiratorymovements are symmetrically, do not decrease significantlyTABLE IQUIET BREATHING MOVEMENTS OF MEN AND WOMEN 20-69 YEARS (INmm). DATA FROM [10].QuietbreathingAbdominal Lower thoracic Upper thoracicRA LA RLTh LLTh RUTh LUThMen 7.47 7.33 3.35 3.38 2.64 2.66Women 6.49 6.20 3.87 3.92 3.38 3.39TABLE IIDEEP BREATHING MOVEMENTS OF MEN AND WOMEN 20-69 YEARS (INmm). DATA FROM [10].DeepbreathingAbdominal Lower thoracic Upper thoracicRA LA RLTh LLTh RUTh LUThMen 24.68 24.57 19.72 20.66 18.37 17.62Women 17.52 17.22 16.01 16.22 18.04 17.70with age (from 20 to 69), and is different in men and womenfor abdominal motion during deep breathing.C. Spirometry measurementsIn accordance with the objectives of this paper, spirometrycan provide additional information to determine the modes ofchest elongation in certain situations. Spirometry measures therate which the lung changes volume during forced breathingmanoeuvres. Tidal volume is the quantity of air cycled throughinhalation and exhalation, this quantity multiplied by therespiration rate is called minute ventilation, and it is andimportant indicator of lung function. These values vary fromperson to person. Infants and children have considerablehigher respiratory rates than adults. Table III, summarizes thebreathing rates by ages.TABLE IIIRESPIRATION RATEGroups Rate (times/min)Newborn 44Infant 50Children 25Adult man 16Adult woman 14D. Elongation modes definitionAs a person performs the breathing process, as presented inthe literature review, the chest and abdomen move dependingon the breathing pattern. This variation can range from a fewmillimeters to about 25 mm. If the antennas of a radar arepointing the chest and abdomen, the signal received will varyin magnitude and phase. At this point, it is possible to definethe elongation modes as the portion of the chest or abdomen,in which the movement is greatest during the breathingprocess. These elongation modes may vary depending on theperson’s age, gender, and state of health.Whereas the movement in the chest and abdomen duringbreathing is symmetrical from right to left, two modes ofelongation have been identified that allows classify the typeof breathing as thoracic and abdominal. As shown in Fig.1a. However, according to the breathing patterns analyzed,an approach that gives much more information is to usethree elongation modes, abdominal, upper thoracic and lowerthoracic, as shown in figure 1b.(a) (b)Fig. 1. (a) Two elongation modes enables the thoracic and abdominalbreathing detection. (b) Three elongation modes are useful for breathingpattern identification.III. METHODOLOGYThis study has been developed in two parts. The first partconsists on constructing a topographic map of the chest ofthe human body by mean of numerical simulations from animage in a real driving situation. To do this, the beamwidthof the radar has been simulated, in terms of the longitudinaland transversal resolution, and the reconstruction of the imagehas been made from the received signal. The second part ofthe study focuses on achieving the sensitivity, in terms ofresolution level, on the radar that enables constructing a realtopographic map of the chest, whose elongation modes arerelated to breathing patterns. A radar calibration has beendeployed, then experiments for target detection and finallybreathing detection and elongation measurements. Figure 2depicts a schematic of the proposed scenario. The radar islocated in the rear-view mirror of the car pointing to the driver.Fig. 2. The radar is located in the rear-view mirror, the distance to the driveris R1=65 cm, and to the passenger is R2=131 cmA. SubjectsExperiments were carried out in the scenario shown inFig. 2, and includes two people inside the car. One subject(height: 170 cm, weight: 65 kg, age: 32), named subject 1,was sitting in the front of the car positioning at 65 cm (R1)away from the radar and the other subject (height: 179 cm,weight: 69 kg, age: 23), named subject 2, was in the backseat, 160 cm (R2) away from the radar. Both of them wereusing normal clothing and met the following requirements:no smoking history and no previous disorders affecting therespiratory system. According to [11], the body max index(BMI) influences in chest and abdomen motion; a personwith BMI of 30 and above have reduced movement of thediaphragm. So, the selected subjects have BMIs 22,5 and 21,5respectively. For numerical simulations, a real picture of thescenario was used.B. Radar systemChest and abdominal movements were measured with aradar that operates at the carrier frequency of 122 GHz witha 7 GHz bandwidth, has a range resolution of 10m andnoise figure of 8.7 dB. The radar front-end (RFE) is used infrequency-modulated continuous-wave (FMCW) mode, usingchirp signals. A collimator lens of diameter Dl placed 10mmfrom the RFE, is used to control the beamwidth and to focuscorrectly the human chest. The received data is packaged inthe form of frames, that are transmitted by a serial commu-nication to a host computer to be analyzed and plotted usingMatlab. Target range information is extracted by applying aFast Fourier Transform (FFT) to each chirp signal, each peakin the frequency domain represents the displacement in thetarget (chest and abdomen motion).C. Numerical simulationWhen a radar is pointing the human body, each movementof the persons can modify the signal both in phase and inmagnitude. Compared to common environments for breathingrate monitoring, the space inside the vehicle is limited, forthis reason, to determine the ideal monitoring conditions, anoptimal beamwidth and lens size are of fundamental impor-tance, since it directly provides a correct resolution for imagereconstruction. Numerical simulations have been conducted todetermine the optimal beamwidth and lens diameter with twoobjectives: (i) in-cabin passengers image reconstruction andthen (ii) elongation chest measuring.The resolution of the reconstructed image depends of thebeamwidth of the radar, and it can be modified by mean ofa lens, according to δt = Ri. λDl , where Ri is the distance tothe target, λ is the wavelength, and Dl is the lens diameter.If the driver is located at R1=65 cm and Dl=3 cm, theoptimal beamwidth to reconstruct the driver is δt=53mm. Thereconstructed image is shown in Fig. 3.(a) (b)Fig. 3. (a) Real picture used for imaging reconstruction. (b) Reconstructedimage using 3 cm lens.When a passenger is sitting at the rear of the vehicle, the3 cm lens is no longer sufficient for a correct definition ofthe person, because while the δt is 53mm for driver, forthe passenger it is 131mm, due to R2=130 cm. In this case,a smaller beamwidth is required, therefore, it means that alarger lens it is necessary, so with Dl= 7 cm the δt=56mmfor passenger. Figure 4 plots the reconstructed images for eachlens.(a) (b) (c)Fig. 4. (a) Real image used in radar simulations. Picture was taken from therear-view mirror. (b) Reconstructed image using 3 cm lens. (c) Reconstructedimage using 7 cm lens, δt=23.8mm at the passenger distance.IV. RESULTSA. Breathing rate measurementsA calibration process was deployed to test the sensitivityof radar in elongation chest movements measuring. A com-mercial metronome was placed 65 cm from the radar withthe sliding weight moving longitudinally at two beat rates, 40and 80 periods/min, corresponding to 0.66Hz and 1.25Hz,respectively. The measured signal was represented over timein Matlab, along with a software-generated sinusoidal signalof the same frequency as beat rates, as shown in Fig. 5.(a) (b)Fig. 5. a) Measured signal of 0.66 Hz. b) Measured signal of 1.33 HzThen, with radar connected to the computer, measurementswere made to determine the distance to the target detectedby the radar. The scenario is the same depicted in Fig. 2,a horizontal scan was carried out that covers the interior ofthe car. The received data is processed in Matlab and thenplotted in terms of the received power and distance while theradar is scanning the interior of the vehicle. Fig. 6a, shows thereceived signal when nobody is in front the radar, the detectedpeaks are due to the seat of the vehicle. The Fig. 6b, show thepeak produced by the presence of the driver inside the car.Once the radar has been calibrated, breathing measurementshave been carried out with a human subject. The first experi-ment consists of detecting and measuring respiration when theradar is fixed in front of the subject at a distance of 65 cm.Fig.7, shows the acquired signal from a experiment where thesubject was instructed to normally breath during 20 seconds,stops for 10 seconds, and continues until arrive at 60 seconds.B. Numerical simulations for elongation modes detectionUsing a real photo of subjects 1 and 2, contours thatrepresent the elongation of the chest were plotted. Then,(a) (b)Fig. 6. (a) Signal of the radar without passenger. (b) Received signal of thedriverFig. 7. Breathing rate of a humanthe image has been subdivided into cells according with thenumber of modes defined. The 120GHz radar beamwidth hasto be of comparable size of the cell of elongation mode, forthis reason, three lens diameter where tested, 3, 5 and 10 cm.The elongation modes representation is achieved by measuringthe distance of each quadrant and placing the information ina intensity matrix. Figure 8, shows the result of numericalsimulations, where the lower thoracic mode is evaluated..(a) (b)(c) (d)Fig. 8. (a) Real image used in radar simulations. Picture was taken from therear-view mirror. Reconstructed image using 3 cm (b), 5 cm (c), and 10 cm(d) lensesV. DISCUSSIONDifferent types and patterns of breathing are the result ofthe movement of several muscles. Normal breathing movesthe abdomen and lower thorax region, so a 2-mode elongationmodel might be enough to characterize breathing, howeverin men the chest sizes is 20% larger than women [12], andduring deep breathing while the excursion is greatest in theupper thorax of females, for males is greatest in the abdominalregion, therefore a 3-mode elongation system would be moresuitable for use inside the vehicle.VI. CONCLUSIONSBased on scientific review, three vertical modes of chestelongation can be used to determine patterns or types ofbreathing in people. Elongation modes can be generated usingradar to measure the distance and frequency of motion of thechest and abdomen.ACKNOWLEDGEMENTSThis work was supported by the Spanish “Comision Inter-ministerial de Ciencia y Tecnologia” (CICYT) under projectsTEC2016-78028-C3-1-P and MDM2016-O6OO; Catalan Re-search Group 2017 SGR 219; and ”Secretarı́a Nacionalde Educación Superior, Ciencia, Tecnologı́a e Innovación”(SENESCYT) from the Ecuadorian government.REFERENCES[1] M. A. Cretikos, R. Bellomo, K. Hillman, J. Chen, S. Finfer, andA. Flabouris, “Respiratory rate: the neglected vital sign,” MedicalJournal of Australia, vol. 188, no. 11, pp. 657–659, 2008.[2] M. Weenk, H. van Goor, B. Frietman, L. J. Engelen, C. J. vanLaarhoven, J. Smit, S. J. Bredie, and T. H. van de Belt, “Continuousmonitoring of vital signs using wearable devices on the general ward:pilot study,” JMIR mHealth and uHealth, vol. 5, no. 7, p. e91, 2017.[3] A. M. Chan, N. Selvaraj, N. Ferdosi, and R. 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In-cabin 120 GHz radar system for functional human breathing monitoring in a 3D scenario

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In-cabin 120 GHz radar system for functional human breathing monitoring in a 3D scenario

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