High-precision infrared body temperature measurement device and method based on age segmentation

Abstract

This invention discloses a high-precision infrared body temperature measurement device and method based on age segmentation. It includes multiple sets of bias filter circuits corresponding to different age groups. The MCU temperature calculation module outputs a corresponding channel selection signal to the control terminal of an analog selection switch based on the read range selection signal. The analog selection switch selectively connects the output of the bias filter circuit corresponding to that range selection signal to its common output terminal based on the channel selection signal. The common output terminal is connected to the ADC sampling terminal of the MCU temperature calculation module. The MCU temperature calculation module also processes the sampled digital signal to calculate and output the body temperature value. This effectively solves the technical problem of existing infrared thermometers, which use a single fixed analog front-end circuit and cannot simultaneously accommodate the amplitude and bandwidth differences of body temperature signals from different age groups, resulting in weak signals from newborns being drowned out by noise and distorted broadband signals from infants.

Description

Technical Field

[0001] This invention relates to the field of infrared body temperature measurement devices, and in particular to a high-precision infrared body temperature measurement device and method based on age segmentation. Background Technology

[0002] An infrared thermometer is a non-invasive electronic device that measures body temperature by detecting the infrared radiation emitted by the human body. It has gained increasingly widespread application in areas such as home healthcare, pre-screening and triage in medical institutions, and epidemic prevention and control in public places. Especially in recent years, with the frequent occurrence of global public health events and the increasing public awareness of health, infrared thermometers have become one of the essential medical and health products in households.

[0003] Infrared thermometers typically use a thermopile sensor as the detection element. This sensor converts the received infrared radiation into a weak voltage signal, with a typical output amplitude in the range of tens of microvolts to several millivolts. This weak signal is then amplified by an analog amplifier circuit, filtered to remove noise and interference, and then converted into a digital signal by an analog-to-digital converter (ADC). Finally, a microcontroller (MCU) runs a temperature measurement algorithm, incorporating ambient temperature compensation, emissivity correction, and other calculations to output the final human body temperature value.

[0004] However, existing infrared thermometers generally suffer from a long-standing technical problem that has not been effectively solved: the same infrared thermometer cannot achieve high-precision temperature measurement in people of different age groups.

[0005] The root of this technical problem lies in the fact that people of different ages have different physiological characteristics, which causes the physical properties of their body temperature signals to change accordingly. However, existing solutions generally use a single sampling circuit and algorithm to adapt to all users.

[0006] Specifically, newborns aged 0 to 3 months have the following unique physiological characteristics: their thermoregulatory center is not fully developed, their metabolic rate fluctuates significantly, their body surface area to weight ratio is much higher than that of adults, and they lose heat quickly. These physiological characteristics are reflected in infrared thermometry signals as follows: the amplitude of the effective body temperature signal is extremely low, typically only 40% to 60% of that of people over 36 months old; the signal changes extremely slowly, with an effective bandwidth of only 0.008 Hz to 0.3 Hz, which is a typical ultra-low frequency, slowly changing signal; at the same time, this group is extremely sensitive to the ambient temperature, and even small fluctuations in the ambient temperature can introduce significant baseline drift in the temperature measurement signal.

[0007] In contrast, infants aged 3 to 36 months exhibit distinctly different signal characteristics: children in this age group are active and uncooperative, making it difficult for them to remain still during measurement. Therefore, their infrared temperature measurement signals contain a large amount of transient components caused by limb movements, breathing fluctuations, and probe contact jitter, with an effective bandwidth ranging from 0.01 Hz to 5 Hz, far wider than the signal bandwidth of newborns. Furthermore, the amplitude of motion artifacts in this age group is often much larger than the true body temperature signal amplitude, making it a major source of interference with measurement accuracy.

[0008] Children over 36 months old and adults have mature thermoregulation systems and are highly cooperative during measurement. Their infrared temperature measurement signals have the largest and most stable amplitudes, with a moderate effective bandwidth (approximately 0.01Hz to 2Hz) and relatively balanced interference types.

[0009] Faced with the three user groups with the above-mentioned distinct characteristics, existing infrared thermometers generally adopt the following two solutions, but both have insurmountable drawbacks: The first approach uses a fixed analog front-end circuit (fixed gain, fixed filter bandwidth) to suit all age groups. This approach inevitably faces a performance trade-off: if the circuit gain and bandwidth are set to suit the wide bandwidth requirements of infants (0.01Hz-5Hz), the excessively wide passband will introduce a large amount of out-of-band high-frequency interference for newborns, significantly reducing the signal-to-noise ratio. Simultaneously, the gain will be insufficient to boost the weak signals of newborns to the optimal quantization range of the ADC, resulting in significant quantization noise. Conversely, if set to a narrowband high-gain mode suitable for newborns, the high-frequency components of the transient effective signal will be filtered out during infant measurements, causing a lengthened signal rise time, phase distortion, and severe measurement deviations. This trade-off is determined by the physical properties of the single circuit; no amount of back-end digital processing can fundamentally recover the signal accuracy lost in the analog front-end.

[0010] The second approach involves using a programmable gain amplifier (PGA) and an adjustable filter, with circuit parameters modified via software configuration. However, the cost of PGAs and adjustable filters is significantly higher than that of fixed circuits, and their adjustable range and accuracy are still limited by the chip design itself, making it difficult to simultaneously meet the two extreme requirements of extremely narrow bandwidth for newborns and extremely wide bandwidth for infants and young children.

[0011] Furthermore, in terms of backend algorithms, existing technologies generally employ a common compensation model and body temperature grading standard. For example, most products use a linear core body temperature compensation model based on adult clinical data, ignoring differences in the emissivity of newborn skin, the thermal conductivity of subcutaneous tissue, and the nonlinear characteristics of the surface-core body temperature difference with age. This leads to systematic biases in measurement results for young children. Regarding body temperature grading, existing products uniformly use 36.0℃ to 37.2℃ as the normal body temperature range. However, clinical pediatrics clearly points out that the normal body temperature range for newborns (0 to 3 months) and children (3 to 36 months) differs from that of adults. Using adult standards can lead to misdiagnosis of a large number of healthy newborns and children, causing unnecessary anxiety and medical visits.

[0012] Therefore, a new technical solution needs to be researched to address the above problems. Summary of the Invention

[0013] In view of this, the present invention addresses the deficiencies of the existing technology, and its main objective is to provide a high-precision infrared body temperature measurement device and method based on age segmentation. It effectively solves the technical problem that existing infrared thermometers, due to their use of a single fixed analog front-end circuit, cannot simultaneously take into account the amplitude and bandwidth differences of body temperature signals in different age groups, resulting in weak signals from newborns being submerged by noise and effective broadband signals from infants being distorted.

[0014] To achieve the above objectives, the present invention adopts the following technical solution: A high-precision infrared body temperature measurement device based on age segmentation includes: An age range selection module is used to generate a range selection signal representing the age group to which the target user belongs; An infrared temperature acquisition module is used to acquire and output the raw infrared signal from the target user; At least two sets of bias filter circuits are provided, each set corresponding to an age group. The inputs of all bias filter circuits are connected to the output of the infrared temperature acquisition module to receive the raw infrared signal. Each set of bias filter circuits has a preset bias voltage and filtering parameters that are different from each other and are matched with the age group. These are used to condition the raw infrared signal in the analog domain and output a conditioned signal that matches the signal characteristics of the age group. An MCU temperature calculation module is connected to the age range selection module to read the range selection signal. An analog selection switch has a control terminal, at least two input terminals, and a common output terminal. The at least two input terminals are respectively connected to the common output terminal of the at least two sets of bias filter circuits. The control terminal is connected to the output terminal of the MCU temperature calculation module. The MCU temperature calculation module outputs a corresponding channel selection signal to the control terminal of the analog selection switch based on the read gear selection signal. The analog selection switch selectively connects the output terminal of the bias filter circuit corresponding to the gear selection signal to its common output terminal based on the channel selection signal. The common output terminal is connected to the ADC sampling terminal of the MCU temperature calculation module. The MCU temperature calculation module is also used to process the sampled digital signal to calculate and output the body temperature value.

[0015] As a preferred embodiment, the at least two sets of bias filter circuits include: The first bias filter circuit, corresponding to newborns aged 0 to 3 months, has a cutoff frequency of no more than 1Hz; The second bias filter circuit, corresponding to infants aged 3 to 36 months, has a cutoff frequency higher than that of the first bias filter circuit but not higher than 5Hz. The third bias filter circuit, corresponding to people aged 36 months and above, has a cutoff frequency higher than that of the second bias filter circuit but not lower than 10Hz.

[0016] As a preferred embodiment, the infrared body temperature measuring device further includes a buffer amplifier, the input of which is connected to the common output of the analog selection switch, and the output of which is connected to the ADC sampling terminal of the MCU temperature calculation module.

[0017] As a preferred embodiment, the analog-to-digital converter built into the MCU temperature calculation module has an accuracy of no less than 24 bits.

[0018] As a preferred embodiment, the MCU temperature calculation module pre-stores multiple sets of exclusive temperature measurement algorithms corresponding to each age group; The MCU temperature calculation module is further configured to: automatically call a dedicated temperature measurement algorithm corresponding to the read gear selection signal, and process the sampled digital signal according to the read gear selection signal. The processing includes at least one of the following: a. Calculate body temperature compensation using a compensation model corresponding to this age group; b. Perform digital filtering using digital filtering parameters corresponding to this age group; c. Use the body temperature grading threshold corresponding to this age group for clinical judgment.

[0019] As a preferred option, it also includes: A parameter storage module, connected to the MCU temperature calculation module, is used to store the calibration coefficients and nonlinear compensation parameters corresponding to each age group. When the MCU temperature calculation module calls the dedicated temperature measurement algorithm corresponding to the age group, it reads the calibration coefficient and nonlinear compensation parameter corresponding to the age group from the parameter storage module and uses them to correct the body temperature calculation result.

[0020] As a preferred embodiment, the infrared temperature acquisition module includes: an infrared temperature sensor and an infrared preamplifier circuit, wherein the infrared temperature sensor is connected to the input terminals of all bias filter circuits via the infrared preamplifier circuit.

[0021] A high-precision infrared body temperature measurement method based on age segmentation includes the following steps: S1. Gear selection steps: Obtain the gear selection signal representing the age group of the target user; S2. Signal conditioning steps: The raw infrared signal output by the infrared temperature acquisition module is simultaneously input into at least two sets of bias filter circuits corresponding to different age groups. Each set of bias filter circuits performs analog domain conditioning on the raw infrared signal based on different preset bias voltages and filter parameters that match the age group, and outputs a conditioned signal that matches the signal characteristics of the age group. S3, Channel selection step: The MCU temperature calculation module outputs the corresponding channel selection signal to the control terminal of the analog selection switch according to the acquired gear selection signal, so that the analog selection switch selectively connects the conditioned signal output by the bias filter circuit corresponding to the gear selection signal to its common output terminal. S4. Analog-to-digital conversion step: The MCU temperature calculation module converts the conditioned signal output from the common output terminal into a digital signal; S5. Body temperature calculation steps: The MCU temperature calculation module processes the digital signal, calculates and outputs the body temperature value.

[0022] As a preferred embodiment, after the channel selection step and before the analog-to-digital conversion step, a buffering step is also included: the conditioned signal output from the common output terminal of the analog selection switch is buffered by a buffer amplifier for voltage follower buffering before entering the analog-to-digital conversion step.

[0023] As a preferred embodiment, the body temperature calculation step further includes: S5-1. Based on the acquired gear selection signal, call the exclusive temperature measurement algorithm corresponding to the age group from the pre-stored multiple exclusive temperature measurement algorithms. S5-2. The digital signal is processed using the called proprietary temperature measurement algorithm, and the processing includes at least one of the following: a. performing body temperature compensation calculation using a compensation model corresponding to the age group; b. performing digital filtering using digital filtering parameters corresponding to the age group; c. performing clinical judgment using body temperature grading thresholds corresponding to the age group. S5-3. Output the final body temperature value and clinical judgment result; the clinical judgment result is presented by the color of the body temperature value number or the backlight color of the interface where the body temperature value number is located. The color will be different depending on the clinical judgment result.

[0024] Compared with existing technologies, this invention has significant advantages and beneficial effects. Specifically, as can be seen from the above technical solution, it mainly involves setting up an age-level selection module, an infrared temperature acquisition module, at least two sets of bias filter circuits, an MCU temperature calculation module, and an analog selection switch. The MCU temperature calculation module outputs a corresponding channel selection signal to the control terminal of the analog selection switch based on the read level selection signal. The analog selection switch selectively connects the output terminal of the bias filter circuit corresponding to the level selection signal to its common output terminal based on the channel selection signal. The common output terminal is connected to the ADC sampling terminal of the MCU temperature calculation module. The MCU temperature calculation module is also used to process the sampled digital signal to calculate and output the body temperature value. It can systematically and without compromise match the physical signal characteristics and physiological characteristics of different age groups from the source of analog signal acquisition, breaking the performance ceiling of a single circuit, and achieving high signal-to-noise ratio, high fidelity, and high clinical consistency infrared body temperature measurement across all age groups.

[0025] Furthermore, it can systematically and without compromise match the physical signal characteristics and physiological characteristics of different age groups from the source of analog signal acquisition to the end of digital algorithm processing, breaking through the performance ceiling of single circuits / general algorithms, and achieving high signal-to-noise ratio, high fidelity, and high clinical consistency infrared body temperature measurement in all age groups.

[0026] To more clearly illustrate the structural features and effects of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0027] Figure 1 This is a block diagram of the main modules of a high-precision infrared body temperature measurement device based on age segmentation, according to an embodiment of the present invention. Figure 2 This is a system schematic diagram of a high-precision infrared body temperature measurement device based on age segmentation, according to an embodiment of the present invention. Figure 3This is a detailed circuit diagram of the MCU, age range selection module, bias filter circuit, and analog selection switch according to an embodiment of the present invention. Figure 4 This is a schematic diagram of the infrared temperature acquisition module circuit according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the EEPROM circuit for the parameter storage module according to an embodiment of the present invention; Figure 6 -7 is an overall workflow diagram of the high-precision infrared body temperature measurement device based on age segmentation according to an embodiment of the present invention (0-3M newborns); Figure 8 -9 is an overall workflow diagram of the high-precision infrared body temperature measurement device based on age segmentation according to an embodiment of the present invention (3M-36M infants); Figure 10 -11 is an overall workflow diagram of the high-precision infrared body temperature measurement device based on age segmentation according to an embodiment of the present invention (for ages three and above, the same as adults). Detailed Implementation

[0028] Please refer to Figures 1 to 11 As shown, a high-precision infrared body temperature measurement device based on age segmentation includes: an age range selection module, an infrared temperature acquisition module, at least two sets of bias filter circuits, an MCU temperature calculation module, an analog selection switch, and a power management module; it achieves accurate matching of analog front-end signal characteristics for different age groups through multiple sets of dedicated bias filter circuits, thereby obtaining high signal-to-noise ratio and low distortion body temperature signals across all age groups.

[0029] The age range selection module is used to generate a range selection signal representing the age range to which the target user belongs; An infrared temperature acquisition module is used to acquire and output the raw infrared signal of the target user; the infrared temperature acquisition module includes: an infrared temperature sensor and an infrared preamplifier circuit, wherein the infrared temperature sensor is connected to the input terminal of all bias filter circuits via the infrared preamplifier circuit.

[0030] At least two sets of bias filter circuits are provided, each set corresponding to an age group. The inputs of all bias filter circuits are connected to the output of the infrared temperature acquisition module to receive the raw infrared signal. Each set of bias filter circuits has a preset bias voltage and filtering parameters that are different from each other and are matched with the age group. These are used to condition the raw infrared signal in the analog domain and output a conditioned signal that matches the signal characteristics of the age group. An MCU temperature calculation module has its input connected to the output of the age range selection module to read the range selection signal. An analog selection switch has a control terminal, at least two input terminals, and a common output terminal. The at least two input terminals are respectively connected to the common output terminal of the at least two sets of bias filter circuits. The control terminal is connected to the output terminal of the MCU temperature calculation module. The MCU temperature calculation module outputs a corresponding channel selection signal to the control terminal of the analog selection switch based on the read gear selection signal. The analog selection switch selectively connects the output terminal of the bias filter circuit corresponding to the gear selection signal to its common output terminal based on the channel selection signal. The common output terminal is connected to the ADC sampling terminal of the MCU temperature calculation module. The MCU temperature calculation module is also used to process the sampled digital signal to calculate and output the body temperature value.

[0031] By using at least two dedicated circuits with different bias voltages and filtering parameters, the body temperature signal characteristics of different age groups (such as newborns, infants, or adults) are matched. Each circuit performs optimal DC bias and band filtering in the analog domain, ensuring that the signal entering the ADC has the highest signal-to-noise ratio and the lowest distortion. This avoids the performance trade-offs of a single fixed circuit, achieving accurate age-specific matching of the analog front end. In practical design, only different resistor and capacitor parameters need to be used in multiple bias filtering circuits, along with a low-cost analog selection switch (such as CD4051). High-precision age-specific temperature measurement can be achieved without expensive programmable gain amplifiers or adjustable filters. After reading the gear selection signal, the MCU actively controls the analog selection switch, enabling it to determine the current age group in real time. This provides the foundation for subsequently calling the corresponding dedicated temperature measurement algorithm (compensation model, digital filtering, clinical threshold), which is a key point in achieving hardware + software matching. Furthermore, the MCU's active selection method allows for the addition of anti-jitter and fault diagnosis logic in the software, preventing false selection due to poor mechanical switch contact. It also allows for dynamic channel switching based on gear changes without the need for additional hardware interlocking circuits, resulting in more flexible and reliable control. In this embodiment, the at least two sets of bias filter circuits include: The first bias filter circuit, corresponding to newborns aged 0 to 3 months, has a cutoff frequency of no more than 1Hz; The second bias filter circuit, corresponding to infants aged 3 to 36 months, has a cutoff frequency higher than that of the first bias filter circuit but not higher than 5Hz. The third bias filter circuit, corresponding to people aged 36 months and above, has a cutoff frequency higher than that of the second bias filter circuit but not lower than 10Hz.

[0032] The age range is divided into three categories: newborn, infant, and adult. The newborn category has an ultra-low cutoff frequency (≤1Hz, preferably 0.72Hz), which effectively suppresses high-frequency noise. Ambient temperature drift is compensated for by ambient temperature and baseline correction to extract extremely weak slow-change temperature signals. The infant category has a moderate cutoff frequency (≤5Hz, preferably 3.39Hz), which fully preserves the characteristics of transient signal fluctuations, making it easy for the MCU to identify and eliminate abnormal signals (attenuation ≤3.4dB within 5Hz). The adult category has a high cutoff frequency (≥10Hz, preferably 15.4Hz), which ensures that effective signals within 2Hz pass through without attenuation and with fast response.

[0033] Each of the first, second, and third bias filter circuits includes a first resistor, a second resistor, a third resistor, and a capacitor. One end of the first resistor is connected to the power supply voltage (+3.3V); the other end of the first resistor is connected to one end of the second resistor; the other end of the second resistor is grounded (GND); the series connection of the first and second resistors serves as the output of the bias filter circuit, which is connected to one input of an analog selection switch; the series connection is also connected to the output of the infrared temperature sensor (i.e., the original infrared signal input) through the third resistor; the series connection is also grounded (GND) through the capacitor C. The first and second resistors form a DC voltage divider bias network, providing a stable DC bias voltage at the output to boost the weak signal from the infrared sensor to the optimal input range of the ADC. The third resistor and capacitor form a first-order RC low-pass filter to filter out high-frequency noise. The third resistor also acts as a signal coupling resistor, superimposing the original infrared signal onto the DC bias voltage.

[0034] Taking the bias filter circuit for the newborn setting as an example: One end of the 100kΩ first resistor R1 is connected to a 3.3V power supply, and the other end is connected to the 57kΩ second resistor R3, with the other end of the second resistor R3 grounded. The series connection point of the first resistor R1 and the second resistor R3 (i.e., the bias voltage output point) is connected to the output terminal of the infrared temperature sensor through the 220kΩ third resistor R2, and this connection is grounded through the 1.0μF capacitor C1. The bias filter circuit structures for the infant and adult settings are exactly the same, only the values ​​of the second and third resistors and the capacitor differ: for the infant setting, the first resistor R4 is 100kΩ, the second resistor R8 is 100kΩ, the third resistor R7 is 100kΩ, and the capacitor C4 is 0.47μF; for the adult setting, the first resistor R11 is 100kΩ, the second resistor R14 is 34.7kΩ, the third resistor R12 is 47kΩ, and the capacitor C8 is 0.22μF. The first resistor R1 in all three circuits is 100kΩ to ensure consistent output impedance. Calculations show that the cutoff frequency for the newborn setting is approximately 0.72Hz, with a bias voltage of approximately 1.21V; the cutoff frequency for the infant setting is approximately 3.39Hz, with a bias voltage of approximately 1.65V; and the cutoff frequency for the adult setting is approximately 15.4Hz, with a bias voltage of approximately 0.85V. These parameters have been verified to provide optimal bias voltage and filtering performance under a 3.3V power supply. Furthermore, by ensuring that the first resistor is identical (100kΩ), the output impedance of each circuit group is kept consistent, facilitating the matching of analog switches and subsequent stage driving.

[0035] The infrared body temperature measurement device also includes a buffer amplifier, whose input is connected to the common output of the analog selector switch, and whose output is connected to the ADC sampling terminal of the MCU temperature calculation module. In actual design and manufacturing, the specific model of the analog selector switch (e.g., CD4051) and the subsequent buffer amplifier (e.g., LM358) are crucial. The CD4051 is a low-cost single-ended multi-channel analog multiplexer suitable for applications with up to three channels. The buffer amplifier is configured as a voltage follower, isolating the influence of the charging and discharging of the subsequent ADC sampling capacitor on the output impedance of the analog switch, and providing low-impedance drive to ensure the accuracy and stability of ADC sampling, avoiding sampling errors.

[0036] The MCU temperature calculation module's built-in analog-to-digital converter has a precision of at least 24 bits. The MCU model used in the temperature calculation module is not limited; it can be SN8P2988 or other models. The MCU temperature calculation module has a built-in LCD driver, operational amplifier, and at least 8K of ROM space. The signal amplitude in the newborn range is extremely weak, and even after bias filtering, it may only show changes of tens of microvolts. A Σ-Δ ADC with a precision of 24 bits or higher can provide microvolt-level voltage resolution (theoretically, the minimum resolvable voltage can reach 0.2μV @ 2.5V reference), ensuring that weak signals are effectively quantized and avoiding quantization noise becoming a bottleneck for accuracy. The MCU temperature calculation module selects signals according to different temperature ranges and sets corresponding dedicated ADC sampling frequencies.

[0037] The MCU temperature calculation module pre-stores multiple sets of exclusive temperature measurement algorithms corresponding to each age group; the MCU temperature calculation module is also configured to: automatically call the exclusive temperature measurement algorithm corresponding to the selected gear level signal based on the read gear level selection signal, and process the sampled digital signal, the processing including at least one of the following: a. A compensation model corresponding to the age group is used for body temperature compensation calculation. The compensation model in the proprietary temperature measurement algorithm is as follows: for the 0-3 month age group, a third-order dynamic compensation model for core body temperature based on infrared emissivity correction and ambient temperature; for the 3-36 month age group, a contact jitter compensation model; and for the 36 month and older age group, a standard core body temperature compensation model. Newborns' thermoregulatory center is not fully developed, and the surface-core body temperature difference is significantly affected by ambient temperature, requiring a third-order polynomial model that includes ambient temperature as an input variable. Infants and young children are active, and the contact state between the probe and skin changes constantly during measurement, requiring a jitter compensation model specifically designed to suppress contact thermal resistance fluctuations (such as real-time monitoring of signal fluctuation rate, automatic identification and removal of motion artifacts). Adults can use a standard linear compensation model. This age-specific compensation model, together with the aforementioned age-specific hardware circuit, constitutes a precise mapping from physical signals to clinical body temperature, a technical effect that ordinary general-purpose algorithms cannot achieve.

[0038] b. Perform digital filtering using digital filtering parameters corresponding to this age group; c. Use the body temperature grading threshold corresponding to this age group for clinical judgment.

[0039] Building upon hardware-based age-matching, software algorithms are added for age-matching, achieving dual precision matching through both hardware and software. This enables: 1. Compensating for physiological differences that hardware cannot handle: While hardware circuits can match the physical characteristics of signals (amplitude, bandwidth), they cannot match the physiological characteristics of different age groups (such as skin emissivity, subcutaneous tissue thermal conductivity, and the conversion relationship between surface and core body temperature). Dedicated compensation models (newborn three-stage ambient temperature compensation, infant contact vibration compensation, and adult standard compensation) solve this problem. 2. Further suppressing residual interference: Dedicated digital filtering, building upon hardware filtering, can target and suppress specific frequency bands (such as 50Hz power frequency and ultra-low frequency drift) without damaging the effective signal. 3. Improving clinical accuracy: Dedicated body temperature grading thresholds (0-3 months, 3-36 months, and 36 months and above, each with its own threshold) avoid misjudgments caused by uniform thresholds, resulting in more accurate clinical conclusions. Because the Chinese "Expert Consensus on the Management of Fever in Children (2026 Edition)," the WHO general standards, and the American Academy of Pediatrics' "Guidelines for the Assessment and Management of Fever in Infants Aged 0-12 Months" all have slight differences in their definitions of normal, low-grade, and high-grade fever, the specific temperature grading thresholds are changed accordingly when different standards are adopted in actual design and manufacturing. The microcontroller is also equipped with temperature grading threshold judgment logic that corresponds to each age group, directly embedding the age-specific temperature standards of clinical pediatrics into the judgment logic of the device. Judgments are made based on the clinical thresholds of different age groups, so that the measurement results are not only accurate in numerical terms, but also in clinical conclusions (whether there is a fever and the degree of fever), which improves the professionalism of the product and user trust.

[0040] The high-precision infrared body temperature measurement device based on age segmentation also includes: a parameter storage module connected to the MCU temperature calculation module, used to store the calibration coefficient and nonlinear compensation parameter corresponding to each age segment; When the MCU temperature calculation module calls the dedicated temperature measurement algorithm corresponding to a specific age group, it reads the calibration coefficient and nonlinear compensation parameters corresponding to that age group from the parameter storage module and uses them to correct the body temperature calculation results. A non-volatile memory (such as EEPROM) is used to implement a production process with independent calibration for each channel. Due to manufacturing tolerances in resistors and capacitors, and the nonlinearity of infrared sensor response, by measuring and storing dedicated calibration coefficients for each age group channel separately during the factory blackbody furnace calibration stage, errors caused by hardware inconsistencies and nonlinearities can be completely eliminated. This allows the infrared body temperature measurement device of this invention to achieve age-specific matching not only in circuit design but also in precise age-specific calibration in actual physical implementation, improving the consistency and reliability of mass production.

[0041] Next, we will introduce a high-precision infrared body temperature measurement method based on age segmentation, which includes the following steps: S1. Gear selection steps: Obtain the gear selection signal representing the age group of the target user; S2. Signal conditioning steps: The raw infrared signal output by the infrared temperature acquisition module is simultaneously input into at least two sets of bias filter circuits corresponding to different age groups. Each set of bias filter circuits performs analog domain conditioning on the raw infrared signal based on different preset bias voltages and filter parameters that match the age group, and outputs a conditioned signal that matches the signal characteristics of the age group. S3, Channel selection step: The MCU temperature calculation module outputs the corresponding channel selection signal to the control terminal of the analog selection switch according to the acquired gear selection signal, so that the analog selection switch selectively connects the conditioned signal output by the bias filter circuit corresponding to the gear selection signal to its common output terminal. S4. Analog-to-digital conversion step: The MCU temperature calculation module converts the conditioned signal output from the common output terminal into a digital signal; S5. Body temperature calculation steps: The MCU temperature calculation module processes the digital signal, calculates and outputs the body temperature value.

[0042] This method can be based on the aforementioned high-precision infrared body temperature measurement device based on age segmentation; Furthermore, after the channel selection step and before the analog-to-digital conversion step, a buffering step is also included: the conditioned signal output from the common output terminal of the analog selection switch is buffered by a buffer amplifier for voltage follower before entering the analog-to-digital conversion step.

[0043] Furthermore, the body temperature calculation step further includes: S5-1. Based on the acquired gear selection signal, the appropriate temperature measurement algorithm for the corresponding age group is called from multiple pre-stored proprietary temperature measurement algorithms. When the gear selection signal corresponds to the 0 to 3-month age group, the compensation model called is a third-order core temperature dynamic compensation model based on infrared emissivity correction and ambient temperature. When the gear selection signal corresponds to the 3 to 36-month age group, the compensation model called is a contact vibration compensation model. When the gear selection signal corresponds to the 36-month and above age group, the compensation model called is a standard core temperature compensation model.

[0044] S5-2. The digital signal is processed using the invoked proprietary temperature measurement algorithm. The processing includes at least one of the following: a) Performing body temperature compensation calculation using a compensation model corresponding to the age group; the compensation model is age-specific, with newborns using third-order ambient temperature compensation, infants using contact shaking compensation, and adults using standard compensation, thus resolving the differences in the conversion rules of core body temperature for different age groups; b) Performing digital filtering using digital filtering parameters corresponding to the age group; age-specific digital filtering allows for targeted filtering of residual interference characteristics in each age group; c) Performing clinical judgment using body temperature grading thresholds corresponding to the age group; age-specific clinical thresholds avoid misjudgments caused by uniform thresholds.

[0045] S5-3 outputs the final body temperature value and clinical assessment result. This achieves seamless optimization across the entire process from physical signal to clinical body temperature.

[0046] Infrared body temperature measurement devices typically also include a body temperature display module, such as an LED display module. The LED display module includes an LED screen and may further include LED warning lights. The clinical judgment result is presented through the color of the body temperature digits or the backlight color of the interface displaying the body temperature digits; different clinical judgment results correspond to different colors. For example, in one embodiment: For children aged 0 to 3 months, the temperature grading threshold ranges are as follows: 35.9°C to 37.5°C is considered normal temperature, and the color is green; 37.6°C to 38.1°C is considered low-grade fever, and the color is green; 38.2°C to 43.0°C is considered high fever, and the color is orange. For children aged 3 to 36 months, the temperature grading thresholds are as follows: 35.7°C to 7.4°C is considered normal temperature, and the color is green; 37.5°C to 38.0°C is considered low-grade fever, and the color is green; 38.1°C to 43.0°C is considered high fever, and the color is orange. For individuals aged 36 months and older, the temperature grading thresholds are as follows: 35.5°C to 7.3°C is considered normal and the color is green; 37.4°C to 38.0°C is considered a low-grade fever and the color is green; 38.1°C to 43.0°C is considered a high fever and the color is orange. The orange color mentioned above can also be changed to red to achieve a more eye-catching warning effect.

[0047] Because there are different standards or guidelines for fever management worldwide, with slight differences in the determination of normal, low-grade fever, and high fever, the temperature grading threshold range is not limited to the above embodiments in other examples. Furthermore, the specific color used to present the clinical assessment result is not limited, as long as it allows the user to visually distinguish several different colors and understand which color corresponds to which clinical assessment result based on the user manual of the infrared body temperature measurement device. Further, a calibration step is included before the temperature calculation step: For the bias filter path corresponding to each age group, a blackbody furnace is used to perform full-temperature calibration to obtain the specific calibration coefficient and nonlinear compensation parameter corresponding to that age group. The specific calibration coefficients and nonlinear compensation parameters are stored in non-volatile memory; The step of calling the specific temperature measurement algorithm corresponding to the age group also includes reading the specific calibration coefficient and nonlinear compensation parameter corresponding to the age group from the non-volatile memory, and using them to correct the body temperature calculation result.

[0048] Furthermore, the body temperature calculation step also includes: Based on the gear selection signal, the body temperature classification threshold corresponding to that age group is invoked; The calculated body temperature value is compared with the body temperature grading threshold, and the body temperature grading result is output. like Figures 6 to 11 As shown, this demonstrates the overall workflow of a high-precision infrared body temperature measurement device based on age segmentation across three age groups. This dual synchronous switching between hardware and software ensures that every step, from analog signal acquisition to digital result output, is optimally configured for the current age group, achieving accurate temperature measurement without compromise throughout the entire process. Compared to solutions that only segment age using hardware, this embodiment shows significant improvements in neonatal environmental adaptability, infant motion resistance, and clinical judgment accuracy.

[0049] Other variations: Those skilled in the art should understand that the scope of protection of this invention is not limited to the specific values ​​and device models mentioned above. For example, different binary codes can be used for different gear levels. For instance, two-bit binary codes, 00, 01, 10, and 11, can represent four different gear levels. Similarly, three-bit binary codes can be freely set within eight gear levels. Therefore, the age gear level can be set to 2, 4, 8, or other numbers, simply by adjusting the number of channels of the analog selection switch and the judgment logic of the MCU accordingly. Furthermore, the resistance value of the first resistor in the three circuits can also be slightly different, as long as the matching relationship between the bias voltage and the cutoff frequency is ensured. Additionally, other models of CMOS multiplexers (such as 74HC4051, MAX4617, etc.) can be used for the analog selection switch, and other low-offset voltage rail-to-rail operational amplifiers can be used for the buffer amplifier. Furthermore, different gear selection signals can be set with dedicated ADC sampling frequencies: 8Hz for newborns, 16Hz for infants, and 16Hz for newborns.

[0050] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the technical scope of the present invention. Therefore, any minor modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A high-precision infrared body temperature measurement device based on age segmentation, characterized in that, include: An age range selection module is used to generate a range selection signal representing the age group to which the target user belongs; An infrared temperature acquisition module is used to acquire and output the raw infrared signal from the target user; At least two sets of bias filter circuits, each set of bias filter circuits corresponding to an age group, and the input terminals of all bias filter circuits are respectively connected to the output terminal of the infrared temperature acquisition module to receive the original infrared signal; Each bias filter circuit has a different preset bias voltage and filter parameters that match the age group, used to condition the original infrared signal in the analog domain and output a conditioned signal that matches the signal characteristics of the age group. An MCU temperature calculation module is connected to the age range selection module to read the range selection signal. An analog selection switch has a control terminal, at least two input terminals, and a common output terminal. The at least two input terminals are respectively connected to the common output terminal of the at least two sets of bias filter circuits. The control terminal is connected to the output terminal of the MCU temperature calculation module. The MCU temperature calculation module outputs a corresponding channel selection signal to the control terminal of the analog selection switch based on the read gear selection signal. The analog selection switch selectively connects the output terminal of the bias filter circuit corresponding to the gear selection signal to its common output terminal based on the channel selection signal. The common output terminal is connected to the ADC sampling terminal of the MCU temperature calculation module. The MCU temperature calculation module is also used to process the sampled digital signal to calculate and output the body temperature value.

2. The age segment based high precision infrared body temperature measurement device according to claim 1, wherein, The at least two sets of bias filter circuits include: The first bias filter circuit, corresponding to newborns aged 0 to 3 months, has a cutoff frequency of no more than 1Hz; The second bias filter circuit, corresponding to infants aged 3 to 36 months, has a cutoff frequency higher than that of the first bias filter circuit but not higher than 5Hz. The third bias filter circuit, corresponding to people aged 36 months and above, has a cutoff frequency higher than that of the second bias filter circuit but not lower than 10Hz.

3. The age segment based high precision infrared body temperature measurement device according to claim 1, wherein, The infrared body temperature measuring device also includes a buffer amplifier, whose input is connected to the common output of the analog selection switch, and whose output is connected to the ADC sampling terminal of the MCU temperature calculation module.

4. The age segment based high precision infrared body temperature measurement device according to claim 1, wherein, The MCU temperature calculation module has a built-in analog-to-digital conversion module with an accuracy of no less than 24 bits.

5. The age segment based high precision infrared body temperature measurement device according to claim 1, wherein, The MCU temperature calculation module has multiple sets of exclusive temperature measurement algorithms pre-stored, each corresponding to a specific age group. The MCU temperature calculation module is further configured to: automatically invoke a dedicated temperature measurement algorithm corresponding to the read gear selection signal, and process the sampled digital signal according to the read gear selection signal. The processing includes at least one of the following: a. Calculate body temperature compensation using a compensation model corresponding to this age group; b. Perform digital filtering using digital filtering parameters corresponding to this age group; c. Use the body temperature grading threshold corresponding to this age group for clinical judgment.

6. The age segment based high precision infrared body temperature measurement device according to claim 1, wherein, Also includes: A parameter storage module, connected to the MCU temperature calculation module, is used to store the calibration coefficients and nonlinear compensation parameters corresponding to each age group. When the MCU temperature calculation module calls the dedicated temperature measurement algorithm corresponding to the age group, it reads the calibration coefficient and nonlinear compensation parameter corresponding to the age group from the parameter storage module and uses them to correct the body temperature calculation result.

7. The age segment based high precision infrared body temperature measurement device according to claim 1, wherein, The infrared temperature acquisition module includes an infrared temperature sensor and an infrared preamplifier circuit. The infrared temperature sensor is connected to the input of all bias filter circuits via the infrared preamplifier circuit.

8. An age segment-based high-precision infrared body temperature measurement method, characterized in that, Includes the following steps: S1. Gear selection steps: Obtain the gear selection signal representing the age group of the target user; S2. Signal conditioning steps: The raw infrared signal output by the infrared temperature acquisition module is simultaneously input into at least two sets of bias filter circuits corresponding to different age groups. Each set of bias filter circuits performs analog domain conditioning on the raw infrared signal based on different preset bias voltages and filter parameters that match the age group, and outputs a conditioned signal that matches the signal characteristics of the age group. S3, Channel selection step: The MCU temperature calculation module outputs the corresponding channel selection signal to the control terminal of the analog selection switch according to the acquired gear selection signal, so that the analog selection switch selectively connects the conditioned signal output by the bias filter circuit corresponding to the gear selection signal to its common output terminal. S4. Analog-to-digital conversion step: The MCU temperature calculation module converts the conditioned signal output from the common output terminal into a digital signal; S5. Body temperature calculation steps: The MCU temperature calculation module processes the digital signal, calculates and outputs the body temperature value.

9. The age segment-based high precision infrared body temperature measurement method according to claim 8, characterized in that, After the channel selection step and before the analog-to-digital conversion step, a buffering step is also included: the conditioned signal output from the common output terminal of the analog selection switch is buffered by a buffer amplifier for voltage follower buffering before entering the analog-to-digital conversion step.

10. The age-segment-based high-precision infrared body temperature measurement method according to claim 8, characterized in that, The body temperature calculation step further includes: S5-1. Based on the acquired gear selection signal, call the exclusive temperature measurement algorithm corresponding to the age group from the pre-stored multiple exclusive temperature measurement algorithms. S5-2. The digital signal is processed using the called proprietary temperature measurement algorithm, and the processing includes at least one of the following: a. performing body temperature compensation calculation using a compensation model corresponding to the age group; b. performing digital filtering using digital filtering parameters corresponding to the age group; c. performing clinical judgment using body temperature grading thresholds corresponding to the age group. S5-3. Output the final body temperature value and clinical judgment result; the clinical judgment result is presented by the color of the body temperature value number or the backlight color of the interface where the body temperature value number is located. The color will be different depending on the clinical judgment result.

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