Fever is a common symptom of many infections e.g. COVID -19 in the ongoing pandemic, 16 keeping monitoring devices like thermometers in constant demand. Recent technological advance- 17 ments in thermometers have the infrared (IR) thermometers as the thermometer of choice for screen- 18 ing multiple individuals in a contactless manner. Yet, even so, the measurement accuracy of such 19 thermometers is affected by many factors including the distance from the volunteer’s forehead, im- 20 purities (such as sweat) and the location me asured on the volunteer’s forehead. To overcome such 21 factors, we describe the assembly of an Arduino -based digital IR thermometer with distance correc- 22 tion using the MLX90614 IR thermometer and HC -SR04 ultrasonic sensors. Coupled with some anal- 23 ysis of these factors, we also found ways to programme compensation methods for the final as- 24 sembled digital IR thermometer to provide more accurate readings and measurements. 25 Keywords: Infrared; Arduino; Nano; Contactless thermometer; H C-SR04; MLX90614 26 27 1. Introduction 28 Early methods of measuring body core temperature utiliz ing contact mercury ther- 29 mometers are replaced by the safer and more convenient electronic thermometers at the 30 sublingual, armpits, ear canals, and in some rare occasions, the rectum and axillary for 31 core temperature accuracy [1]. Many of the se surface measurement sites , specifically the 32 temporal and central forehead, reflect lower reading s than the more internal sites such as 33 the tympanic temperature readings - the current gold standard to represent the body core 34 tempe rature [2], especially given the impracticality of rectal/anal temperature takings. 35 For disease screening as in the ongoing pandemic, rapid temperature measurements 36 of many individuals quickly and safely without allowing the thermometer to be a vector 37 of pathogen transfer is crucial , thus making contact infeasible, ruling out many of the 38 above measurement sites . 39 Infrared (IR) thermometers can fulfil this gap by measur ing the surface temperature 40 without direct contact. The IR sensors do this by detecting the am ount of thermal or black - 41 body radiation emitted by the object and these thermome ters are now commonly used in 42 clinical practices [3], and now almost routinely during the pandemic for self -monitoring 43 and screening at border customs and entrances of public places . 44 45 2 of 14 Typically, IR thermometer casings are manufactured by the expensive injection 46 molding (due to mold production and tooling c osts), producing significant waste mate- 47 rial. The increased adoption of three -dimensional (3D) printing technology has revolu- 48 tionized prototyping and reduce d cost by shortening the lead time to manufacture with 49 also significantly less waste. Coupling with 3D printing, the use of ‘off -the-shelf’ micro- 50 controller kits s uch as Arduino, Raspberry Pi, and Micro:bit can now allow novel elec- 51 tronic products to be cost -effectively assembled, even by non -engineers in non-commer- 52 cial settings . It is with such enabling technology that even home -made measurement de- 53 vices e.g. spectrophotometer [4,5] , including those for psychology [6] research use, can be 54 made easily. 55 While thermometers can be easily assembled , IR thermometers are often thought to 56 be less reliable [7] than traditional contact thermometers. Non-contract infrared thermom- 57 eters were previously reported to have a sensitivit y between 4.0% to 89.6% , specificity 58 between 75.4% to 99.6% , and a positive predictive value between 0.9% to 76.0% [8]. There 59 are in fact, recommendations for it to be utilized twice at hospital gantries [9], given that 60 temperature measurements using IR thermometers are highly prone to external interfer- 61 ences by surrounding temperature s, relative humidity [10], the site of measurement [11], 62 and the presence of oil (sebum) and sweat o n the forehead [12] as well as other factors in 63 the immediate environment [13]. Apart from these innate factors, intrinsic human physi- 64 ological factors such as fever [14] or exercise [15] – both of which can produce sweat to 65 affect measurements and with further confounding influence from the surrounding tem- 66 perature and humidity that can affect blood supply to the skin surface which by itself is 67 generally lower than the expected body temperature [16,17] . Due to these drawbacks, 68 many IR thermometers , especially self -assembled ones can be inaccurate as they lack am- 69 bient temperature and distance sensors [7] for compensation. 70 At the point of writing, many IR sensors have in -built radiation emitter and receiver 71 devices [18] and can be used to provide reliable measurement s at predetermined dis- 72 tance s. Yet, with the above issues, the onus is still on the user before accura te measure- 73 ments . 74 To help alleviate the above problems, we describe the design and assembly of a low - 75 cost IR thermometer with distance and environmental temperature sensing capabilities to 76 provide more accurate measurements. Experiments were conducted to validate compen- 77 sation adjustments mad e in the algorithm as well as the effects of measurements on dif- 78 ferent locations of the forehead . 79 2. Materials and Methods 80 2.1. Components and Specifications 81 Arduino Nano (HWA YEH , Shenzhen , China) , ultrasonic sensor (HC-SR04 ) [19], in- 82 frared sensor (MLX90614 ) [20] and OLED display (SSD1306 ) [21] were used. A factory 83 calibrated MLX90614 infrared sensor suitable for a wide range of temperature s between - 84 40 to 85°C for the ambient temperature and -70 to 1030 °C for the target object temperature , 85 providing the average temperature of all objects within the field of view (FoV) of the sen- 86 sor, and providing a standard accuracy of 0.5°C around room temperature. The Ultra sonic 87 Sensor HC -SR04 emit s a 40 kHz ultrasound and computes the distance based on the time 88 taken to detect the ultrasound wave reflected off an object. An SSD1306 organic light - 89 emitting diode (OLED) display is incorporated to display the readings. 90 91 2.2. As sembly of Infrared Thermometer 92 The design and development of the thermometer in this project were adapted and 93 modified from online instructions [22] and comprises of two main aspects: 1) the physical 94 form and mechanical assembly 2) the electronic circuit, including the firmware . 95 96 2.2.1. Physical Assembly 97 3 of 14 Figure 1 a shows the physical design with the top half ( Figure 1, in yellow) housing 98 the components : – IR sensor, ultrasound sensor, Arduino Nano, LED bulbs and OLED 99 display. The bottom half (Figure 1, in black) comprises of the battery holder and a push 100 button switch. The shell ( top and bottom half ) was 3D printed with polylactic acid (PLA) 101 filament ( 3D AURA Pte Ltd , Singapore) using a Prusa i3 Mk3 3D printer. 102 103 Figure 1. (a) Back view of prototype segmented into top (yellow) and bottom (black) half with color differentiation for display pur- 104 poses. (b) Front view of prototype displaying the IR sensor and ultrasound sensor in the top half . The b ottom half of the device 105 includes the push butto n switch and battery holder. 106 2.2.2 . Circuitry Design and Implementation 107 The Arduino Nano [23] microcontroller to which the copper wires from th e sensor 108 pins of the ultrasonic sensor, IR sensor, OLED and push button switch were soldered to 109 are as shown in Figure 2 with a 9V battery supplying 3.3 to 5V to the circuit (Figure 2) . 110 111 112 Figure 2. A circuit schematic of the assembled digital IR thermometer consisting of : 1) ultrasonic sensor HC -SR04, 2) push button 113 switch, 3) Arduino Nano board, 4) OLED display SSD1306, and 5) IR temperature sensor MLX90614 114 2.3. Programming Arrangement 115 Arduino IDE 1.8.13 softw are is used to program t he thermometer . Holding down the 116 push button activates measurement within 2 -4 centimeters (range recommended by the 117 4 of 14 sensor manufacturers) from the volunteer forehead . Five readings from the ambient and 118 surface body temperature would be made and the average shown . Simultaneously, the 119 ultrasonic sensor detects the distance from the target area and calculates the average of 5 120 readings . With the inputs of distance and temperature to the algorithm, the compensated 121 reading from the algorithm would be displayed on the mono color, 128×64 pixels OLED 122 module (Figure 3). 123 The compensation adjustment equation was derived from the regression analysis of 124 the relationship between the oral temperature values and the measured values. Compen- 125 sated values by the IR thermometer wer e used as the dependent value y while the meas- 126 urement values by the IR thermometer and ambient temperature were each viewed as 127 independent variables. 128 129 Figure 3. OLED display illustrating the distance to the target surface, measured surface tempera- 130 ture and the measurement status. 131 2.4. Sensor calculations 132 2.4.1 Infrared Sensor 133 The equations and calculatio ns of the target temperature are based on a previous 134 work by others [24]. For precise measurement of the absolute temperature of the target 135 (Tk), the device temperature (Tdev) should be kept small with a stable ambient temperature 136 (Tamb). To compensate for the proximity effects, a distance -to-spot ratio (D/S Ratio) is built 137 in the algorithm . Specifically, the area measured increases as the distance increases. The 138 selected IR temperature sensor has a fie ld of view of 80 °. This translates to a D/S Ratio of 139 1:1.68 . Setting the average height of a human forehead of 58.3 mm as the constraint [25], 140 the maximum horizontal distance that the IR temperature sensor can reliably measure the 141 temperature of the target is approximately 4 cm. Beyond this distance, flanking areas of 142 the forehead would also be measured, affecting the accuracy. 143 2.4.2. Ultrasound Sensor 144 The ultrasound sensor consists of a transmitter sending an ultrasound wave and a 145 receiver detecting the reflected wave by the targeted physical o bject. The time taken be- 146 tween the transmission and detected wave is registered for the calculation of the distance 147 from the speed of ultrasound wave s at 330 m/s by the Arduino Nano. 148 2.4.3. Experimental Setup 149 Ethical review and approval were waived for this study, due to the low risk and 150 anonymized data collection under A*STAR IRB Reference Number: 2021 -006 for recruit- 151 ment of five volunteers (aged 21 and above) with anonymized informed consent. To 152 5 of 14 ensure anonym ity, a random volunteer ID between 1 to 1000 was generated for each vol- 153 unteer entry. 154 Three experiments were performed for this study. Each experiment was conducted 155 in an air -conditioned environment of 20 to 22 °C for a relatively constant Tamb. Volunteers 156 were asked to avoid high intensity activities before the experiments, and temperature 157 measurements were taken five minutes after acclimatization to the test environment. Ster- 158 ilized Omron digital thermometer MC -343F was used to measure oral temperatures that 159 was also set as the target point for compensation adjustment . Temperature measurements 160 of the volunteers’ forehead were taken in triplicates. 161 In the first experiment, the IR thermometer was u sed to measure the volunteers’ fore- 162 head temperatures at three different locations (left, right and center of forehead) at vary- 163 ing distances from the forehead (2.0 to 4.0 cm, at 0.5 cm intervals). The range of 2 to 4 cm 164 is based on the minimum and maximum a llowable horizontal distance that the IR tem- 165 perature sensor can accurately measure (2 - 4 cm) as per manufacturer’s recommenda- 166 tions. In the second experiment, water was sprayed onto volunteers’ forehead using a 167 spray bottle to simulate wetness from sweat. 168 The IR and oral temperature readings from the first experiment set were used for 169 compensation adjustments and stored . The calibrated IR thermo meter was then used to 170 measure the center and lateral forehead temperature s of volunteer s and to test its perfor- 171 mance and deviation from oral temperature . Data from each experiment were plotted 172 with the distance against the temperature. 173 2.4.4. Statistical Analysis 174 The mean and standard deviations of temperature readings were calculated and an- 175 alyzed using Microsoft Excel (version 15.0) and expressed as a linear regression showing 176 the R2 value. One-way ANOVA (Analysis of Variance) followed by Dunnett’s multiple 177 comparisons tests were performed using R software (version 3.6.2) [26] to compare mean 178 recorded temperatures of each volunteer relative to the control (oral temperature). 179 Cronbach’s α was set at p < 0.05. 180 3. Results 181 3.1. Performance of IR thermomter on forehead 182 Prior to compensation adjustments of the IR thermometer, an inverse correlation be- 183 tween the temperature readout and distance from the forehead was measured for all five 184 volunteers at all three forehead locations (left, right and center, see Figure 4). 185 186 187 6 of 14 188 Figure 4. Measured forehead temperatures against distance between 2 - 4 cm for each volunteer taken on the a) left of the fore- 189 heads, (b) right of forehead and (c) center of forehead prior to compensation adjustments . Error bars represent the standard devia- 190 tion fro m triplicates. 191 The variation of the mean temperature measurements between the center and lateral 192 areas of the forehead were calculated to be between -0.69 to 0.55 °C (Table 1) . The center 193 is taken as the most accurate region for compensation, in view of the stronger correlative 194 relationship between the recorded temperatures and distance. 195 Table 1 . Variation s in forehead temperature measured from the center and lateral positions of the forehead of five volunteers 196 using o ur IR thermometer prior to compensation adjustments . 197 Volunteer Temperature difference between center of fore- head and left forehead (°C) Temperature difference between center of fore- head and right forehead (°C) 1 0.13 ± 0.44 0.31 ± 0.34 2 -0.16 ± 0.35 -0.51 ± 0.31 3 0.04 ± 0.27 -0.69 ± 0.27 4 -0.51 ± 0.34 0.00 ± 0.56 5 -0.03 ± 0.23 0.55 ± 0.40 3.2. Performance of IR thermomter on wet forehead 198 Variation s in the mean temperature me asurements between the wet and dry fore- 199 head ranged from 3.06 ± 0.00 to -2.85 ± 0.02 °C (Table 2 , Table S1 ). Generally, the mean wet 200 forehead temperatures were found lower than the dry forehead temperatures, with very 201 few exceptions. This finding confirms the concern where perspiration or wet weathers 202 may result in false negatives of fever during screening. 203 7 of 14 Table 2 . Difference between dry and wet forehead temp eratures on the respective locations from 2 – 4 cm . Positive value implies 204 that the dry forehead registers a higher temperature. 205 Distance (cm) Volunteer Difference between dry and wet (dry -wet) forehead (°C) Center Left Right 2.0 1 1.34 ± 0.01 -2.85 ± 0.02 1.57 ± 0.01 2 1.85 ± 0.08 0.80 ± 0.07 2.35 ± 0.25 3 2.49 ± 0.03 2.01 ± 0.06 0.34 ± 0.05 4 1.89 ± 0.04 1.41 ± 0.02 0.96 ± 0.19 5 1.03 ± 0.06 1.55 ± 0.07 -0.18 ± 0.22 2.5 1 1.69 ± 0.05 2.20 ± 0.01 2.81 ± 0.27 2 1.58 ± 0.01 0.28 ± 0.01 0.26 ± 0.07 3 2.07 ± 0.02 1.55 ± 0.01 -0.35 ± 0.18 4 2.33 ± 0.05 1.34 ± 0.08 2.55 ± 0.17 5 0.51 ± 0.89 0.72 ± 0.01 -0.24 ± 0.22 3.0 1 1.37 ± 0.06 1.86 ± 0.05 2.00 ± 0.01 2 2.60 ± 0.12 -0.04 ± 0.00 1.47 ± 0.04 3 2.36 ± 0.16 0.98 ± 0.01 1.26 ± 0.05 4 1.79 ± 0.03 1.47 ± 0.04 0.90 ± 0.03 5 1.66 ± 0.06 1.73 ± 0.02 1.32 ± 0.55 3.5 1 1.87 ± 0.02 2.83 ± 0.08 2.75 ± 0.01 2 1.54 ± 0.00 0.00 ± 0.02 1.31 ± 0.02 3 0.77 ± 0.09 0.82 ± 0.23 1.01 ± 0.22 4 1.73 ± 0.00 2.13 ± 0.19 1.80 ± 0.23 5 2.07 ± 0.00 0.76 ± 0.01 0.76 ± 0.01 4.0 1 1.16 ± 0.06 2.83 ± 0.02 3.06 ± 0.00 2 0.80 ± 0.06 0.09 ± 0.01 1.49 ± 0.03 3 1.09 ± 0.05 -0.29 ± 0.17 0.36 ± 0.07 4 1.69 ± 0.02 1.10 ± 0.03 1.10 ± 0.18 5 1.93 ± 0.11 1.49 ± 0.01 0.94 ± 0.03 3.3. Compensation adjustments and testing of IR thermometer 206 Linear regression models were applied on the measured readings for each volunteer 207 (Figure 5). The compensation adjustments lines for the temperature (y) against the dis- 208 tance (x) over two different ranges (2 - 3 cm and 3 - 4 cm, respectively) w ere obtained, as 209 shown in Fig.7. The data points between 2 to 3 cm are used to generate a best -fit straight - 210 line equation y = -0.3107 x + 34.152 , and a coefficient of determination R2 = 0.998. Similarly, 211 a best -fit straight -line equation of y = -0.3573x + 33.612 is obtained using the measured 212 readings from 3 to 4 cm . With the R2 close to 1 in both linear regression models , the sensor 213 used in this experiment is shown to have high reproducibility for measuring temperature 214 (based on the IR temperature sensor) and distance. 215 216 8 of 14 217 Figure 5. Combined trend lines for all the volunteers between 2cm to 3cm (in black) and between 3cm to 4cm (in red) 218 3.4. Test Performance of the Optimized IR temperature System 219 The performance of our implemented control system with distance -sensing capabil- 220 ities was tested factoring the gradient into the algorithm. For compensation , a fixed arbi- 221 trary number was added to the raw temperature outputs , given that this would di ffer 222 across various sources of manufactured IR sensors. 223 Following compensation adjustments , experiments were repeated with compensa- 224 tion applied to the mea surements. We found only volunteer 4’s left forehead to have sig- 225 nificant differences (of an average 1.36 °C, p < 0.0 01) from the oral temperature using Dun- 226 nett’s post -hoc test . Across five volunteers, the mean temperature measured at the center 227 of the forehead (over the left and right) is closer to the mean oral temperature ( Figure S1 ). 228 Thus, subsequent measurements were performed based on the center of the forehead tem- 229 peratures. 230 Based on the ANOVA results, there was no statistically significant difference in tem- 231 perature measurement from the center or laterals of the forehead against the oral temper- 232 ature ( Figure S1 ). However, Dunnett’s post -hoc test showed that the p -value differen ces 233 between the measurements from the center of forehead to control was higher than that of 234 measurement of laterals to control across all volunteers. Between 2 and 4 cm, measure d 235 temperatures were within a range of ±0.29 °C of their oral temperature (Figure 6). De- 236 spite the presence of outlier s, the recorded temperature displayed a standard deviation of 237 ±0.3°C (Volunteer 3) from the oral temperature . 238 9 of 14 239 Figure 6. Recorded temperatures and the oral temperature for each volunteer. For each volunteer, the dots represent individual 240 data points in the respective distance from the foreheads. 241 4. Discussion 242 We set out to assemble and calibrate an Arduino based thermometer capable of com- 243 pensating for varying measurement distances from the forehead for more accurate con- 244 tactless body temperature measurement. 245 With the availability of off -the-shelf electronic sensors and microcontroller kits, it is 246 possible for non-engineers to assemble their own devices to meet times of shortages such 247 as that experienced by the authors when self-monitoring measures were implemented 248 during the 2020 COVID -19 pandemic. While it will take significant time for such self-as- 249 sembled thermometers to be approved by regulatory bodies and passing required calibra- 250 tions as required for commercial devices , at times of extended shortages, such self -assem- 251 bled devices allow an immediate patch solution also known in Hindi as “Jugaad”. Ye t, the 252 potential problem arising from inaccurate measurements can have dire effects in infection 253 control measures with false negatives. In recognition of such, , we have dec ided to release 254 our results for community tweaking of their own assembled thermometers. 255 4.1. Assembly of the Arduino -based thermometer 256 We adopted Arduino for its ease of use and variety of sizes for assembly. While 257 Scratch programming with Micro:bit [27] may be simpler in terms of programming, it is 258 foreseen that its larger size and pin connectivity poses a problem for small handheld ther- 259 mometer s. Size is also a concern f or the more powerful alternative Raspberry Pi [28]. Bal- 260 ancing these considerations, we adapted an online DIY thermometer assembly guide, 261 using Arduino Nano to connect to the available devices. 262 To reduce measurement error caused by improp er targeting at the forehead, we pro- 263 grammed the thermometer to take five readings and display the average. Similarly, the 264 sensors allow for ambient temperature sensing, that together with our added ultrasound 265 module for distance measurements, allow for compensations to be applied once the effects 266 of some common parameters such as forehead location, wetness, and distance of meas- 267 urement, are established. 268 4.2. Differences in temperature between center and laterals of the for ehead 269 We first sought to investigate if there were differences on the surface temperature 270 between the center and the laterals of the forehead. Differences between the center and 271 laterals of the forehead were observed and persisted even after compensation adjustments 272 10 of 14 (Figure S1 ). This difference in mean temperature are also attributed to the physiological 273 phenomenon explained by the individual’s unique forehead temperature distribution as 274 determined through simulation software [29]. It should be noted that the IR sensor in our 275 assembled thermometer is commonly used to measure the surface temperature of the skin 276 and is unable to determine the muscle temperature near the s uperficial temporal artery – 277 a major artery located beneath the vascular bed of the head’s skin [30]. While the differ- 278 ences between the forehead locations are small and perhaps inconsequential in differenti- 279 ating high fevers above 38 °C, our studies show that using the IR thermometer for the cen- 280 ter of the forehead is the most accurate and consistent. Given that this is a specific forehead 281 locale variable, compensation mechanisms are not easily programmed into the device so 282 the onus falls upon the user. 283 4.3. Wetness of forehead 284 In the second experiment set, the mean wet forehead temperatures were typically 285 lower than the dry forehead temperatures with exceptions . Consistent with a previous 286 study where a high performance t hermal imaging camera also detected lower tempera- 287 ture at various parts of a perspiring body [31], temperature measurements taken with an 288 IR thermometer on wet foreheads can be inaccurate . However, there are no compensation 289 measures that we could incorporate given that we do not have the means of incorporating 290 wetness detection. Therefore, compliance to the correct practice of measuri ng the right 291 target location and the surface being dry , is required to avoid false negatives . 292 4.4. Performance of calibrated IR thermometer 293 Our improved IR thermometer recorded an ave rage temperature within ± 0.29 °C of 294 the volunteers’ oral temperature (Figure 6). As measurements for oral temperature are 295 widely used to non -invasively measure the body temperature, measurements of the fore- 296 head temperature can be used to establish a thre shold in the screening for fever. The IR 297 thermometer obtained better precision compared to alternative and more expensive non - 298 contact IR devices and was certainly more accurate with distance compensation . In a sep- 299 arate study, tympanic and forehead temperat ures taken by a BRAUN IRT -3020 were 300 measured with an error range of ± 0.286 ° C and ± 0.392 ° C [32]. Another study showed 301 a tympanic and forehead temperature error s of ± 0.37 °C and ± 0.36 °C respectively 302 [33]. However, other co ntact devices such as the rectal thermometer, with a small error 303 range of ± 0.05 °C [34] outperformed our improve d thermometer. Still, our device costs 304 only a fraction of commercial IR thermometers and was sufficiently accurate to be consid- 305 ered as a low -cost alternative (~US$7.50, S$10) to current entry level IR thermometers 306 (>S$80) in the market. This non -contact device is more convenient than that of tympanic 307 or rectal thermometers. 308 To improve accuracy , there have been various establishe d methods to calibrate IR 309 thermom eters [35,36] , and for our purposes of distance compensation to improve the ther- 310 mometer, we found that it did improve accuracy as with others [36]. 311 For clinical grade temperature measurements of the forehead lateral areas, contact 312 type thermometers are recommended [37] where its sensing element - a thermistor, must 313 touch the skin of the forehead or be inserted into the muscle. While contact type thermom- 314 eters are recommended over non -contact types, it is not widely adopted because IR ther- 315 mometers have greater sensitivity and specificity over contact temporal thermometers for 316 temperatures >37.5 °C [38] . In working towards commercial use, it may be useful to use 317 a second order equation for compensation adjustment from our two first -order equation s 318 as well as bearing in mind potential revisions on the International Temperature Scale of 319 1990 (ITS -90) for better reproducibility [39] along with the use of smart materials to make 320 the thermometer casings [40]. 321 5. Conclusions 322 Forehead temperature measurement using a n infrared thermometer plays an im- 323 portant role to rapidly screen for fever to identify the infected. Its performance and 324 11 of 14 precision for forehead temperature screening was studied together with the design and 325 implementation of a n improved IR temperature sensor -based system with distance sens- 326 ing capabilities. 327 While minimal, t emperature differences between the center and laterals of the fore- 328 head highlight the importance of the user in targeting the right area - center of the fore- 329 head. 330 Since we have also shown that perspiration and water on the forehead can cause a 331 significant decrease in the detected temperature, but unable to make programmed com- 332 pensations, it is necessary for user to take precaution in en suring that the forehead be dr y 333 and the skin surface temperature restored before accurate measurements can be taken. 334 After implementation of a range sensor, the preliminary results show that our IR 335 thermometer to achieve a more accurate forehead temperature measurement over a short 336 distance range compared to current infrared thermometers without range sensors. This is 337 achieved by obtaining an optimized algorithm from experimentally plotted linear regres- 338 sion lines. It is observed that the measured temperatures were well within a ± 0.29 °C 339 variation of their oral temperature over the distance of 2 to 4 cm – achieving similar per- 340 formance to commercial thermometers. Therefore, it could be concluded that the designed 341 control system has high validity to measure human forehead temperatures at varying dis- 342 tances. 343 Supplementary Materials: The follow ing are available online at www.mdpi.com/xxx/s1, Figure S1: 344 Statistical difference between the recorded average temperatures for the five volunteers , Table S1: 345 Measured dry and wet forehead temperature against distance between 2 - 4 cm of the five volun- 346 teers. 347 Author Contributions: Conceptualization, S.K.E.G.; m ethodology, N.W. -J.G., J.J.P., resources, S. 348 C.L., J. J. -W.C., C. T. Y. L. ; formal analysis, N.W. -J.G., J.Y.Y. ; investigation, N.W. -J.G., J.J.P., J.Y.Y., 349 B.-J.J.A. ; writing —original draft preparation, N.W. -J.G.; writing —review and editing, S.K.E.G., 350 J.Y.Y. ; supervision, S.K.E.G. All authors have read and agreed to the published version of the man- 351 uscript. 352 Funding: This research received no external funding . 353 Instituti onal Review Board Statement: Ethical review and approval were waived for this study, 354 due to the low risk and anonymized data collection under A*STAR IRB Reference Number: 2021 - 355 006. 356 Informed Consent Statement: Informed consent was obtained from all volunteer s involved in the 357 study. 358 359 Data Availability Statement: In this section, please provide details regarding where data support- 360 ing reported results can be found, including links to publicly archived datasets analyzed or gener- 361 ated during the study. Ple ase refer to suggested Data Availability Statements in section “MDPI Re- 362 search Data Policies” at https://www.mdpi.com/ethics. You might choose to exclude this statement 363 if the study did not report any data. 364 Acknowledgments: The authors thank Anthony Chong f or help in coordination. SKEG thanks 365 Ebenezer for the behind the scenes help in the work. 366 Conflicts of Interest: The authors declare no conflict of interest. 367 368 369 370 371 372 373 374 12 of 14