System and method for measuring temperature of an individual

Abstract

A system and method for operating a thermometer comprising: generating first sensor data by at least one first sensor of the thermometer; analyzing the first sensor data by a processor of the thermometer to determine a distance value defining a distance between the thermometer and a body surface of an individual at which the thermometer is aimed; modifying, by the processor, a sensitivity of the thermometer circuitry based on the distance value; and generating a temperature measurement for the individual by the thermometer circuitry.

Description

[Technical field]

[0001] (CROSS REFERENCE TO RELATED APPLICATIONS) This application claims priority to U.S. Provisional Application No. 63 / 212,551, filed June 18, 2021, the disclosure of which is incorporated herein by reference.

[0002] Description of the Technology Area

[0003] The present disclosure relates generally to thermometers and, more particularly, to implementing systems and methods for measuring the temperature of an individual. [Background technology]

[0004] Thermometers have been used to measure the temperature of individuals. Each thermometer includes a temperature sensor that measures a change in temperature, converts the measured change in temperature into a numerical value that represents the temperature of the individual, and stores the numerical value in a data store. Summary of the Invention

[0005] The present application relates to implementations of thermometer operating systems and methods that include generating first sensor data by at least one first sensor of the thermometer, analyzing the first sensor data by a processor of the thermometer to determine a distance value defining a distance between the thermometer and a body surface of an individual at which the thermometer is aimed, modifying, by the processor, the sensitivity of the thermometer circuitry based on the distance value, generating a body temperature reading for the individual by the thermometer circuitry, and / or modifying the body temperature reading when the second sensor data indicates that the thermometer is not equilibrated. Modifying the sensitivity of the thermometer circuitry can be done, for example, by changing the location of a vent to adjust the overall size of an opening in the thermometer circuitry, by changing calibration parameters of the thermometer, by changing an algorithm used to calculate or adjust the temperature reading, and / or by changing a temperature measurement technique used by the thermometer.

[0006] In some scenarios, the method further includes performing operations to align the thermometer circuitry with a target point on the target individual without assistance from a user of the thermometer, causing the thermometer to measure an air temperature in the surrounding environment, transmitting the air temperature measurement from the thermometer to an external device (e.g., a heating, ventilation and air conditioning system), transitioning the thermometer to a hypothermic or hyperthermic operating mode capable of producing accurate body temperature measurements in the temperature range of 30°C to 34°C or 40°C to 42°C, and / or preventing the spread of infection using a surface of the thermometer formed at least in part from an antibacterial material.

[0007] In such or other scenarios, the method includes detecting a change in airflow within or external to the thermometer, detecting the presence of an operating fan in the vicinity of the thermometer based on the detected change in airflow, and / or dynamically adjusting the operation of the thermometer to account for the possible effect of the operating fan on the temperature measurement, which adjustment may result in adding or subtracting a value (e.g., but is not limited to, 0.01° C. to 2° C.) to or from the temperature measurement.

[0008] In such or other scenarios, the method may include detecting excess moisture on the surface of the individual and / or causing the thermometer to output an indication of the presence of excess moisture.

[0009] In such or other scenarios, the method includes selecting one of a plurality of temperature measurement techniques to be used by the thermometer circuit to generate a body temperature reading for the individual, which may include, but is not limited to, a shutter-based technique, a multi-temperature sensor-based technique, and an interchangeable filter-based technique. If the interchangeable filter-based technique is selected, a body temperature reading may be generated by the thermometer circuit using signals output from the plurality of interchangeable bandpass filters.

[0010] The thermometer circuitry may transition between the first and second of the plurality of temperature measurement techniques based on the second sensor data, the distance value, conditions of the thermometer's internal environment, conditions of the thermometer's external environment, a region of the subject's body closest to the thermometer, and / or a medical condition of the subject. Alternatively, the thermometer circuitry may transition between the first and second of the plurality of temperature measurement techniques in response to a triggering event. The triggering event may include, but is not limited to, a user software interaction (e.g., pressing a key on a keyboard to enter a command), actuation of an input device (e.g., pressing a button), moving the thermometer to a particular geographic location, a temperature reading that exceeds a threshold (e.g., a value below 35° C. (or 95° F.) or above 38° C. (or 100.4° F.)), or a change in sensitivity of the temperature sensor.

[0011] In such or other scenarios, the method includes detecting a skin condition (e.g., eczema, sunburn, blisters, rash, and / or insect bites) of the target individual based on the second sensor data and validating the temperature measurement using the detected skin condition. For example, for an individual with a given skin condition and / or medical condition (e.g., fever, chicken pox, and / or systemic infection) indicated by the skin condition, the temperature measurement may be considered acceptable when it is within an expected range (e.g., a value above 37° C. (or 98.6° F.) or 38° C. (or 100.4° F.)). The solution is not limited to this specific example.

[0012] In such or other scenarios, the method may include periodically and automatically generating a baseline temperature measurement for the subject individual, detecting when the baseline temperature measurement deviates from a specified range (e.g., 35° C. (or 95° F.) to 38° C. (or 100.4° F.)), causing the thermometer to output an indicator indicating that a deviation from the specified range of the baseline temperature measurement has been detected, and / or causing the thermometer to output suggestions for addressing a medical condition of the subject individual (e.g., hyperthermia or fever) upon detecting a deviation from the specified range of the baseline temperature measurement.

[0013] In such or other scenarios, the method may include selecting a threshold from among a plurality of thresholds (e.g., a value outside the range of 32° C. (or 89.6° F.) and 38° C. (or 100.4° F.)) based on the individual's average temperature over a given time period, the difference between the measured temperature values ​​in a given series of measurements, a trend in the measured temperature values, and / or a weighted combination of the measured temperature values. An output may be provided from the thermometer based on a comparison of the temperature measurements generated for the individual to the selected threshold. For example, if the individual's average temperature is 37° C. (or 98.6° F.), then a threshold of 38° C. (or 100.4° F.) is selected. The solution is not limited to this specific example.

[0014] Additionally or alternatively, the method includes acquiring, by a computing device, sensor data generated by a plurality of sensors disposed at different locations within the thermometer, analyzing, by the computing device, the sensor data to detect anomalies or patterns, and modifying, by the computing device, the operation of the thermometer based on the anomalies or patterns. The plurality of sensors may include, but are not limited to, humidity sensors, temperature sensors, accelerometers, mechanical shock / vibration sensors, scent / odor sensors, position sensors, cameras, and microphones. The different locations may include, but are not limited to, adjacent to an internal processor or computing device of the thermometer, on a printed circuit board of the thermometer, embedded within a housing of the thermometer, and / or on the housing. The sensor data may include, but is not limited to, the temperature of the thermometer's electronics, the temperature of the thermometer's printed circuit board, the temperature at a reference point inside the thermometer, the temperature of the environment outside the thermometer, the humidity inside the thermometer housing, the humidity of the external environment, any shock and / or vibration experienced by the thermometer, any acceleration and / or other movement of the thermometer, sounds inside the thermometer, sounds outside the thermometer, any scents / odors inside and / or outside the thermometer, the position of the thermometer, and / or objects in the vicinity of the thermometer.

[0015] The anomalies or patterns may be detected using machine learning algorithms. The detected anomalies or patterns may indicate whether the thermometer is equilibrated. The correction may include transitioning an operational mode of the thermometer and / or adjusting the temperature measurement according to an offset value selected or determined based on the detected anomalies or patterns.

[0016] Additionally or alternatively, machine learning algorithms may be used to predict measurement errors, system failures or malfunctions based on detected anomalies or patterns. The machine learning algorithms may be trained to detect combinations of at least two of temperature measurements, humidity measurements, device vibrations, applied external forces, predetermined types of sounds, odors, proximity of predetermined types of objects, device deformation, device movement, and device location.

[0017] The implementation system may include a processor and a non-transitory computer-readable storage medium having programming instructions that cause the processor to perform the interference mitigation method. Alternatively, or in addition, the implementation system may include logic circuits (e.g., subtractors, adders, multipliers, etc.), passive circuit elements (e.g., resistors, capacitors, switches, delays, etc.), and / or other active circuit elements (e.g., transistors, demodulators, modulators, combiners, etc.). [Brief description of the drawings]

[0018] The present solution is described with reference to the following drawings, in which like reference numerals refer to like features throughout.

[0019] FIG. 1 shows a diagram of an exemplary system.

[0020] FIG. 2 shows a diagram of another exemplary system.

[0021] FIG. 3 shows a diagram of an example architecture of a thermometer.

[0022] FIG. 4 illustrates a diagram of an example architecture for a computing device.

[0023] Each of Figures 5-13 shows a diagram of an example board layout for a thermometer.

[0024] FIG. 14 shows a flow diagram of an exemplary method of operating a thermometer.

[0025] FIG. 15 illustrates a flow diagram of another exemplary method of operating a thermometer.

[0026] FIG. 16 illustrates a flow diagram of an exemplary method for setting the operation and / or parameters of a thermometer.

[0027] FIG. 17 illustrates a flow diagram of an example method for performing battery checks and / or other power management operations for a thermometer.

[0028] FIG. 18 illustrates a flow diagram of an exemplary method for performing thermometer data backup mitigation.

[0029] FIG. 19 illustrates a flow diagram of an exemplary method for automatic uploading of data from a thermometer.

[0030] FIG. 20 illustrates a flow diagram of an exemplary method for data management.

[0031] FIG. 21 illustrates a flow diagram of an exemplary method for thermometer software upgrade.

[0032] 22-24 each show a flow diagram of an exemplary method for system management using sensor data.

[0033] 25A-25B (collectively referred to as "FIG. 25") show a flow diagram of an exemplary method of operating a thermometer.

[0034] FIG. 26 illustrates a flow diagram of another exemplary method of operating a thermometer. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0035] As used in this application, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art. As used in this application, the term "comprising" means "including, but not limited to." Additional definitions of terms relevant to this application are provided at the end of this embodiment.

[0036] An "electronic device" or "computing device" refers to a device that includes a processor and a memory. Each device may have its own processor and / or memory, or the processor and / or memory may be shared with another device, such as in a virtual machine or container configuration. The memory may store or receive programming instructions that, when executed by the processor, cause the electronic device to perform one or more operations in accordance with the programming instructions.

[0037] The terms "memory," "memory device," "data store," "data storage facility," and the like each refer to a non-transitory device in which computer-readable data, programming instructions, or both are stored. Unless specifically stated otherwise, the terms "memory," "memory device," "data store," "data storage facility," and the like are intended to include single device embodiments, embodiments in which multiple memory devices together or collectively store sets of data or instructions, as well as individual portions within such a device.

[0038] The terms "processor" and "processing device" refer to hardware components of an electronic device configured to execute programming instructions. Unless specifically stated otherwise, the singular term "processor" or "processing device" is intended to include both single processing device embodiments and embodiments in which multiple processing devices together or collectively perform processing.

[0039] In this application, when the terms "first" and "second" are used to modify a noun, they are simply intended to distinguish one item from another. No ordering is intended unless otherwise stated. Also, when terms indicating relative positions, such as "vertical" and "horizontal" or "front" or "back", are used, they are intended to be relative to each other and not necessarily absolute. They simply indicate one possible position of the device corresponding to the terms depending on the orientation of the device.

[0040] The present solution relates to an improved thermometer that provides novel functionality and internal controls that result in improved temperature measurement and other device operation, which will become apparent as the description proceeds.

[0041] Exemplary System

[0042] Referring now to Figure 1, a system 100 for implementing the present solution is illustrated. The system 100 includes a thermometer 102, 120, a network 104, a client computing device(s) 106, a server(s) 110, a data store(s) 112, a medical client computing device(s) 114, a thermometer docking / charging station(s) 116, and a medical device(s) 122. The client computing device(s) 106 and / or the medical clinic computing device(s) 114 may include, but are not limited to, personal computers, desktop computers (as shown), tablets, smartphones, personal digital assistants, smart watches, and other devices. In some scenarios, the computing device(s) 106, 114 and / or the medical device(s) 122 execute software application(s) for using / operating the thermometer(s) 102, 120. Additionally or alternatively, the computing device(s) 106, 114 and / or the medical device(s) 122 access cloud service(s) to facilitate control of the use and / or operation of the thermometer(s). The medical device(s) 122 may include, but are not limited to, patient bed(s), medication dispenser(s), ventilator(s), and / or vital signs monitor(s).

[0043] Each thermometer 102, 120 generally measures the temperature of an individual(s) 124 (e.g., a patient in a clinic, a family member such as a child, etc.). How such measurements are made will become clear as the description proceeds. Temperature measurements may be communicated to remote device(s) 106, 110, 114, 122 via a wired communication link 126, a wireless communication link 128, and / or a network 104.

[0044] The network 104 may include, but is not limited to, the Internet, an intranet, a cellular network, a WiFi network, a Bluetooth network, a Bluetooth Low Energy (BLE) network, a Zigbee network, a long-range wireless network (LoRaWAN) network, a Narrow Band Internet of Things (NB-IoT) network, a telecommunications network (3G, 4G, 5G), a Long Term Evolution (LTE) network, a Radio Frequency (RF) network, a Near Field Communication (NFC) network, a Short Range Communication (SRC) network, a Long Range Communication (LRC) network, and / or other networks that are known or will become known. The network may be realized through network nodes such as access nodes and / or gateways. A network security system (e.g., a firewall(s)) may be provided to monitor and control incoming and / or outgoing network traffic based on prescribed security rules.

[0045] The thermometer docking / charging station(s) 116 may be selectively coupled to or otherwise communicatively connected to the thermometer(s) 102, 120 to enable, for example, Over The Air (OTA) access to data and / or operational control of the thermometer(s) 102, 120, charge the thermometer(s) 102, 120 via inductive coupling or other means, transfer data, code and / or software to / from the thermometer(s) 102, 120, act as a communications hub for the system 100, and / or incorporate any wireless communication technology.

[0046] The present solution is not limited to the system architecture of Figure 1. Other system architectures may be used to implement the present solution. Figure 2 shows another exemplary system architecture.

[0047] 3, there is illustrated an example architecture for a thermometer 300. Thermometers 102, 120 of FIG. 1 and 202 to 218 of FIG. 2 are the same as or similar to thermometer 300. Thus, with the description of thermometer 300, thermometers 102, 120 of FIG. 1 and 202 to 218 of FIG. 2 are fully understood.

[0048] Thermometer 300 generally measures the temperature of an individual located in its vicinity. In some scenarios, temperature measurements may be taken at multiple locations on the individual's body based on a group classification associated with the individual and / or based on a medical diagnosis for the individual, depending on a given application (e.g., for use in analysis of different patient groups). For example, temperature measurements may be taken at different locations on the individual's body where a particular hypothermic or hyperthermic condition occurs and / or where useful information can be obtained from temperature measurements at different locations on the patient's body surface. The locations on the individual's body may be determined and / or verified before a temperature measurement is taken by the thermometer.

[0049] Distance to the individual's body surface may further be determined and / or used by the thermometer to aid in targeting locations where temperature measurements or otherwise sensor data may be generated. Imaging techniques may be used to facilitate location and / or distance measurements. Detected distance may be used to selectively and / or dynamically vary the sensitivity of the temperature sensor. For example, sensor information from a larger target area of ​​the individual's body may be collected and, within a distance tolerance (allowing for distance deviations), the sensitivity of the temperature sensor(s) may be minimized or otherwise altered in response to changes in distance to the individual.

[0050] The thermometer 300 may function as a background air temperature monitoring device even when not in normal use for measuring body temperature. This is useful for detecting and / or flagging extreme changes in air temperature outside of a desired temperature range within an environment (e.g., a hospital ward, a clinic, etc.). If the environment is an indoor environment, the temperature of the indoor environment may be controlled by any known or to be known heating, ventilation, and air conditioning (HVAC) system (e.g., system 150 of FIG. 1). This may include providing warnings according to predefined thresholds for upper and lower tolerance limits (e.g., a lower threshold equal to 35° C. (or 95° F.) and an upper threshold equal to 38° C. (or 100.4° F.)). In fact, the thermometer 300 may facilitate adjustment of HVAC operation for heating or cooling the indoor environment and / or notifying an operator of a possible malfunction of the HVAC system. For example, the air temperature measurement(s) may be wirelessly communicated from the thermometer 300 to the HVAC system. The HVAC system may then adjust its operation based on the air temperature measurement(s) according to known techniques. The solution is not limited to this example. The thermometer 300 may further measure other environmental parameters, such as carbon dioxide concentration and / or the amount of other gases present in the environment. The measurements may be used in elderly care facilities to address various health-related issues associated with elderly individuals. Again, measurements may be recorded so that an overview of the environment is built for the thermometer user and any variations or trends in subsequent measurements may be identified.

[0051] Additionally or alternatively, the thermometer 300 may be configured to be used as a special purpose hypothermia device by having a hypothermia operating mode that operates accurately in the temperature range of 30° C. to 34° C. (or 86° F. to 93.2° F.) and / or the temperature range of 40° C. to 42° C. (or 104° F. to 107° F.), may be configured to be used as a special purpose hyperthermia device by having a hyperthermia operating mode that operates accurately at temperatures above 40° C. (or 104° F.), may have at least a contact surface made in part of an antimicrobial material to minimize the spread of infection via surface contact, and / or may have a special tight fitting seal to minimize the capture of contaminants (e.g., body fluids and / or cleaning fluids). Conventional thermometers typically do not provide accurate body temperature measurements in the ranges mentioned above (i.e., 30° C. to 34° and 40° C. to 42° C.). This improved accuracy in the hypothermia mode of thermometer 300 is facilitated at least by the ability of the thermometer to selectively and dynamically vary its sensor sensitivity and / or add / subtract an offset amount from the temperature reading. The offset amount may be selected based on patterns in the sensor data detected by machine learning models and / or by user software interaction with thermometer 300. The patterns may be indicative of different medical conditions or age groups, such as, for example, neonates, Pediatric Active Enhanced Diseases (PAED), and / or the elderly.

[0052] Additionally or alternatively, the thermometer 300 may be provided with a locking mechanism to conveniently change the power source (e.g., battery) while minimizing the possibility of damaging the plastic catch. Examples of such locking mechanisms include a magnet, a single twist screw clamp, a screw, and / or a screw cap.

[0053] 3, the thermometer 300 includes an optional antenna 302, an optional transceiver 304, a computing device 306, a location sensor 308, a humidity sensor 310, a temperature sensor 312, an accelerometer 314, a shock / vibration sensor 316, other sensor(s) 318 (e.g., microphone, camera, location device (e.g., GPS), scent / odor sensor, carbon dioxide sensor, and / or gas sensor), an optional scanner 319, a network interface 320, a ranger device(s) 322, a thermometer circuitry 324, and a rechargeable power source 340. In particular, the thermometer 300 is designed such that the operation of the enumerated components 308 to 319, 322 is optimized and not affected by any object contacting the outer surface of the thermometer.

[0054] In some scenarios, the housing has an ergonomic design and / or is provided with a collection hood accessory that (i) facilitates easy holding and alignment to the surface to be measured, and / or (ii) allows an individual to perform their own measurement. For example, the housing may have an arched body shape and / or an elongated body shape that is linearly aligned to the surface to be measured (e.g., as shown in FIG. 2). The thermometer housing may further be provided with a grip portion so that a user can grasp / hold the thermometer in a position and manner selected to facilitate performance optimization of components 308 to 319 and / or 322 and ensure that the user's physical condition (e.g., temperature and / or force applied to the housing) does not affect the operation of the thermometer. For example, the grip / handle portion is located on the housing such that the human body does not block the field of view (FOV) of the camera. The housing may further be designed to minimize thermal effects on the sensor(s) (e.g., from holding the device in warm hands). This can be achieved by using low thermal conductivity materials, elongated housings that increase the distance between the sensor(s) and the heat source (e.g., a body part, a barcode scanner, display electronics, a local warm object other than the patient's forehead), low thermal conductivity posts / brackets to hold the PCB(s) within the housing, and / or thermally insulating feet on the housing's base for placement on a bench, docking station, etc. Additionally or alternatively, the grip portion may be designed with a tilt sensor that detects the angle of the thermometer relative to a reference point. For example, in some scenarios, the thermometer may be placed on an individual's forehead at four different locations to obtain angle measurements with the tilt sensor. The angle measurements can be analyzed to detect any distortions after imaging by the camera.

[0055] The antenna 302 and transceiver 304 are provided to facilitate wireless communication with an external device through wireless technology (e.g., RF technology). The antenna 302 receives wireless signals from the external device and transmits wireless signals generated by the transceiver 304. Transceivers are known in the art and will not be described herein.

[0056] A computing device 306 is coupled to the transceiver 304 and transmits information to the transceiver 304 that is encoded and modulated into a wireless signal. The wireless signal is provided from the transceiver 304 to the antenna 302 for transmission from the thermometer 300 to an external device (e.g., devices 106, 110, 114 and / or 122 of FIG. 1). This information may include, but is not limited to, temperature readings, alerts, and / or notifications.

[0057] The transceiver 304 also demodulates and decodes wireless signals received from an external device(s) (e.g., devices 106, 110, 114, and / or 122 of FIG. 1). The transceiver 304 is coupled to a computing device 306 and provides decoded signal information to the computing device 306. The computing device 306 uses the decoded wireless signal information according to the function(s) of the thermometer 300. The decoded signal information may include, but is not limited to, requests for specific information and / or commands to control the operation of the thermometer 300.

[0058] The network interface 320 facilitates wired communication with external devices (e.g., network nodes such as access points, etc.) Such network interfaces are known in the art.

[0059] The location sensor 308 determines the location of the thermometer. The location sensor may include, but is not limited to, a Global Positioning System (GPS) sensor and / or a beacon signal transceiver. The location sensor may facilitate device tracking for several reasons (e.g., tracking the location of a thermometer in a hospital or other environment, home monitoring, and / or asset management). Additionally or alternatively, device tracking may be facilitated using signals from local hubs in a building or other localized environment and / or wireless signal strength from radio towers or base stations. The wireless signals may include, but are not limited to, SRC and / or LRC signals.

[0060] The ranger device(s) 322 measure the distance from the thermometer 300 to a person or other object in its vicinity. The distance is determined via signal Time of Flight (TOF) techniques (e.g., using RF and / or acoustic signals), optical techniques, laser pulse techniques, radar techniques, and / or other techniques. Each of the listed techniques is known in the art. The ranger device(s) 322 may employ acoustic and / or optical techniques. For example, the ranger device(s) 322 may estimate the distance to and align to a target location / point on a target individual to ensure optimal placement of the thermometer 300 to perform a temperature measurement or generate other sensor data. This may be automated such that the measurement can proceed if the correct conditions exist within a predefined threshold. Alignment may be performed between the ranger device(s) 322 and the target location / point, and / or between the thermometer circuitry 324 and the target location / point. Alignment may be achieved without assistance from a user of the thermometer. In this regard, alignment may be automated by activating or otherwise operating a mechanism 336 that rotates or otherwise changes the position of at least a portion of the thermometer circuitry 324 (e.g., sensor 328). Mechanism 336 may include, but is not limited to, a motor, gears, and / or a material that deforms when an electrical signal is applied.

[0061] Humidity sensor 310 measures the humidity of the environment outside thermometer 300 and / or the environment within thermometer 300. Temperature sensor(s) 312 measure the temperature(s) of internal component(s) of thermometer 300, measure the temperature of the internal environment of thermometer 300, and / or measure the temperature of the environment outside thermometer 300. Accelerometer 314 measures the acceleration of thermometer 300. Shock / vibration sensor 316 records shock and / or vibration over a defined period of time. Sensor data generated by sensors 310-316 may be stored, accessed, processed, and used by computing device 306 in response to operation of thermometer 300. Feedback may be provided to a user when a measured temperature exceeds a threshold.

[0062] The other sensor(s) 318 may include, but are not limited to, a microphone, a camera, and / or an airflow sensor. In the case of a camera, the computing device 306 performs image processing using an image captured by the camera. This image processing may be performed, for example, to obtain a code printed or otherwise disposed on the object. The code may include, but is not limited to, a barcode. In the case of an airflow sensor, the sensor 318 may detect changes in temperature and / or airflow in and / or around the thermometer 300 and / or the individual whose temperature is being measured. For example, the sensor data generated by the sensor 318 may be used by the computing device 306 to detect the presence of a running fan in the vicinity of the thermometer 300 and / or the individual. The sensor 318 may be located on the exterior of the housing and / or in a side wall of the housing. The operation of the thermometer may be adjusted to take into account the possible effect of a running fan on the temperature measurement. The solution is not limited to this specific example.

[0063] The scanner 319 may include a barcode scanner, an RFID tag scanner, and / or a video camera. Barcode scanners and RFID tag scanners are known in the art and will not be described herein. Any known or to become known barcode scanner and / or RFID tag scanner may be used herein, without limitation. The scanner 319 generally scans an item or object to obtain at least one code therefrom. The code may include, but is not limited to, a barcode and / or a Unique Product Code (UPC). The scanner 319 may be placed on and / or within the housing of the thermometer 300 such that it is positioned and oriented to minimize discomfort to the user and / or other individual(s) in the vicinity. For example, the scanner 319 may be positioned relative to the housing and / or other components of the thermometer to ensure that the likelihood of light being directed into the eyes of the user and / or other individual(s) in the vicinity is minimized.

[0064] The thermometer circuit 324 may include one or more of a reference sensor 326, a sensor 328, a replaceable filter(s) 330, a shutter 332, and / or an aperture stop 334. The thermometer circuit 324 measures the temperature of an object (e.g., object 124 of FIG. 1) proximate the thermometer 300. The temperature may be measured according to one or more techniques, which may include, but are not limited to, a shutter-based technique, a multi-temperature sensor-based technique, and / or a replaceable filter-based technique. A shutter-based technique involves closing a shutter to operate the sensor 328 to obtain a reference temperature measurement, and opening the shutter 332 to operate the sensor 328 to obtain an actual temperature measurement. A multi-temperature sensor-based technique involves using a reference sensor 326 to obtain a reference temperature measurement, and using the sensor 328 to obtain an actual temperature measurement (either simultaneously or sequentially over a relatively short period of time). The replaceable filter based approach involves analyzing different bandpasses using the replaceable filter 330 and performing a ratiometric analysis to determine the temperature measurement. This filter approach is an iterative process since the filter must be changed at least once to obtain at least two bandpass measurements. The filters can be changed automatically by manipulating mechanical means (e.g., motors, gears, tracks, grippers, posts, bars, latches, magnets, springs, etc.) or manually by the individual. Individuals can have spectral signatures (visible and infrared) that can be detected and used to facilitate improved medical care for them. The thermometer detects these spectral signatures.

[0065] When more than one technique is implemented in the thermometer circuitry 234, the thermometer selects one of these techniques and / or causes the thermometer to transition between temperature measurement techniques based on predetermined criteria and / or triggering events. The criteria may include, but are not limited to, values ​​contained in the sensor data (e.g., temperature, vibration, shock, smell, sound, carbon dioxide concentration, gas concentration, etc.), the condition of the thermometer's internal environment (e.g., temperature, humidity, etc.), the condition of the thermometer's external environment (e.g., temperature, humidity, etc.), the distance between the thermometer and the individual, the part of the body closest to the thermometer (e.g., as detected by the thermometer using image processing), and / or a medical condition of the individual whose temperature is being measured (e.g., diabetes vs. hypothermia). Here, machine learning can be used to learn combinations and / or patterns of the enumerated criteria that indicate a given technique is optimal. The triggering events may include, but are not limited to, user-software interaction, pressing or other actuation of an input device (e.g., a button), and / or moving the thermometer to a particular geographic location.

[0066] It should be noted that the thermometer circuitry 324 may implement one or more of the described techniques. If more than one of the described techniques is employed, the computing device 306 may select which technique to use at a given time based on user input, sensor data generated by the sensors 310-318, and / or other information. The computing device 306 may select or change the technique in response to a triggering event (e.g., a temperature measurement exceeding a threshold and / or a change in sensitivity of the thermometer via the aperture 334). The aperture 334 may provide a means to dynamically adjust the sensitivity of the thermometer circuitry to temperature(s) and / or temperature changes. For example, the overall size of the aperture 334 may be adjusted (e.g., via a movable vent) to change the sensitivity of the thermometer to temperature(s) and / or temperature changes. This sensitivity adjustment feature facilitates operation in different modes to achieve better performance for patients or other individuals with different medical conditions (e.g., hypothermic and / or diabetic patients).

[0067] The power source 340 may include, but is not limited to, a secondary battery, a supercapacitor, a charging connection port, an isolation filter (e.g., inductor or ferrite-based components), a voltage regulator circuit, and / or a power plane (e.g., a circuit board layer dedicated to power). The power source 340 may be charged and / or recharged by direct connection to an external power source (e.g., mains power) and / or by a docking / charging station (e.g., docking / charging station 116 of FIG. 1). The power source 340 may further include energy harvesting circuitry to charge and / or recharge the supercapacitor and / or the battery using harvested energy (e.g., light, RF energy, etc.).

[0068] The computing device 306 periodically performs system checks and monitoring to alert about important times and dates (e.g., warranty period(s), calibration date(s), recalibration date(s), etc.) and / or performs self and automatic diagnostics to verify thermometer function and performance. These diagnostics may be accomplished using machine learning algorithms where patterns of readings from diagnostic sensors are learned and may be used to identify possible failure modes. Diagnostic sensors may include, but are not limited to, temperature monitors, shock detectors, humidity sensors, primary sensors, reference sensors, secondary sensors, position sensors, vibration sensors, and / or magnetic field sensors. Failure modes may include, but are not limited to, fixed high or fixed low readings, no primary readings, and / or fixed readings despite changes in the thermal environment (e.g., humidity and / or moisture readings). Additionally or alternatively, this information may be used to train the thermometer to detect specific parameters associated with an individual and dynamically generate instructions for using the thermometer based on the detected parameters. Instructions may be output (auditory, visual, and / or tactile) from the thermometer to the user.

[0069] The computing device 306 facilitates personalized diagnostic monitoring for the patient, i.e., generating a baseline for an individual patient and monitoring trends over a series of measurements for the individual, i.e., personalized temperature tracking and / or spectral signature detection. This personalized diagnostic monitoring functionality can be extended to different patient groups (e.g., elderly, neonatal, pediatric, diabetic, etc.). The computing device 306 provides training, guidance, and / or assistance on the system, which can be prompted and / or output (e.g., via a display) to the user of the thermometer 300. Training can provide instructions on how to use and / or operational controls of the thermometer 300. Training can be facilitated with basic tutorials. This can be facilitated by use of barcode and QR code scanning functionality to pull information stored in the computing device's memory.

[0070] The computing device 306 monitors the frequency of the sensor measurements and detects when the temperature profile is matched based on the monitored frequency, the sensor data, and / or diagnostic information. The temperature profile may be learned by the thermometer 300 using machine learning algorithms and / or artificial intelligence (AI) programs. The machine learning algorithms and / or AI programs may be trained and / or operated to ascertain when is optimal or appropriate to take the next sensor measurement. This avoids issues with excessive frequency of sensor measurements resulting in internal heating and / or insufficient time for re-equilibration.

[0071] The computing device 306 may incorporate means for detecting and monitoring excessive moisture on the forehead or other skin location that may affect the accuracy of the temperature measurement. This may evaluate the spectral profile emanating from the surface at various wavelengths. This may provide a warning and instructions to wipe the forehead or other surface before a temperature measurement is taken.

[0072] The computing device 306 and the camera 318 (or other imaging device) may be used to monitor the skin surface color and assess the skin type with respect to pigmentation and texture. This may be accomplished with the camera 318 (or other imaging device) operating in the visible NIR range. This skin information may be used to verify or otherwise confirm the validity of a temperature measurement. For example, a person's skin color is often red or pink when they have a fever or other elevated body temperature. A relatively high temperature measurement (e.g., 37° C. (or 98.6° F.) or 36.1° C. to 37.2° C. (or 97° F. to 99° F.) above normal body temperature) may be valid, accurate, or valid if the skin color is red or pink, and invalid, inaccurate, or invalid if the skin color matches (e.g., to a certain degree) a normal human or reference color. A person may have a particular skin texture (e.g., bumps, rashes, etc.) if they have a particular medical condition. The temperature measurement(s) may be confirmed or verified based on the person's skin texture and / or known medical conditions. Other criteria may be used in addition to or instead of skin tone, skin texture, and / or medical conditions to confirm or verify the temperature measurement. If more than one criteria is used, the criteria may be weighted. The solution is not limited to this example.

[0073] Referring now to Figure 4, there is illustrated an example architecture of a computing device 400. The computing device(s) 106, 114 of Figure 1, the server 110 of Figure 1, and / or the computing device 306 of Figure 3 may be the same as or similar to the computing device 400. Thus, with the description of the computing device 400, the devices 106, 110, 114 of Figure 1 and the computing device 306 of Figure 3 are fully understood.

[0074] Computing device 400 may include more or less components than those shown in Figure 4. However, the illustrated components are sufficient to disclose an exemplary manner of implementing the present solution. The hardware architecture of Figure 4 illustrates one form of a representative computing device configured to operate a thermometer and / or process data as described herein. Thus, computing device 400 of Figure 4 implements at least a portion of the method(s) described herein.

[0075] Some or all of the components of computing device 400 may be implemented as hardware, software, and / or a combination of hardware and software. Hardware includes, but is not limited to, one or more electronic circuits. Electronic circuits may include, but are not limited to, passive elements (e.g., resistors and capacitors) and / or active elements (e.g., amplifiers and / or microprocessors). The passive and / or active elements may be adapted, arranged, and / or programmed to perform one or more of the techniques, procedures, or functions described herein.

[0076] As shown in FIG. 4, the computing device 400 comprises a user interface 402, a central processing unit (CPU) 406, a system bus 410, a memory 412 connected to and accessible by other portions of the computing device 400 through the system bus 410, a system interface 460, an optional wireless communication device 464, and hardware entities 414 connected to the system bus 410. The user interface may include input devices and output devices that facilitate user-software interaction to control the operation of the computing device 400. The input devices include, but are not limited to, a physical and / or touch keyboard 450. The input devices may be connected to the computing device 400 by a wired or wireless connection (e.g., a Bluetooth connection). The output devices include, but are not limited to, a speaker 452, a display 454, a light emitting diode 456, and / or a haptic feedback device 462. The haptic feedback device 462 provides haptic feedback to a user of the computing device. The haptic feedback may include, but is not limited to, haptic feedback, visual feedback, and / or auditory feedback. Tactile feedback may be provided, for example, when the measured temperature exceeds a threshold temperature.

[0077] The system interface 460 facilitates wired and / or wireless communication with external devices (e.g., network nodes such as access points, etc.). In some scenarios, a wireless communication device 464 is provided in addition to the system interface 460 to facilitate wireless communication with external devices. If both components 460 and 464 are wirelessly capable, they may employ different wireless communication technologies.

[0078] At least some of the hardware entities 414 perform actions that involve accessing and using the memory 412. The memory 412 may be a random access memory (RAM), a disk drive, a flash memory, a compact disc read only memory (CD-ROM), and / or other hardware devices capable of storing instructions and data. The hardware entities 414 may include a disk drive unit 416 with a computer readable storage medium 418. The computer readable storage medium 418 has stored thereon one or more instructions 420 (e.g., software code) configured to perform one or more of the techniques, procedures, or functions described herein. The instructions 420 may also reside, completely or at least partially, within the CPU 406 and / or within the memory 412 during execution of the CPU 406 by the computing device 400. The memory 412 and the CPU 406 may also constitute a machine-readable medium. Herein, the term "machine-readable medium" refers to a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) that store the set or sets of instructions 420. Here, the term "machine-readable medium" refers to any medium that can store, encode, or carry a set of instructions 420 for execution by a computing device 400 and cause the computing device 400 to perform any one or more of the techniques of this disclosure.

[0079] Exemplary Methods

[0080] 14, a flow diagram of an example method 1400 of operating a thermometer (e.g., thermometer 102 or 120 of FIG. 1) is shown. Method 1400 begins at 1402, when a user presses or otherwise activates an “on / off” button on a thermometer (e.g., thermometer 102 or 120 of FIG. 1). When the “on / off” button is activated, the thermometer performs the following operations: (i) determine the period during which the “on / off” button was activated, and (ii) determine whether the period exceeds a threshold (e.g., 5 seconds). If the period exceeds the threshold (1404: YES), the thermometer transitions to a configuration mode and continues with the setup operations of FIG. 16 (described below).

[0081] On the other hand, if the time period does not exceed the threshold (1404: NO), the method 1400 continues to the temperature measurement mode. Operations 1408 to 1424 of the first branch and operations 1430 to 1452 of the second branch may be performed in parallel during the temperature measurement mode of the thermometer. In some scenarios where wireless communication of the thermometer is disabled, operations 1430 to 1452 are not performed.

[0082] The operations of the first branch generally involve the thermometer performing the following operations: At 1408, perform initialization operations (e.g., perform start-up procedures, illuminate the display, output important information (e.g., battery status, mode setting, parameter setting(s), device status (e.g., ready to measure temperature), etc.); At 1410, prompt the user to point the thermometer at the individual of interest (e.g., individual 124 of FIG. 1); At 1412, verify that the thermometer is pointed at the individual of interest. This verification may be based on user input and / or sensor data generated by the thermometer's sensor (e.g., sensor 318 of FIG. 3). For example, the sensor data may include images taken by a local camera of the thermometer and processed to detect a predetermined type of object (e.g., a person) therein. If the confirmation is not obtained within a predetermined time (e.g., 10 seconds), the thermometer may return to 1410, continue to 1424, where processing ends, or another action may be performed. If the confirmation is obtained within the predetermined time, the thermometer may generate a temperature reading for the individual (e.g., automatically or in response to user input (e.g., a button press or actuation)), as shown at 1412.

[0083] At 1412, the temperature reading may be stored in a data store local to the thermometer (e.g., memory 412 of FIG. 4) and / or in a remote data store external to the thermometer (e.g., data store 112 of FIG. 1). At 1414, the thermometer outputs the temperature reading and / or status information (e.g., via display 454 of FIG. 4). The status information may indicate whether the local and / or remote storage of the temperature reading was successful.

[0084] Upon completion of 1414, the thermometer determines at 1416 whether to repeat the temperature measurement. This determination may be made automatically based on user input and / or based on a comparison of the temperature measurement to a threshold. For example, a determination may be made that the temperature measurement should be repeated if the temperature measurement is outside of a predetermined range of temperature values. If the temperature measurement should be repeated (1416: YES), method 1400 returns to 1412. Otherwise (1416: NO), method 1400 continues to optional 1418.

[0085] In some scenarios, the thermometer's wireless communication capabilities are disabled. Thus, the thermometer may check at 1418 to determine whether the communication capabilities are enabled or disabled. If disabled, the thermometer may prompt for user input to enable the thermometer's wireless communication capabilities. Alternatively, method 1400 continues to 1424, where processing ends or another action is taken (e.g., the thermometer is turned "off"). If the wireless communication capabilities are enabled (1418: YES), the thermometer may perform an action to determine whether the remote storage of the temperature reading was successful. If successful (1420: YES), method 1400 continues at 1424. If not successful, the thermometer initiates the backup mitigation process shown in FIG. 18 (described below), as shown at 1452.

[0086] The operations of the second branch generally involve initializing communication operations to establish a communication link between the thermometer and an external device (e.g., the client computing device 106 of FIG. 1, the medical clinic computing device 114 of FIG. 1, and / or the medical device 122 of FIG. 1). These operations are performed in function blocks 1430 through 1436. The operations depend on the type of wireless communication used by the thermometer. The thermometer may output status information (e.g., via display 454 of FIG. 5) indicating whether a wireless connection has been established between the thermometer and the external device.

[0087] The thermometer then performs an operation at 1440 to determine whether it has data to transmit. This determination may be made based on the value of a flag set in data stored in a local memory (e.g., memory 412 of FIG. 4). If there is no data to transmit (1440: NO), the thermometer waits to transmit data. If there is data to transmit (1440: YES), the thermometer performs an operation at 1446 to read the data from the local memory, format the data for wireless communication, and transmit the formatted data over the established communications link with the external device. An indication may optionally be output by the thermometer to indicate that data is being transmitted.

[0088] The thermometer may also selectively continue or discontinue wireless communication, as shown at 1450. For example, if a temperature measurement is repeated, a connection may be maintained so that new temperature measurements are stored remotely from the thermometer, whereas if a temperature measurement is not repeated, the wireless communication functionality may be disabled, for example to conserve power.

[0089] The present solution is not limited to the method 1400. For example, additional operations may be performed as shown in Fig. 15. In Fig. 15, operations 1502 to 1514, 1522 to 1530 are the same as or similar to operations 1402 to 1424 in Fig. 14. Similarly, operations 1532 to 1552 in Fig. 15 are the same as or similar to operations 1430 to 1452 in Fig. 14. The difference between Fig. 14 and Fig. 15 is the inclusion of additional operations 1516 to 1520 that may perform user software interaction to prompt the user to accept or reject the temperature measurement.

[0090] 16, a flow diagram of an example method 1600 for configuring operations and / or parameters when the thermometer is in a configuration mode is shown. The method 1600 begins at 1602 and continues at 1604 where a graphical user interface (GUI) is presented on the thermometer's display. The GUI prompts user software interaction to configure the thermometer's operation. As shown in function blocks 1606 to 1610, the GUI includes prompts and / or widgets that allow the user to optionally select units of temperature measurement (e.g., Celsius or Fahrenheit). In function blocks 1612 to 1616, the GUI presents prompts and / or widgets that allow the user to optionally enable and disable sounds for the thermometer. The GUI further includes prompts and / or widgets that allow the user to optionally select a surface temperature measurement mode of operation or a core body temperature calculation mode of operation as shown in function blocks 1618 to 1622. The GUI further includes prompts and / or widgets that allow the user to optionally select an offset mode for adding a calibration value to the temperature reading for normalization purposes, as shown in function blocks 1628 to 1632. In function blocks 1634 to 1638, the GUI prompts user software interaction to enable or disable the wireless communication device / feature of the thermometer. The GUI also prompts user software interaction to select an operation mode from among a number of predefined operation modes of the thermometer. The operation modes may include, but are not limited to, a calibration operation mode, a configuration operation mode, a power charging operation mode, a thermometer operation mode without wireless communication, a thermometer operation mode with wireless communication, an OTA operation mode, a data logging operation mode, a thermometer performance logging / analysis operation mode, and / or a power management operation mode. In some scenarios, the system performs an operation to verify the stability of the calibration before sending any readings from the thermometer. If the stability of the calibration is not verified, no readings are sent from the thermometer. In 1652, the thermometer performs a self-reconfiguration operation in response to the user selection. Subsequently, as indicated in function block 1656, the method 1600 may end or another operation may be performed.Widgets may include, but are not limited to, virtual buttons, text entry boxes, list boxes, and / or menus.

[0091] It should be noted that the system has a timeout feature that causes the thermometer to operate according to the initial setting(s) or previously selected setting(s) if the thermometer does not receive user software interaction(s) within a predetermined period of time from the time the GUI prompts the user to select a setting. The timeout feature is illustrated by function blocks 1624 and 1644. Method 1600 then ends or the thermometer performs another action, as illustrated by function blocks 1626 and 1642.

[0092] 17, a flow diagram of an example method 1700 for performing a battery check and / or other power management operations by a thermometer is shown. The method 1700 may begin in response to a particular triggering event. The triggering event may include, but is not limited to, powering up the thermometer, a shutdown mode of the thermometer, completion of a temperature measurement cycle, user software interaction to select a power management mode of operation, insertion of the thermometer into a charging dock, and / or a change in the surrounding environment (e.g., an increase or decrease in light, radio frequency (RF) energy, and / or other types of harvestable energy).

[0093] Method 1700 starts at 1702 and continues to 1704. At 1704, the thermometer performs an operation to determine a current voltage level of a battery and / or a current state of charge of another power source (e.g., a supercapacitor). The current voltage level and / or current state of charge are compared to a threshold to determine if it is relatively low. If not (1706:NO), method 1700 continues to decision block 1708. At 1708, the thermometer determines whether to turn off or otherwise shut down. If not (1708:NO), the thermometer transitions to a temperature measurement mode of operation and transitions to FIG. 14, as shown in function block 1712. If not (1708:YES), the thermometer performs a turn off or other shut down operation at function block 1714. Method 1700 then ends at function block 1724.

[0094] If the battery voltage level and / or the charge level of the other power source is low (1706: YES), an indicator and / or a warning message is output from the thermometer to inform of the low voltage level / charge level. The output may be visual, tactile, and / or audible. In response to the indicator and / or the warning message, the thermometer's power source may be charged, as shown in function block 1720. The thermometer may be a low-energy device and may have a power management function to ensure its sustainability. The thermometer may further be configured with a counter to detect the number of measurements over its lifetime. The power charging may be achieved by placing the thermometer in a charging station (e.g., charging dock / station 116 of FIG. 1) and / or separately connecting the thermometer to an external power source. In some scenarios, the thermometer has an energy harvesting circuit configured to harvest energy (e.g., light, RF energy, heat, etc.) from the surrounding environment. The energy harvesting circuit may be enabled to charge the thermometer's battery or other power source(s). The solution is not limited to this specific example. Once the power source is charged, the method 1700 returns to 1708 .

[0095]

[0013] Referring now to Figure 18, a flow diagram of an example method 1800 for performing thermometer data backup mitigation is shown. Method 1800 begins at 1802 and continues to 1804 where the thermometer performs a data check. The data check may involve accessing a local data store (e.g., memory 412 of Figure 4) to identify any data records that are not associated with a log file or other information (e.g., a flag) that indicates that data has been uploaded to a remote data store (e.g., data store 112 of Figure 1). If no data records are identified, the thermometer makes a determination at 1806 that no data is to be uploaded. If this determination is made (1806: NO), method 1800 continues to 1820. At 1820, a notification or other indicator is output from the thermometer to inform the user that all data uploads have been completed and / or that no uploading is required. The notification and / or indication may be tactile, audible, and / or visual.

[0096] If one or more data records are identified, the thermometer determines that there is data that needs to be uploaded at 1806. If this determination is made (1806: YES), method 1800 continues at 1808. At 1808, an indicator or notification is output from the thermometer to inform the user that a data upload has failed and / or is necessary. The notification and / or indication may be tactile, audible and / or visual.

[0097] The thermometer then performs 1810 an operation to establish a connection with a remote device (e.g., the client computing device 106 of FIG. 1, the medical clinic computing device 112 of FIG. 1, and / or the medical device 122 of FIG. 1). A function may be provided to limit the number of times the thermometer attempts to establish a connection, as shown in function block 1820. If a connection is not made within a predetermined number of attempts (1820: YES), then a log file or record is updated 1824 to include information regarding the connection attempt(s). A further indicator or warning message may be output from the thermometer, as shown in function block 1826. The method 1800 then ends or another operation is performed, as shown in function block 1828.

[0098] Once a connection is established (1812: YES), the thermometer performs operations to communicate the data over a network (e.g., network 104 of FIG. 1) to the remote device. Message(s) may be provided from the remote device to the thermometer indicating whether data has been received, whether a data upload is in progress, and / or whether the data upload has been successfully completed. As shown in function block 1816, a status indicator may be output from the thermometer to inform a user of successful data transmission and / or data upload status.

[0099] Upon completion of 1816, the thermometer checks to see if there is more data to upload. If there is (1818:YES), method 1800 returns to 1814 and the upload process is repeated for the next data. If there is no data to upload (1818:NO), method 1800 continues to 1820, where an indication is provided by the thermometer that all data has been uploaded. Then, in function block 1828, method 1800 ends or another operation is performed.

[0100] 19, a flow diagram of an example method 1900 for automatically uploading data from a thermometer is shown. Method 1900 begins at 1902 and continues to 1904. At 1904, the thermometer determines whether (i) the automatic upload feature is enabled or disabled, and / or (ii) the wireless communication feature is enabled or disabled. If (i) and / or (ii) are enabled (1904: YES), the thermometer performs operations in function blocks 1906 to 1938. The operations in function blocks 1906 to 1914, 1918, 1920, 1926 to 1930, 1936, and 1938 are the same as or similar to the operations in function blocks 1806 to 1828 of FIG. 18, respectively. Method 1900 differs from method 1800 of FIG. 18 by the addition of decision blocks 1916, 1922, and 1934 that perform decisions (i) and / or (ii) periodically during processing.

[0101] 20, a flow diagram of an exemplary method 2000 for data management is shown. Method 2000 begins at 2002 and continues to decision block 2004. At block 2004, the thermometer performs an operation to determine whether new analog data is present. If new analog data is present (2004: YES), then operations are performed at function blocks 2006 through 2010 to store the analog data and / or other information locally at the thermometer and / or remotely in a remote data store. If new analog data is not present (2004: NO), then the thermometer determines whether there is a system problem and / or failure. The system problem and / or failure is recorded at 2014.

[0102] If there are no system problems and / or failures (2012: NO), the thermometer determines if the transaction history log feature is enabled. If so (2016: YES), the transaction information is logged. If not (216: NO), the thermometer determines if all data was successfully transferred to the remote device. If the data transfer was not successful (2020: NO), the data is stored in a local data store for future transmission. If the data transfer was successful (2020: YES), the thermometer repeats the process unless a shutdown request has been received (2024: NO). If a shutdown request has been received, method 2000 ends or another action is taken to shut down or otherwise turn off the thermometer.

[0103] 21, a flow diagram of an example method 2100 for a thermometer software upgrade is shown. The method 2100 begins at 2102 and continues to 2104. At 2104, the thermometer determines whether OTA mode is enabled. If OTA mode is not enabled (2104: NO), the thermometer transitions to a configuration mode of operation and transitions to FIG. 16, as shown in function block 2106.

[0104] If OTA mode is enabled (2104: YES), the thermometer performs operations to establish a wireless connection with a remote device (e.g., the client computing device 106 of FIG. 1, the server 110 of FIG. 1, the medical clinic computing device 114 of FIG. 1, and / or the medical device 122), as shown in function blocks 2108 through 2112. Once the wireless connection is established, the thermometer prepares and receives the updated / upgraded software in function block 2114. Once the update / upgrade is complete, the thermometer checks to confirm a valid software upload in function block 2124. In function block 2126, an indicator may be output from the thermometer to indicate to the user that the software update / upgrade was successfully completed. In function block 2128, information regarding the software update / upgrade is recorded. Subsequently, in function block 2130, the method 2100 ends or another operation is performed.

[0105] 22, a flow diagram of an example method 2200 for system management using sensor data is shown. Method 2200 begins at 2202 and continues to 2204. At 2204, sensor data is acquired or otherwise generated by sensor devices (e.g., sensors 310, 312, 314, 316, and / or 318 of FIG. 3) located at various locations on / within the thermometer housing. The sensor devices may include, but are not limited to, humidity sensor(s), temperature sensor(s), accelerometer(s), mechanical shock / vibration sensor(s), scent / odor sensor, location sensor(s) (e.g., GPS sensor), camera(s), and / or microphone(s). The locations may include, but are not limited to, locations adjacent to an internal processor or computing device (e.g., computing device 306 of FIG. 3), locations on a printed circuit board (PCB), locations embedded within the housing, and / or locations on the housing. For example, in some scenarios, the sensor device measures the temperature of the thermometer's electronics (e.g., processor), the temperature of the thermometer's PCB, the temperature at a reference point inside the thermometer, the temperature of the environment outside the thermometer, the humidity inside the thermometer housing, the humidity of the external environment, any shocks and / or vibrations the thermometer experiences, any accelerations and / or other movements of the thermometer, sounds inside the thermometer, sounds outside the thermometer, any scents / odors inside and / or outside the thermometer, the location of the thermometer, and / or objects in the vicinity of the thermometer. The solution is not limited to this specific example. Sensor measurements / detections can be performed continuously or periodically depending on any given application.

[0106] In function block 2206, the sensor data is analyzed to detect anomalies and / or patterns therein. Any detected anomaly / pattern information may be recorded as shown in function block 2226. In function block 2228, an indicator or other notification may be output from the thermometer to notify / notify a user of the detection. Then, in function block 2230, the method 2200 ends or another operation is performed.

[0107] In this regard, the thermometer may provide a patient monitoring means in addition to a temperature measurement means. For example, the temperature readings output from the reference sensor 326 may be monitored to detect when the baseline temperature deviates from a particular range. Upon such detection, the thermometer may generate and output indicators and / or suggestions to address the individual's condition in a predetermined manner (e.g., provide more or change medication, dispatch a nurse to the patient, give the patient liquid or solid food, etc.).

[0108] In addition to temperature measurement means, the thermometers can also facilitate centralized asset management means. For example, a remote centralized computing device may communicate with multiple thermometers to obtain sensor data therefrom. The remote centralized computing device may analyze the obtained sensor data and determine if any thermometers need to be inspected, replaced, recharged, and / or recalibrated. The remote centralized computing device may then output messages indicating the health of the thermometers, any operational issues with the thermometers, and / or recommendations to inspect / replace / charge / calibrate the thermometer(s). The messages may further dispatch personnel to the location(s) of the thermometer(s) and / or move the thermometer(s) to a predetermined location.

[0109] Anomaly / pattern detection may be achieved by comparing measurements with predefined thresholds stored in a local data store (e.g., memory 412 in FIG. 4) of the thermometer and / or by executing machine learning algorithms that detect learned patterns in the object and / or sensor data. Any machine learning algorithm may be used here. For example, one or more of the following machine learning algorithms may be employed: supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. The machine learning algorithm may be trained to predict inaccuracies / deviations / issues in the thermometer measurements, system failures, and / or malfunctions. This is based on a learned combination of temperature measurements, humidity measurements, device vibrations, applied external forces (e.g., acceleration, movement, mechanical shock, vibration, and / or external forces on the thermometer when it is dropped to the ground causing deformation of at least a portion of the thermometer), predefined types of interior / exterior sounds (e.g., cracking, bubbling, exploding, impact, etc.), interior / exterior odors (e.g., smoke, etc.), proximity of predefined types of objects, device deformation, device movement(s), and / or device location(s).

[0110] In some scenarios, the sensor data may be analyzed to determine whether the thermometer is equilibrated by comparing multiple temperature measurements to one another (e.g., the temperature of an electronic component within an enclosure is the same or similar to the temperature of the external environment), as shown in function block 2210. If the thermometer is equilibrated (2210: YES), method 2200 continues to 2212. At 2212, the thermometer transitions operational modes (e.g., begins temperature measurement mode) and transitions to FIG.

[0111] If the thermometer is not equilibrated (2210: NO), the system waits a predetermined time and performs another loop of sensor data analysis to recheck for equilibration, as shown in function blocks 2214 through 2216. If the thermometer can proceed without equilibration (2214: NO), operations in function block 2224 are performed to configure the operation of the thermometer according to predetermined rules and / or sensor data profiles (e.g., in response to temperature gradients through the device). For example, the thermometer may be configured to add a predetermined offset amount V to / from any temperature reading of the subject individual. offset Add or subtract a given offset amount V offset , S1, S2, ..., S2, ... may be predefined and stored in a local data store (e.g., memory 412 in FIG. 4) or a remote data store (e.g., data store 112 in FIG. 1), or may be dynamically determined according to a predefined algorithm. N can be defined by the following equation (1) in which V offset =W1 S1 + W2 S2 + … + W N ·S N (1) Here, W1, …, W N Each of S1, S2, ..., S N Some or all of the may be of the same type (e.g., all temperature values ​​but measured at different locations within the thermometer) or different types (e.g., temperature and / or humidity values ​​measured at one or more locations within the thermometer). The sensor data value(s) may include, but are not limited to, actual measurements (e.g., temperature measurements) and / or values ​​determined based on the sensor data (e.g., values ​​assigned to geographic locations and / or values ​​assigned to given types of objects and / or odors). Next, as shown in function block 2212, the thermometer transitions operational modes (entering temperature measurement mode) and transitions to FIG. 14.

[0112] 23, a flow diagram of an example method 2300 for system management is shown. Method 2300 begins at 2302 and continues to 2304. At 2304, sensor data is acquired and analyzed to detect anomalies and / or patterns therein. This detection may be accomplished in a manner similar to that described above with respect to function blocks 2204 through 2206 of FIG. 22. If there are anomalies and / or patterns (2306: YES), the system may optionally perform operations in function block 2317 to verify that the thermometer is operating properly and / or take corrective action(s) to address any detected improper device operation (e.g., switching operation from the first device to a second backup device and / or switching operation modes to optimize operation of the thermometer with respect to the detected anomalies, sensor data patterns, and / or improper electronic component operation / function). Information regarding the anomalies, patterns, device operation, and / or corrective actions may be recorded in function block 2318. An indicator and / or notification may be output from the thermometer to inform a user of the detected anomalies and / or patterns, as shown in function block 2320. Then, in function block 2322, the method 2300 ends or another operation is performed.

[0113] If no anomalies and / or patterns are detected (2306: NO), the thermometer performs an operation to determine if its electronic component(s) are operating as expected. If one or more electronic components are not operating as expected (2308: NO), corrective action(s) may be taken at function block 2317. Information may be recorded at 2318 and an indicator / notification may be output from the thermometer at 2320. The method 2300 then ends or another operation is performed at function block 2322.

[0114] If the electronic components are operating as expected (2308: YES), information may be output from the thermometer indicating proper operation and / or that the thermometer is ready to generate a temperature measurement. The information may also be recorded, as shown in function block 2312. The thermometer may then transition modes, such as to a temperature measurement mode, as shown in function block 2316, and transition to FIG.

[0115] 24, a flow diagram of an exemplary method 2400 for system management is shown. The method 2400 starts at 2402 and continues to 2404. At 2404, with the shutter 332 of FIG. 3 in an open position, a calibration routine is performed. For example, a reference temperature sensor is used to obtain temperature measurements of the environment within and / or outside the thermometer. The temperature measurements are compared to previous temperature measurements. If the temperature measurements deviate (by a particular level) from the previous value(s), then at 2406, the temperature sensor is determined to be properly calibrated. Otherwise, the temperature sensor is deemed to be improperly calibrated. Information regarding the first calibration routine may be recorded at function block 2416 and / or output from the thermometer at function block 2418. Subsequently, at function block 2420, the method 2400 ends or another operation is performed.

[0116] 3 in the closed position. Information regarding the calibration routine may be recorded and / or output from the thermometer, as shown in function blocks 2410 through 2412 and 2416 through 2418. If the results of the calibration process indicate that the thermometer and / or its electronic device(s) are operating properly, the thermometer may transition its operational mode, for example to a temperature measurement mode, as shown in function block 2414, and transition to FIG.

[0117] In some scenarios, the thermometer automatically measures the individual's temperature a predetermined number of times and / or analyzes a series of temperature measurements for the individual (taken over a period of time) to determine a baseline value, threshold temperature value, or range of temperature values ​​that is tailored / customized for the individual. For example, the thermometer may select a threshold value or threshold values ​​from among a number of threshold values ​​based on the individual's average temperature over a predetermined period of time, a maximum or minimum difference between the measured temperature values ​​in a series of temperature measurements, a detected increasing and / or decreasing trend in the measured temperature values. The baseline value and / or threshold value may be selected or calculated based on an average of the temperature measurements and / or a weighted combination of the temperature measurements. For example, each temperature measurement is selectively / dynamically assigned a weight based on other sensor data (individual's humidity, baseline temperature, internal / external environmental temperature, shock, vibration, odor, range, etc.) generated at the same / similar time as the respective temperature measurement. Alternatively or in addition, the baseline value and / or threshold value may be selected depending on the medical condition of the individual.

[0118] Referring now to Figure 25, a flow diagram of an example method 2500 for operating a thermometer (e.g., thermometers 102, 120 of Figure 1, 202-218 of Figure 2, and / or 300 of Figure 3) is shown. The solution is not limited to the specific order in which the operations are performed in Figure 25. Two or more operations may be performed in a different order relative to that shown in Figure 25.

[0119] Method 2500 begins at 2502 and continues to 2504. At 2504, the sensor(s) of the thermometer (e.g., 308-318, 322, 326, and / or 328 of FIG. 3) generate sensor data. At 2506, a temperature measurement technique to be used by the thermometer circuit (e.g., thermometer circuit 324 of FIG. 3) to generate a temperature reading for the individual of interest (e.g., individual 124 of FIG. 1) is selected by the thermometer's processor (e.g., CPU 406 of FIG. 4) or computing device (e.g., computing device 306 of FIG. 3). The temperature measurement technique may include, but is not limited to, a shutter-based technique, a multi-temperature sensor-based technique, and / or a replaceable filter-based technique. The selection may be made based on user input, the sensor data, the distance value, conditions of the thermometer's internal environment, conditions of the thermometer's external environment, the part of the individual's body closest to the thermometer, and / or a medical condition of the individual. The thermometer is then transitioned to the selected temperature measurement technique at 2508. This transition may be performed in response to a triggering event, which may include, but is not limited to, a user software interaction, actuation of an input device, moving the thermometer to a particular geographic location, a temperature reading exceeding a threshold, or a change in the sensitivity of the temperature sensor.

[0120] At 2510, a processor or computing device detects airflow inside and / or outside the thermometer. This detection can be made using the sensor data generated at 2504. The detected airflow characteristic(s) are then used at 2512 to detect the presence of an operating fan in the vicinity of the thermometer. The characteristics can include, but are not limited to, speed, airflow rate, changes in speed, and / or changes in airflow rate. At 2512, the operation of the thermometer can be adjusted to account for the expected effect of the operating fan on the temperature measurement.

[0121] At 2516, the processor or computing device detects excessive moisture on the surface of the individual of interest. For this detection, the sensor data generated at 2504 may be used. The processor or computing device may then optionally cause the thermometer to output a notification indicating that excessive moisture has been detected, as shown at 2518. At 2520, the processor or computing device causes the thermometer to enter a hypo / hyperthermia mode of operation. In the hypo / hyperthermia mode of operation, the thermometer is capable of producing accurate body temperature readings in the temperature ranges of 30° C. to 34° C. or 40° C. to 42° C.

[0122] At 2522, the processor or computing device may analyze the sensor to obtain a distance value. The distance value defines the distance between the thermometer and the body surface of the individual at which the thermometer is aimed. At 2524, the sensitivity of the thermometer circuitry may be modified based on the distance value. As shown at 2526, the processor or computing device may align the thermometer circuitry to a point of interest on the individual without assistance from a user of the thermometer.

[0123] At 2528, the thermometer generates a temperature reading for the subject individual. The surface of the thermometer may be formed at least in part from an antimicrobial material to minimize the spread of infection. The temperature reading may be generated by the thermometer circuit using signals output from the plurality of interchangeable bandpass filters. If the thermometer is not equilibrated, the temperature reading may optionally be corrected at 2530. Upon completion of 2528 or 2530, method 2500 continues to 2532 in FIG. 25B.

[0124] As shown in Figure 25B, 2532 involves performing an operation of selecting a threshold value by a processor or computing device. The threshold value may be selected from a number of threshold values ​​based on the subject's average temperature over a given time period, the difference between the measured temperature values ​​in a given series of measurements, a trend in the measured temperature values, and / or a weighted combination of the measured temperature values. Optionally, at 2534, the temperature measurement is compared to the threshold value. At 2536, an output may be provided from the thermometer based on the comparison result.

[0125] At optional 2532, the processor and / or computing device detects a skin condition of the individual based on the sensor data. The detected skin condition may be used to validate the temperature reading at 2534. The temperature reading may be discarded if determined to be invalid or output from the thermometer if determined to be valid.

[0126] At 2536, the thermometer optionally periodically and automatically generates a baseline temperature reading for the subject individual. The processor and / or computing device may detect when the baseline temperature reading falls outside a particular range, as shown at 2538. At 2540, information may be output from the thermometer. The information may include an indicator that the baseline temperature reading falls outside a particular range. Alternatively or additionally, the information may include suggestions for addressing a medical condition of the subject individual.

[0127] Optionally, the thermometer is caused to measure the air temperature of the surrounding environment at 2544. The air temperature measurement may be communicated from the thermometer to an external device (e.g., a heating, ventilation and air conditioning system) at 2544. Method 2500 then ends or another operation is performed (e.g., returning to 2502).

[0128] Referring now to Figure 26, a flow diagram of an example method 2600 for operating a thermometer (e.g., thermometers 102, 120 of Figure 1, 202-218 of Figure 2, and / or 300 of Figure 3) is shown. The solution is not limited to the specific order in which the operations are performed in Figure 26. Two or more operations may be performed in a different order relative to that shown in Figure 26.

[0129] Method 2600 starts at 2602 and continues to 2604. At 2604, a processor (e.g., CPU 406 of FIG. 4) or computing device (e.g., computing device 306 of FIG. 3) obtains sensor data generated by sensors (e.g., sensors 312, 326, and / or 328 of FIG. 3) located at different locations within the thermometer. The sensors may include, but are not limited to, humidity sensor(s), temperature sensor(s), accelerometer(s), mechanical shock / vibration sensor(s), scent / odor sensor(s), position sensor(s), camera(s), and / or microphone(s). The different locations may include, but are not limited to, adjacent to the thermometer's internal processor or computing device, on the thermometer's printed circuit board, embedded within the thermometer's housing, and / or on the housing. The sensor data may include, but is not limited to, the temperature of the thermometer's electronics, the temperature of the thermometer's printed circuit board, the temperature at a reference point inside the thermometer, the temperature of the environment outside the thermometer, the humidity inside the thermometer housing, the humidity of the external environment, any shock and / or vibration experienced by the thermometer, any acceleration and / or other movement of the thermometer, sounds inside the thermometer, sounds outside the thermometer, any scents / odors inside and / or outside the thermometer, the position of the thermometer, and / or objects in the vicinity of the thermometer.

[0130] At 2606, the sensor data is analyzed to detect anomalies or patterns therein. The anomalies or patterns may be detected using machine learning algorithms. The anomalies or patterns may indicate whether the thermometer is equilibrated. At 2608, based on the anomalies or patterns, the operation of the thermometer may be modified. The modifications may include, but are not limited to, transitioning an operational mode of the thermometer and / or adjusting the temperature reading according to an offset value selected or determined based on the detected anomalies or patterns.

[0131] At 2610, a machine learning algorithm can be used to predict measurement errors, system failures or malfunctions based on the detected anomalies or patterns. The machine learning algorithm can be trained to detect a combination of at least two of temperature measurements, humidity measurements, device vibrations, applied external forces, predetermined types of sounds, odors, proximity of predetermined types of objects, device deformation, device movement, and device location. Then, 2612 is executed where method 2600 ends or another operation is executed (e.g., returning to 2602).

[0132] While the present solution has been shown and described with respect to one or more implementations, equivalent modifications and alterations will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. Moreover, while a particular feature of the present solution may be disclosed with respect to only one of several implementations, such feature may be combined with one or more other features of other implementations as may be desirable or advantageous for any or a particular application. Thus, the breadth and scope of the present solution should not be limited by any of the above-described embodiments. Rather, the scope of the present solution should be defined in accordance with the following claims and their equivalents.

Claims

1. A method for operating a thermometer, comprising: generating first sensor data by at least one first sensor of the thermometer; analyzing the first sensor data by a processor of the thermometer to obtain a distance value defining a distance between a body surface of a target individual to which the thermometer is directed and the thermometer; modifying a sensitivity of a thermometer circuit by the processor based on the distance value; generating a body temperature measurement value for the target individual by the thermometer circuit.

2. The method according to claim 1, further comprising, by the processor, performing an operation of aligning the thermometer circuit with a target point on the target individual without assistance from a user of the thermometer.

3. The method according to claim 1, further comprising, by the processor, causing the thermometer to measure an air temperature of a surrounding environment.

4. The method according to claim 3, further comprising, by the processor, transmitting an air temperature measurement value from the thermometer to a heating, ventilation, and air conditioning system.

5. The method according to claim 1, further comprising transitioning the thermometer to a hypothermia or hyperthermia operation mode in which an accurate body temperature measurement value can be generated in a temperature range of 30°C to 34°C or 40°C to 42°C.

6. The method according to claim 1, further comprising preventing infection spread by using a surface of the thermometer formed at least partially of an antibacterial material.

7. The method according to claim 1, further comprising, by the processor, detecting a change in an air flow inside or outside the thermometer.

8. The method according to claim 7, further comprising, by the processor, detecting the presence of an operating fan in the vicinity of the thermometer based on the detected change in the air flow. Claim 9 The method according to claim 8, further comprising dynamically adjusting the operation of the thermometer in consideration of the assumed influence of the fan in operation on temperature measurement. Claim 10 The method according to claim 1, further comprising detecting, by the processor, excessive moisture on the surface of the target individual. Claim 11 The method according to claim 10, further comprising causing the thermometer to output, by the processor, a notification of the presence of the excessive moisture. Claim 12 The method according to claim 1, further comprising selecting, by the processor, one method from among a plurality of temperature measurement methods to be used by the thermometer circuit to generate the body temperature measurement value for the target individual. Claim 13 The method according to claim 12, wherein the plurality of temperature measurement methods includes a method based on a shutter, a method based on a multi-temperature sensor, and a method based on an exchangeable filter. Claim 14 The method according to claim 12, further comprising causing the processor to transition the thermometer circuit between a first and a second method of the plurality of temperature measurement methods based on at least one of second sensor data, the distance value, the state of the internal environment of the thermometer, the state of the external environment of the thermometer, the body part of the target individual closest to the thermometer, and the medical condition of the target individual. Claim 15 The method according to claim 12, further comprising causing the processor to transition the thermometer circuit between a first and a second method of the plurality of temperature measurement methods in response to a trigger event. Claim 16 The method according to claim 15, wherein the trigger event includes a user-software interaction, the activation of an input device, the movement of the thermometer to a specific geographical location, a temperature measurement value exceeding a threshold, or a change in the sensitivity of a temperature sensor. Claim 17 The body temperature measurement value is generated by the thermometer circuit using signals output from a plurality of replaceable bandpass filters, according to the method of claim 1.

18. The method according to claim 1, further comprising detecting a skin condition of the target individual based on second sensor data and confirming the validity of the body temperature measurement value using the detected skin condition.

19. The method according to claim 1, further comprising periodically and automatically generating a reference temperature measurement value for the target individual and detecting when the reference temperature measurement value deviates from a specific range.

20. The method according to claim 19, further comprising causing the thermometer to output an indicator indicating that a deviation of the reference temperature measurement value from the specific range has been detected.

21. The method according to claim 19, further comprising causing the thermometer to output a proposal for dealing with the medical condition of the target individual when a deviation of the reference temperature measurement value from the specific range is detected.

22. The method according to claim 1, further comprising correcting the body temperature measurement value generated for the target individual when second sensor data indicates that the thermometer is not balanced.

23. The method according to claim 1, further comprising selecting a threshold value from a plurality of threshold values based on at least one of an average temperature of the target individual over a predetermined period, a difference between measurement temperature values in a predetermined series of measurements, a trend of the measurement temperature values, and a weighted combination of the measurement temperature values.

24. The method according to claim 23, further comprising providing an output from the thermometer based on a comparison result between the body temperature measurement value generated for the target individual and the selected threshold value.

25. A non-transitory computer-readable medium storing instructions for causing at least one computing device to execute, the instructions causing the at least one computing device to, cause at least one first sensor of a thermometer to generate first sensor data; obtain a distance value that defines a distance between a body surface of a target individual to which the thermometer is directed and the thermometer by analyzing the first sensor data; correct the sensitivity of a thermometer circuit based on the distance value; generate a body temperature measurement value for the target individual, and execute operations including the above. A computer-readable medium.

26. A thermometer, a plurality of sensors in which at least one sensor generates first sensor data; a thermometer circuit that generates at least a body temperature measurement value for a target individual; (i) obtain a distance value that defines a distance between a body surface of a target individual to which the thermometer is directed and the thermometer by analyzing the first sensor data, and (ii) a processor that corrects the sensitivity of the thermometer circuit based on the distance value; A thermometer comprising:

27. A method for operating a thermometer, obtaining sensor data generated by a plurality of sensors provided at different locations within the thermometer by a computing device, detecting an abnormality or pattern by analyzing the sensor data by the computing device, and a method comprising modifying the operation of the thermometer based on the abnormality or pattern by the computing device.

28. The method according to claim 27, wherein the plurality of sensors includes at least one of a humidity sensor, a temperature sensor, an accelerometer, a mechanical shock / vibration sensor, a scent / odor sensor, a position sensor, a camera, and a microphone.

29. The method according to claim 27, wherein the different locations include at least one of a location adjacent to the internal processor or computing device of the thermometer, a location on the printed circuit board of the thermometer, an embedded location within the housing of the thermometer, and a location on the housing.

30. The sensor data includes at least one of the temperature of the electronic components of the thermometer, the temperature of the printed circuit board of the thermometer, the temperature at a reference location inside the thermometer, the temperature of the external environment of the thermometer, the humidity inside the thermometer housing, the humidity of the external environment, any shock and / or vibration received by the thermometer, any acceleration and / or other movement of the thermometer, the sound inside the thermometer, the sound outside the thermometer, any smell / odor inside and / or outside the thermometer, the position of the thermometer, and / or at least one object near the thermometer. The method according to claim 27.

31. The method according to claim 27, wherein the abnormality or pattern is detected using a machine learning algorithm.

32. The method according to claim 31, further comprising predicting a measurement error, a system failure, or a malfunction based on the detected abnormality or pattern using the machine learning algorithm.

33. The machine learning algorithm of claim 31 is trained to detect a combination of at least two of temperature measurement values, humidity measurement values, device vibration, applied external force, a predetermined type of sound, odor, proximity of a predetermined type of object, device deformation, device movement, and device position. The method according to claim 31.

34. The method according to claim 27, wherein the detected abnormality or pattern indicates whether the thermometer is in equilibrium.

35. The method according to claim 27, wherein the correction includes transitioning the operating mode of the thermometer.

36. The method according to claim 27, wherein the correction includes adjusting a temperature measurement value according to an offset value selected or determined based on the detected abnormality or pattern. **Claim 37** A non-transitory computer-readable medium storing instructions for causing at least one computing device to perform operations, the instructions causing the at least one computing device to obtain sensor data generated by a plurality of sensors provided at different locations within a thermometer; detect an abnormality or pattern by analyzing the sensor data; correct the operation of the thermometer based on the abnormality or pattern; and perform operations including the above. **Claim 38** A plurality of sensors provided at different locations within a thermometer and generating sensor data; A thermometer circuit generating at least a body temperature measurement value for a target individual; A processor that obtains the sensor data, detects an abnormality or pattern by analyzing the sensor data, and corrects at least the operation of the thermometer circuit based on the abnormality or pattern; A thermometer comprising the above.

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