Calorie estimation apparatus and method

Abstract

A calorie estimation apparatus for automatically tracking a user's consumed calories comprises; a main body having a contact site configured to be placed against a user's skin; a heat flux sensor arranged at the contact site and configured to provide a signal indicative of a signed heat transfer rate per unit area between the user's skin and the main body at the contact site; one or more auxiliary sensors each sensor configured to provide auxiliary sensor data indicative of at least one of: environmental conditions, user behaviour, or user state; and a processing unit configured to receive the signed heat transfer rate per unit area and the auxiliary sensor data, detect, based on the auxiliary-sensor data, one or more periods of caloric consumption and / or heat-affecting conditions unrelated to caloric consumption, and, in response to detecting a period of caloric consumption, determine changes in the signed heat transfer rate per unit area before, during, and after the detected period of caloric consumption, and estimate calories consumed based on the determined changes.

Description

[0001] CALORIE ESTIMATION APPARATUS AND METHOD TECHNICAL FIELD

[0002] The present invention relates to the field of wearable devices, specifically devices for automatic tracking of a user’s consumed calories through integrated sensors and proprietary algorithms that estimate calories consumed by analyzing data from various thermal sensors and biometric indicators.

[0003] BACKGROUND OF THE INVENTION

[0004] The accurate management of caloric intake is essential for effective weight management and health improvement. Many individuals face challenges in monitoring their daily calorie consumption, often resulting in underestimation that impedes weight loss or maintenance efforts. Traditional calorie intake tracking methods typically rely on manual entries, requiring users to log each meal. This approach can be cumbersome and prone to errors stemming from estimations or lapses in memory.

[0005] While many wearable devices currently offer activity tracking and estimations of calories burned, accurate tracking of calories consumed remains a challenge in the industry. With the advancement of wearable technology, various automated solutions have been attempted to simplify calorie tracking. These devices utilize a range of sensing techniques, such as optical sensors and bioimpedance analysis, to estimate calorie consumption. However, existing solutions often encounter obstacles such as high energy consumption, susceptibility to environmental factors, and issues with accuracy.

[0006] SUMMARY OF THE INVENTION

[0007] Numerous objects and advantages, which will be evident from the description of the present invention, are according to a first aspect of the present invention obtained by:

[0008] A calorie estimation apparatus for automatically tracking a user’s consumed calories, the calorie estimation apparatus comprising; a heat flux sensor configured to measure the flow of heat between the human body of a user and the user’s environment; a plurality of auxiliary sensors configured to detect periods of caloric consumption; and / or to detect heat affecting conditions caused by other effects than consumption of calories; a processing unit configured to determine changes in the flow of heat before, during and after a period of caloric consumption; and estimate calories consumed by the user based on determined changes in the flow of heat. The calorie estimation apparatus comprises a main body having a contact site configured to be placed against a user’s skin. The main body provides structural support and houses, or is operatively coupled to, functional components of the calorie estimation apparatus, including, for example, the processing unit, power source, communication interface(s), the heat flux sensor, and one or more of the auxiliary sensors and / or support sensors described herein. The main body may include one or more modules. As used herein, a “module” denotes a physically distinct or separable sub-assembly — e.g., a housing portion, strap-borne pod, adhesive patch, clip-on unit, or garment-integrated unit — mechanically and / or electrically coupled to the rest of the calorie estimation apparatus by wired and / or wireless connections. In multi-module embodiments, the contact site may be provided by any one module, by a plurality of modules, or by any combinations thereof. References herein to “the contact site” encompass at least one contact site configured to be placed against a user’s skin, provided by the main body unless the context clearly indicates otherwise. The heat flux sensor is arranged at the contact site (as defined herein). The auxiliary and / or support sensors may be disposed at the contact site including being colocated with the heat flux sensor, elsewhere on a portion of the main body other than the contact site, and / or within one or more modules of the calorie estimation apparatus.

[0009] By the flow of heat between the human body of the user and the user’s environment is to be understood the rate of heat energy that passes through the skin of the user.

[0010] A plurality of biological processes generate heat within the human body. To maintain a stable core body temperature, the human body exchanges heat with the environment. The heat flux sensor is configured to capture data on this exchange of heat between the user and the user’s environment.

[0011] As used herein, a heat flux sensor, is any transducer, sensing assembly, or combination thereof that directly measures, or provides a signal from which one can determine, a signed heat transfer rate per unit area (expressed in power-per-area units, e.g., W / m2). For clarity, a heat flux sensor differs from a skin-temperature sensor which is limited to reporting temperature (e.g., °C) at a point on the skin and, as a skin-temperature sensor by itself, does not quantify neither the rate nor the direction of heat transfer.

[0012] As used herein, the “flow of heat between the human body of the user and the user’s environment” denotes the signed heat transfer rate per unit area between the user’s skin and the main body at the contact site (expressed in power-per-area units, e.g., W / m2). The environment comprises media and structures external to the skin, including, without limitation, ambient air, clothing, and device surfaces such as the main body. In this disclosure, that body-environment flow is operationally quantified at the contact site: specifically, the signed heat transfer rate per unit area between the user’s skin and the main body at the contact site.

[0013] The sign convention used herein is as follows: positive values indicate heat flowing out of the body toward the environment — corresponding, at the contact site, to heat flowing from the skin into the main body — and negative values indicate heat flowing into the body from the environment — corresponding, at the contact site, to heat flowing from the main body into the skin. This sign convention will be used throughout the description, but a person skilled in the art will understand that the apparatus and method are likewise applicable with a reverse sign convention. Unless the context indicates otherwise, references to “changes in the flow of heat” refer to changes in the signed heat transfer rate per unit area between the user’ s skin and the main body at the contact site.

[0014] The invention is not limited to a particular heat flux sensing principle. In various embodiments, the heat flux sensor is implemented using at least one of the following, individually or in any combination:

[0015] i) a passive gradient arrangement configured to sense a temperature difference across a known thermal path and to provide a signal indicative of the signed heat transfer rate per unit area; ii) an active isothermal arrangement configured to maintain a controlled interface temperature and to provide a signal indicative of the signed heat transfer rate per unit area based on control power;

[0016] iii) one or more thermoelectric Seebeck-effect transducers selected from the group consisting of thermocouples and thermopiles, and configured to provide a signal indicative of the signed heat transfer rate per unit area;

[0017] iv) a calorimetric power-balance assembly configured to provide a signal indicative of the signed heat transfer rate per unit area based on power required to hold a defined thermal condition, normalized by a known or calibrated effective area;

[0018] v) a thin-film heat flux sensor, a microelectromechanical systems (MEMS) heat flux sensor, or a thin-film MEMS heat flux sensor integrated into a wearable assembly and configured to provide a signal indicative of the signed heat transfer rate per unit area;

[0019] vi) a multi-sensor arrangement including two or more temperature sensors, wherein the processing unit executes a thermal model with known or calibrated parameters to compute the signed heat transfer rate per unit area. In one non-limiting embodiment, the heat flux sensor is a thermopile -based transducer arranged at the contact site and configured to provide a signal indicative of a signed heat transfer rate per unit area between the user’s skin and the main body at the contact site.

[0020] A heat flux measurement at the contact site (as defined herein) provides technical advantages over a single-point skin-temperature measurement as well as multiple skin-temperature measurements that are not configured and / or calibrated to compute a signed heat transfer rate per unit area:

[0021] A heat flux measurement delivers a directional, quantitative signal in power-per-area units (e.g., W / m2) that quantifies how much heat is transferred and in which direction. Under ordinary thermal conditions — i.e., when local skin temperature exceeds ambient temperature at the measurement site — outward heat flow increases after periods of caloric consumption. When environmental and / or physiological factors produce an inward gradient (for example, ambient temperature exceeding local skin temperature), the heat flux measurement remains informative by quantifying inward heat transfer and preserving directionality, aiding discrimination between environmental heating and body-generated heat release . Because a heat flux measurement reports rate and direction rather than absolute temperature alone, heat flux measurement is often more informative and faster-responding than skin-temperature readings. A multi-sensor arrangement comprising a plurality of temperature sensors that are calibrated to output a signed heat transfer rate per unit area, is considered a heat flux measurement in the context of the present disclosure.

[0022] As used herein, “flow of heat data” is to be understood as, data indicative of a signed heat transfer rate per unit area (e.g., W / m2) between the user’s skin and the main body at the contact site, as provided by a heat flux sensor arranged at the contact site.

[0023] The calorie estimation apparatus is configured to continuously capture data from the user, e.g. over the course of the full day. Continuous data capture allows the device to monitor caloric consumption events and variations in physiological metrics consistently, contributing to more accurate overall estimations of caloric intake. However, in certain embodiments, effective calorie estimation may be achieved based on data captured during a limited timeframe. In one variant it may be sufficient to track data from the beginning of a meal and for a post-period following said meal. In some preferred variants the post-period may be one to six hours after ended calorie consumption, preferably two to four hours after ended calorie consumption, such as approximately 3 hours post-consumption. In a more preferred embodiment, the tracking may include a pre -consumption period before the beginning of a meal. In a preferred variant the preconsumption period is shorter than the post-consumption period, such as one to sixty minutes, preferably five to fifteen minutes. This shorter data capture period may be suitable for effective caloric estimation based on changes in the flow of heat following caloric intake, providing flexibility in operation while still enabling accurate readings.

[0024] The processing unit may be configured to utilize the detected changes in the flow of heat to estimate calories consumed by comparing the detected changes in the flow of heat to reference data that represents caloric consumption events. The reference data may be derived from historical data associated with the user and / or from a dataset encompassing a plurality of users.

[0025] By reference data is to be understood at least one pairing of a caloric consumption event with a known caloric content, and an associated flow of heat measured before, during and / or after the caloric consumption event.

[0026] The detection of periods of caloric consumption refers to identifying at least one event during which a substance containing caloric content is ingested by the user. The detection may capture the onset, duration, and / or conclusion of such an event. By caloric consumption events is to be understood the intake of food and / or beverages that contain caloric value.

[0027] The detection of periods of caloric consumption enables the processing unit to automatically initiate estimation of calories consumed after each detected consumption event. This automated trigger allows the calorie estimation apparatus to deliver near-real-time calorie estimates to the user without requiring manual input, enhancing user convenience by providing immediate feedback based on detected caloric consumption.

[0028] The processing unit may utilize contextual data, such as health information or historical calorie consumption patterns, to improve the accuracy of the calorie estimation.

[0029] By health information is to be understood data relating to the user’s known health conditions, medical history, and other personal health factors that may influence caloric intake and / or metabolism. This may include, but is not limited to, information about known diseases, medical diagnoses, prescribed medications, allergies, dietary restrictions, and / or any other relevant physiological characteristics and / or conditions. Such health information may be used by the processing unit to adjust or refine calorie estimation, ensuring that estimations are tailored to the individual user’s health profile. The auxiliary sensors are configured to detect periods of caloric consumption, and / or to detect heat affecting conditions caused by other effects than consumption of calories. The auxiliary sensors may include, but are not limited to, sensors for measuring ambient temperature, skin temperature, heart rate, pulse, and physical movement. In certain embodiments, these sensors may detect external temperature conditions, fluctuations in skin surface temperature, changes in pulse rate, and user activity patterns. For instance, an accelerometer and / or gyroscope sensor may be utilized to detect movement that might impact the flow of heat data. In certain embodiments, the auxiliary sensors may be used in combination and / or in varying quantities, such as multiple ambient temperature sensors positioned at different locations, to enhance the accuracy of caloric estimation under different environmental and physical conditions. The specific arrangement and types of auxiliary sensors may be adjusted and / or expanded as necessary to suit the application, ensuring flexibility in the configuration of the calorie estimation apparatus.

[0030] The calorie estimation apparatus may include at least one auxiliary sensor. In other preferable variants the calorie estimation apparatus may comprise a plurality of auxiliary sensors. In some variants the calorie estimation apparatus having a plurality of auxiliary sensors may have the auxiliary sensors arranged in configurations with two or more sensors positioned in different locations, depending on the application.

[0031] In certain embodiments, the calorie estimation apparatus includes one or more auxiliary sensors, each sensor configured to provide auxiliary sensor data indicative of at least one of: environmental conditions, user behavior or user state. Auxiliary sensor data may for example include signals from one or more of: ambient-temperature sensors, skin-temperature sensors, heart-rate and / orpulse sensors, accelerometer and / or gyroscope sensors. The processing unit then receives the auxiliary sensor data and detects, based on the auxiliary sensor data, one or more periods of caloric consumption and / or heat-affecting conditions unrelated to caloric consumption.

[0032] In operation, detections obtained from the auxiliary sensor data may be used by the processing unit to segment the signed heat transfer rate per unit area to pre -ingestion, ingestion, and post-ingestion windows. Auxiliary sensor data may also be used to gate and / or validate intervals used for estimating calories consumed, and / or to exclude or flag intervals affected by heat-affecting conditions other than caloric consumption for example, environmental heating / cooling or vigorous movement. Hence, the auxiliary sensor data may contribute to ensuring that the estimate of calories consumed remains based on determined changes in the signed heat transfer rate per unit area under appropriate conditions. As used herein, “heat-affecting conditions” are conditions that alter the signed heat transfer rate per unit area at the contact site independently of caloric consumption (i.e., conditions that are not caused by the ingestion of food or drink). Non-limiting examples include:

[0033] i) Abrupt ambient-temperature changes (entering / exiting climate-controlled spaces).

[0034] ii) Vigorous movement

[0035] iii) Physiological states unrelated to intake (fever / chills; exercise- or stress-induced vasomotor changes).

[0036] When such conditions are detected from the auxiliary sensor data, the affected intervals may be gated, down-weighted, or excluded during estimation.

[0037] By “user state” is to be understood, an internal, physiological condition of the user — distinct from environment and behavior — indicated by sensor outputs or derived indicators. The user state may for example include changes in the user’s thermoregulation, the cardiovascular system, respiratory cycles, sleep cycles, hydration levels, stress levels, and / or hormonal phases.

[0038] In some embodiments, the processing of auxiliary sensor data is performed in whole or in part at an auxiliary sensor — for example, by on-sensor logic that outputs a detection indicator — in which case the processing unit receives the detection indicator as part of the auxiliary sensor data and performs the detection of one or more periods of caloric consumption and / or heat-affecting conditions unrelated to caloric consumption based on that indicator and / or other auxiliary sensor data.

[0039] According to a further embodiment of the first aspect of the invention, the calorie estimation apparatus may further include: A support sensor configured to provide additional data to increase the accuracy of the estimate of calories consumed.

[0040] The support sensor may comprise at least one sensor and, in certain embodiments, may include a plurality of support sensors configured to work in combination and / or independently to provide additional data, thereby enhancing the accuracy of the calorie estimation.

[0041] In some embodiments, one or more support sensors provide physiological data used for increasing the accuracy of the estimate of calories consumed, whereas one or more auxiliary sensors provide context and / or physiological data used for enabling and / or conditioning the calorie estimation process. In some embodiments, the auxiliary sensors may be used to increase the accuracy of the estimate of calories consumed by gating and / or weighting the determined changes in the signed heat transfer rate per unit area. The one or more support sensors and the one or more auxiliary sensors may be co-located, placed at different locations or any combinations thereof.

[0042] In some embodiments, one or more support sensors may be the same type of sensor and / or sensing technology as the one or more auxiliary sensors.

[0043] In some embodiments, one or more support sensors provides physiological data from which the processing unit computes one or more derived quantities (e.g., a vascular dilation indicator, a local circulation indicator, and / or other physiological metrics). During the estimation of calories consumed, selected derived quantities are combined with the heat flux sensor’s signal indicative of the signed heat transfer rate per unit area and / or the determined changes in the signed heat transfer rate per unit area, to increase the accuracy of the estimate of calories consumed. The increase in accuracy is achieved by using the selected derived quantities to perform at least one of:

[0044] i) assigning weights to respective time portions of the signed heat transfer rate per unit area; ii) tuning a person-specific conversion from the signed heat transfer rate per unit area to calories consumed;

[0045] iii) updating model parameters representing local blood flow and heat transfer at the measurement site.

[0046] In some embodiments, the support sensor may be an optical sensor configured to measure the dilation of one or more blood veins over time. As used herein, “an optical sensor configured to measure the dilation of one or more blood veins over time”, is to be understood, as acquiring optical signals from tissue of the user. The processing unit is then configured to determine, from the optical signals, a vascular dilation indicator that varies with blood-vessel caliber and / or local blood content over time; direct imaging of any individual vein or its absolute diameter is not required. In certain embodiments, the optical signals may include reflected-light measurements at one or more wavelengths; however, the invention is not limited to any specific optical modality.

[0047] In some embodiments, the support sensor is an optical sensor configured to acquire optical signals from tissue of the user. The optical sensor may for example be configured to perform reflective photoplethysmography (PPG) or near-infrared spectroscopy (NIRS) using one or more wavelengths. From the optical signals, the processing unit generates a vascular dilation indicator that serves as a proxy for vasomotor activity, i.e., a time-varying quantity reflecting changes in blood-vessel caliber and / or local blood content over time. When estimating calories consumed, the processing unit combines the vascular dilation indicator with at least one of:

[0048] i) a signal from the heat flux sensor indicative of the signed heat transfer rate per unit area between the user’s skin and the main body at the contact site;

[0049] ii) the determined changes in the signed heat transfer rate per unit area.

[0050] In some implementations, the processing unit uses the vascular dilation indicator to perform at least one of:

[0051] i) assigning weights to respective time portions of the signed heat transfer rate per unit area; ii) tuning a person-specific conversion from the signed heat transfer rate per unit area to calories consumed;

[0052] iii) updating model parameters representing local blood flow and heat transfer at the measurement site.

[0053] In some embodiments, the support sensor is a bioimpedance sensor. The bioimpedance sensor is configured to acquire electrical signals from tissue of the user. The processing unit is then configured to generate, from the acquired signals, a local circulation indicator that serves as a proxy for vasomotor activity, i.e. a time-varying quantity reflecting changes in local blood volume and / or blood flow through small vessels. When estimating calories consumed, the processing unit combines the local circulation indicator with at least one of:

[0054] i) the signal from the heat flux sensor being indicative of the signed heat transfer rate per unit area at or near the skin-device interface

[0055] ii) the determined changes in the signed heat transfer rate

[0056] In some implementations, the processing unit uses the local circulation indicator to perform at least one of:

[0057] i) assigning weights to respective time portions of the signed heat transfer rate per unit area; ii) tuning a person-specific conversion from the signed heat transfer rate to calories consumed; iii) updating model parameters representing local blood flow and heat transfer at the measurement site.

[0058] As used herein, “bioimpedance sensor” is to be understood as any sensor configured to determine the electrical impedance of tissue (impedance magnitude and / or phase) using skin contact, without requiring any particular electrode arrangement, frequency, or material.

[0059] A benefit of the support sensor is that it may be used to improve the accuracy of the calorie estimation. In the context of the present invention, improved accuracy may be understood as a reduction in at least one statistical measure, such as the Root Mean Square Error (RMSE). According to a further embodiment of the first aspect of the invention, the calorie estimation apparatus may further include: a calorie database configured to store historical data related to the user’s past caloric consumption.

[0060] This calorie database may retain records of previous calorie estimations and / or consumption patterns overtime.

[0061] The processing unit may utilize data from the calorie database to refine and / or adjust new calorie estimations based on the user’s historical caloric intake, allowing for modifications in the estimation process to account for individual consumption habits and / or patterns. In certain embodiments, the calorie database may be updated periodically to reflect the user’s most recent consumption data, thereby enhancing the accuracy of future calorie estimations.

[0062] According to a further embodiment of the first aspect of the invention, the calorie estimation apparatus may be configured as a wearable device comprising dressing means.

[0063] By dressing means is understood any arrangement for attaching the calorie estimation apparatus to the user, such as a strap allowing the apparatus to be worn on the wrist, ankle, and / or another suitable body part, and / or as apparel with the calorie estimation unit integrated, such as being sewn into lining. In certain embodiments, the wearable device may be integrated into clothing, accessories, and / or other items that maintain contact with the user's body.

[0064] In some embodiments, the calorie estimation apparatus may comprise a single main body and / or may be configured as a distributed device with two or more modules. For example, the calorie estimation apparatus may include a heat flux sensor positioned on the wrist while additional auxiliary sensors may be arranged at different positions on a strap and / or integrated into various items of clothing, such as a belt, patch, and / or hat. This configuration enables the distribution of sensors throughout one or more dressing means to optimize data accuracy and comfort for the user.

[0065] The calorie estimation apparatus may further include an integrated display that allows the user to monitor tracked calorie consumption. The display may show information on calories consumed over a predefined period, such as daily intake, and / or display target calorie consumption goals. In some configurations, the calorie estimation unit may forgo a display, with data accessible exclusively through an external device. Alternatively, the device may be equipped with a display while also transmitting data to an external unit, allowing simultaneous access to calorie data on the integrated display and the external unit.

[0066] In certain embodiments, the calorie estimation apparatus may be configured to transmit sensor data and / or estimated calories consumed information to an external unit (such as a smartphone or computer) via wireless communication. This configuration allows the user to view and track calorie consumption through an app and / or an external unit. In some embodiments, the calorie estimation unit may display the same information on both the integrated display and the app, while in other configurations, only a subset of the data may be shown on the integrated display (such as the most recent calorie consumption), with complete data available in the app.

[0067] Another object of the present invention is to provide a method for automatically tracking a user’s calories consumed. According to a second aspect of the present invention, the above objects and advantages are obtained by:

[0068] Capturing data on the flow of heat between the human body of a user and the user’ s environment; detecting periods of caloric consumption; and / or detecting heat affecting conditions caused by other effects than consumption of calories; detecting changes in the flow of heat before, during and / or after a period of caloric consumption; and estimating calories consumed based on determined changes in the flow of heat.

[0069] By capturing data on the flow of heat between the human body of the user and the user’s environment is to be understood capturing data on the rate of heat energy that passes through the skin of the user.

[0070] For the purposes of the foregoing method, the expression “flow of heat between the human body of the user and the user’s environment” has the meaning as defined herein, namely, the signed heat transfer rate per unit area between the user’s skin and the main body at the contact site.

[0071] In certain embodiments, the step of capturing data relating to the flow of heat comprises obtaining the signed heat transfer rate per unit area (as defined herein) using at least one of the following implementations, individually or in any combination:

[0072] i) a passive gradient arrangement configured to sense a temperature difference across a known thermal path and to provide a signal indicative of the signed heat transfer rate per unit area; ii) an active isothermal arrangement configured to maintain a controlled interface temperature and to provide a signal indicative of the signed heat transfer rate per unit area based on control power; iii) one or more thermoelectric Seebeck-effect transducers selected from the group consisting of thermocouples and thermopiles, and configured to provide a signal indicative of the signed heat transfer rate per unit area;

[0073] iv) a calorimetric power-balance assembly configured to provide a signal indicative of the signed heat transfer rate per unit area based on power required to hold a defined thermal condition, normalized by a known or calibrated effective area;

[0074] v) a thin-film heat flux sensor, a microelectromechanical systems (MEMS) heat flux sensor, or a thin-film MEMS heat flux sensor integrated into a wearable assembly and configured to provide a signal indicative of the signed heat transfer rate per unit area;

[0075] vi) a multi-sensor arrangement including two or more temperature sensors, wherein the processing unit executes a thermal model with known or calibrated parameters to compute the signed heat transfer rate per unit area.

[0076] In certain embodiments, obtaining the signed heat transfer rate per unit area employs any of the heat flux sensing implementations described herein for the apparatus aspect items i)-vi), individually or in combination. The method may include calibration at manufacture and / or in the field, to map transducer output to W / m2with outward flow positive and inward flow negative.

[0077] In a preferred embodiment of the invention, data is captured from the user over the course of the full day. Continuous data capture allows the device to monitor caloric consumption events and variations in physiological metrics consistently, contributing to more accurate overall estimations of caloric intake. However, in certain embodiments, effective calorie estimation may be achieved based on data captured during a limited timeframe. In one variant it may be sufficient to track data from the beginning of a meal and for a post-period following said meal. In some preferred variants the post-period may be one to six hours after ended calorie consumption, preferably two to four hours after ended calorie consumption, such as approximately 3 hours post-consumption. In a more preferred embodiment, the tracking may include a pre-consumption period before the beginning of a meal. In a preferred variant the pre-consumption period is shorter than the postconsumption period, such as one to sixty minutes, preferably five to fifteen minutes. This shorter data capture period may be suitable for effective caloric estimation based on changes in the flow of heat following caloric intake, providing flexibility in operation while still enabling accurate readings.

[0078] The estimation of calories consumed may include: Utilizing the detected changes in the flow of heat by comparing the detected changes in the flow of heat to reference data that represents caloric consumption events. The reference data may be derived from historical data associated with the user and / or from a dataset encompassing a plurality of users.

[0079] The estimation of calories consumed may include: Utilizing contextual data, such as health information or historical calorie consumption patterns, to improve the accuracy of the calorie estimation.

[0080] Detecting periods of caloric consumption, and / or detecting heat affecting conditions caused by other effects than consumption of calories may include: Capturing data on physiological metrics. These physiological metrics may include, but are not limited to, ambient temperature, skin temperature, heart rate, pulse, and physical movement. Data capture may involve one or more auxiliary sensors that monitor conditions in the user’s immediate environment and / or on the user’s skin to provide context for the caloric estimation process. In certain embodiments, data on external temperature conditions, variations in skin surface temperature, changes in heart rate and / or pulse, and / or patterns of physical movement may be recorded to detect factors that influence the flow of heat data. For example, data from an accelerometer and gyroscope may be captured to assess user movement that could affect the reliability of the flow of heat data.

[0081] Capturing data from auxiliary sensors may be conducted continuously and / or intermittently, depending on the intended application. In some configurations, multiple auxiliary sensors may be deployed to capture data from different locations on and / or near the user's body, enhancing the accuracy and robustness of the caloric estimation.

[0082] In certain embodiments, the step of detecting one or more periods of caloric consumption and / or detecting heat-affecting conditions unrelated to caloric consumption, is performed by the processing unit that receives the auxiliary sensor data, and performs the detection based on the received auxiliary sensor data. The auxiliary sensor data may be indicative of at least one of: environmental conditions, user behavior and user state. Auxiliary sensor data may for example comprise signals detected by one or more of: ambient-temperature sensors, skin-temperature sensors, heart-rate and / or pulse sensors, accelerometer and / or gyroscope sensors. Detections obtained from the auxiliary sensor data may be used to segment the signed heat transfer rate into pre-ingestion, ingestion, and post-ingestion windows. Auxiliary sensor data may also be used to gate and / or validate intervals used for estimating calories consumed; and / or to exclude or flag intervals affected by heat-affecting conditions other than caloric consumption for example, environmental heating / cooling and vigorous movement. Hence, the auxiliary sensor data may contribute to ensuring that the estimate of calories consumed remains based on determined changes in the signed heat transfer rate under appropriate conditions. In other embodiments, the processing of auxiliary sensor data is performed in whole or in part at an auxiliary sensor — for example, by on-sensor logic that outputs a detection indicator — in which case the processing unit receives the detection indicator as part of the auxiliary sensor data and performs the detection of one or more periods of caloric consumption and / or heat-affecting conditions unrelated to caloric consumption based on that indicator and / or other auxiliary sensor data.

[0083] In the method according to the second aspect of the invention, the process of enhancing calorie estimation accuracy may include: Capturing of additional data using at least one support sensor to increase the accuracy of the estimate of calories consumed.

[0084] In certain embodiments, the capture of additional data may involve a plurality of support sensors configured to operate either in combination and / or independently to provide supplementary data, which contributes to the accuracy of the calorie estimation.

[0085] In some embodiments, the support sensor may be an optical sensor configured to capture data related to the dilation of one or more blood veins over time. This data on blood vein dilation, along with other physiological metrics, may be utilized to refine the calorie estimation, providing additional context that contributes to more precise calculations.

[0086] For the purposes of the foregoing method, the expression “optical sensor configured to capture data related to dilation of one or more blood veins over time” has the meaning as defined herein, namely an optical sensor configured to acquire optical signals from tissue of the user. The processing unit is then configured to determine, from the optical signals, a vascular dilation indicator that varies over time with one or both of i) blood-vessel caliber and ii) local blood content.

[0087] In certain embodiments, the support sensor is an optical sensor configured to acquire optical signals from tissue of the user (e.g., the support sensor may be configured to perform reflective photoplethysmography (PPG) or near-infrared spectroscopy (NIRS) using one or more wavelengths). The processing unit is then configured to determine, from the acquired optical signals, a vascular dilation indicator — a time-varying quantity that serves as a proxy for vasomotor activity, reflecting changes in blood-vessel caliber and / or local blood content over time. Direct imaging of any individual vessel or its absolute diameter is not required. When estimating calories consumed, the processing unit combines the vascular dilation indicator with at least one of:

[0088] i) the signal from the heat flux sensor indicative of the signed heat transfer rate per unit area; ii) the determined changes in the signed heat transfer rate per unit area.

[0089] In some implementations, the processing unit uses the vascular dilation indicator to perform at least one of:

[0090] i) assigning weights to respective time portions of the signed heat transfer rate per unit area; ii) tuning a person-specific conversion from the signed heat transfer rate per unit area to calories consumed;

[0091] iii) updating parameters of a model representing local blood flow and heat transfer at the measurement site.

[0092] In some embodiments, the support sensor is a bioimpedance sensor configured to acquire electrical signals from tissue of the user. The processing unit then generates, from the acquired electrical signals, a local circulation indicator that varies over time with one or both of i) blood volume, and ii) blood flow. When estimating calories consumed, the processing unit combines the local circulation indicator with at least one of:

[0093] i) the signal from the heat flux sensor indicative of the signed heat transfer rate per unit area; ii) the determined changes in the signed heat transfer rate per unit area.

[0094] In some implementations, the processing unit uses the local circulation indicator to perform at least one of:

[0095] i) assigning weights to respective time portions of the signed heat transfer rate per unit area; ii) tuning a person-specific conversion from the signed heat transfer rate per unit area to calories consumed;

[0096] iii) updating parameters of a model representing local blood flow and heat transfer at the measurement site.

[0097] In certain embodiments of the method according to the second aspect of the invention, the process of estimating calories consumed by the user may include: Utilizing data stored in a calorie database.

[0098] The calorie database may contain historical data on the user’s previous caloric consumption events, including recorded estimations and associated physiological metrics.

[0099] During the calorie estimation process, the method may involve accessing the calorie database to retrieve relevant historical data. This historical data may be used by the processing unit to adjust and / or refine current calorie estimations based on the user’s past consumption patterns, allowing for a more individualized estimation process.

[0100] The calorie database may be updated periodically to include new caloric consumption data, ensuring that the historical record remains current and reflective of the user’s most recent behaviours. This ongoing integration of historical data contributes to enhanced accuracy in future calorie estimations, as adjustments can be made based on evolving consumption patterns.

[0101] In certain embodiments of the method according to the second aspect of the invention, the calorie estimation process may be configured for a wearable device. The method may include: Capturing data from sensors positioned on and / or integrated into a wearable device designed to remain in close proximity to the user’s body.

[0102] The wearable device configuration may involve dressing means to secure the apparatus to the user, such as a strap, belt, patch, and / or other attachment mechanisms, enabling continuous and / or intermittent data capture from various regions of the body. In some embodiments, the method may include capturing data from sensors distributed across one or more wearable device components, such as a wrist strap for a heat flux sensor and / or additional auxiliary sensors positioned on other articles of clothing.

[0103] By close proximity to the user’s body is to be understood a range of up to approximately 0-30 centimetres from the skin, allowing the device to capture data effectively from a distance that remains near the body without requiring direct contact.

[0104] For clarity, the close-proximity range (e.g., 0-30 centimetres) applies to sensors other than the heat flux sensor (e.g., auxiliary sensors and / or support sensors). The heat flux sensor is arranged at the contact site, and the contact site is placed against the user’s skin.

[0105] In certain embodiments, data capture in the wearable device configuration may be specifically adapted to optimize sensor readings and / or ensure accuracy based on the sensor’s placement. For example, data from sensors integrated into a wearable device may be processed to account for physical movement and / or environmental factors that are characteristic of certain wearable device setups, thereby refining the calorie estimation process.

[0106] In some embodiments, the data capture and processing may be configured to operate in a single body or in a distributed arrangement across two or more modules. The method may include capturing data from sensors located on different parts of the user’s body and / or integrated into various wearable device components. For instance, the method may involve capturing heat flux sensor data from a module positioned on the wrist while auxiliary sensors capture additional data from modules integrated into other wearable items, such as belts, patches, or other accessories.

[0107] This modular configuration allows for flexibility in sensor positioning, enabling the method to optimize data accuracy based on the sensor locations and the user’s activity. The ability to capture data from distributed modules enhances the calorie estimation process by providing a comprehensive profile of relevant physiological and environmental metrics.

[0108] In some embodiments, the method may include displaying calorie estimation data on an integrated display within the wearable device. The method may involve presenting the user with information such as calories consumed over a specific timeframe, such as daily intake, and / or displaying target calorie consumption goals.

[0109] In other embodiments, the display may be omitted from the wearable device, with data available exclusively through an external unit. Alternatively, the method may include both displaying data on the wearable device’s display and transmitting data to an external unit, allowing simultaneous access to calories consumed data on the integrated display and the external unit.

[0110] According to certain embodiments of the method, the calorie estimation apparatus may be configured to transmit sensor data and / or calculated calorie estimations to an external unit (such as a smartphone or computer) via wireless communication. The method may involve sending data via wireless communication, allowing the user to access and / or track calorie consumption data on an app or similar interface on the external unit.

[0111] In some configurations, the method may include displaying a subset of the data on the wearable device’s integrated display while providing complete data access via the app. Alternatively, all data may be stored and accessible solely on the external unit, depending on the user’s preferences. This external connectivity enables comprehensive tracking and analysis of calories consumed data, providing flexibility in data access and user interaction.

[0112] Other features and aspects may be apparent from the following detailed description, the drawings and the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0113] In the following, examples of embodiments are described according to the invention, where:

[0114] Figure 1 illustrates an example embodiment of the calorie estimation apparatus in a wearable device configuration, comprising two modules. In this embodiment, the heat flux sensor and support sensor are located within the second module, while the auxiliary sensors are located in the first module. This configuration is presented as an example and may vary based on specific application needs.

[0115] Figure 2 lists an example of the sensors used in the calorie estimation apparatus as illustrated in Figure 1. The sensors are categorized by their function, including a heat flux sensor, one and / or more auxiliary sensors, and a support sensor. This categorization is illustrative and the exact sensor configuration may differ in other embodiments.

[0116] Figure 3 illustrates an example embodiment of the sensor placement of the first module, used in the calorie estimation apparatus as illustrated in Figure 1. In this embodiment, four auxiliary sensors are located within the first module.

[0117] Figure 4 illustrates an example embodiment of the sensor placement of the second module, used in the calorie estimation apparatus as illustrated in Figure 1. In this embodiment, the heat flux sensor and support sensor are located within the second module.

[0118] Figure 5 provides an example embodiment of the method steps used in the calorie estimation process. The method steps are shown as an example and may be adapted or modified in various implementations.

[0119] Figure 6 depicts an example of the accuracy achieved with one embodiment where the calorie estimation apparatus is configured as a wearable device. In this illustration, approximately 27 data points are plotted, with the x-axis representing actual values in kcal and the y-axis showing predicted values in kcal. The results shown here are illustrative and may vary depending on specific configurations and datasets.

[0120] Figure 7 depicts a sample data graph from one example of the calorie estimation process, illustrating heat flux sensor data captured over a two-hour period following a meal consumed from 9:50 to 10:00. This data sample is provided as an example and may vary based on different sensor configurations and monitoring conditions. Figure 8 provides an example embodiment of the method steps used in the calorie estimation process. The method steps are shown as an example and may be adapted or modified in various implementations.

[0121] Figure 8A provides an example embodiment of the extra method steps used when support sensor data is used in the calorie estimation process. The method steps are shown as an example and may be adapted or modified in various implementations.

[0122] DETAILED DESCRIPTION

[0123] Terminology. Unless stated otherwise, terms used in the Detailed Description have the meanings set forth elsewhere in this specification; in particular, “flow of heat between the human body of the user and the user’s environment” denotes the signed heat transfer rate per unit area between the user’s skin and the main body at the contact site (e.g., W / m2), and “heat flux sensor”, “auxiliary sensor”, and “support sensor” are used as defined in the Summary of the Invention.

[0124] Fig. 1 illustrates an example embodiment of a calorie estimation apparatus 100 being configured to be a wearable device. The calorie estimation apparatus 100 comprises a heat flux sensor 200 and one or more auxiliary sensors (see Table 1 / Fig. 2). In the shown embodiment the calorie estimation apparatus 100 comprises dressing means 140 taking the form of a strap which may be adjusted to fit around the wrist, ankle and / or neck of a user allowing the user to wear the calorie estimation apparatus 100. As shown in Fig. 1 the calorie estimation apparatus 100 may further comprise a display 130 for displaying the estimated calories consumed. Other embodiments of the calorie estimation apparatus 100 may be without a display unit being configured to transmit calorie estimation data to an external unit. Similarly, embodiment having a display unit may also be configured to transmit collected data to an external unit. The calorie estimation apparatus 100 may further comprise a first module 110, containing one or more auxiliary sensors configured to capture data on various physiological and / or environmental factors and / or effects. In certain embodiments, the first module 110 may be positioned on a different part of the user’s body, allowing the calorie estimation apparatus 100 to collect data from multiple locations. Alternative configurations may incorporate auxiliary sensors within the second module and / or in a distributed arrangement, depending on the application needs. The calorie estimation apparatus 100 may further comprise a second module 120, in which the heat flux sensor 200 is located and, in certain embodiments, a support sensor. The second module 120 is positioned in close proximity to the user’s body, allowing it to capture relevant flow of heat data. In other embodiments, the heat flux sensor 200 and / or support sensor may be located in a different module and / or area of the device, depending on the specific configuration and data requirements of the calorie estimation apparatus 100. The calorie estimation apparatus 100 may further comprise a button 150, which can be used to turn the wearable device on or off, and / or initiate a control command for displaying data in a specific way on the display 130 or on an external unit. In certain embodiments, the button 150 may support additional functions, such as toggling between display modes and / or initiating data transmission to an external unit. The functionality of the button 150 may vary based on the configuration of the calorie estimation apparatus 100 and user preferences.

[0125]

[0126] Table 1

[0127] Table 1 above and Fig. 2 lists an example embodiment of the sensor arrangement within the calorie estimation apparatus 100. The configuration includes:

[0128] A heat flux sensor 200 configured to measure the flow of heat between the human body of the user and the user’s environment

[0129] A set of auxiliary sensors configured to capture additional physiological and / or environmental data, including:

[0130] o An ambient temperature sensor 210 configured to measure the ambient temperature of the user’s environment

[0131] o A skin temperature sensor 220 configured to measure the user’s skin temperature

[0132] o A heart rate sensor 230 configured to measure the user’s heart rate and / or pulse o An accelerometer / gyroscope sensor 240 configured to measure the user’s movement and / or orientation.

[0133] A support sensor in the form of an optical sensor 250 configured to measure the dilation of one or more blood veins This configuration is presented as an example, and other embodiments may include different types of auxiliary sensors and support sensors depending on the specific requirements of the calorie estimation apparatus 100.

[0134] In other words, the example embodiments of Table 1 and Fig. 2 may be seen to include:

[0135] An example embodiment of the sensor arrangement within the calorie estimation apparatus 100.

[0136] The configuration includes:

[0137] A heat flux sensor 200, arranged at the contact site and configured to provide a signal indicative of a signed heat transfer rate per unit area between the user’s skin and the main body at the contact site

[0138] One or more auxiliary sensors each sensor configured to provide auxiliary sensor data indicative of at least one of: environmental conditions, user behavior, or user state. Including:

[0139] o An ambient temperature sensor 210 configured to measure the ambient temperature of the user’s environment

[0140] o A skin temperature sensor 220 configured to measure the user’s skin temperature

[0141] o A heart rate sensor 230 configured to measure the user’s heart rate and / or pulse o An accelerometer / gyroscope sensor 240 configured to measure the user’s movement and / or orientation.

[0142] A support sensor in the form of an optical sensor 250 configured to acquire optical signals from tissue of the user

[0143] This configuration is presented as an example, and other embodiments may include different types of auxiliary sensors and support sensors depending on the specific requirements of the calorie estimation apparatus 100.

[0144] Fig. 3 illustrates an example embodiment of the back side of the first module of the calorie estimation apparatus 100. The figure provides an overview of the sensor placement within the first module, including:

[0145] 300 General sensor placement layouts of the first module

[0146] 310 Placement of the ambient temperature sensor 210

[0147] 320 Placement of the skin temperature sensor 220

[0148] 330 Placement of the heart rate sensor 230

[0149] 340 Placement of the accelerometer / gyroscope sensor 240 In some embodiments the heat flux sensor may be arranged away from the auxiliary sensors. In some embodiments the heat flux sensor may be arranged adjacently with respect to one or more auxiliary sensors while one or more other auxiliary sensor may be arranged spaced apart from the heat flux sensor, to optimize their location for the respective effects to be measured.

[0150] Fig. 4 illustrates an example embodiment of the second module of the calorie estimation apparatus 100. The figure provides an overview of the sensor placement within the second module, including:

[0151] 400 General sensor placement layouts of the second module

[0152] 410 Placement of the heat flux sensor 200

[0153] 420 Placement of the support sensor in the form of an optical sensor 250

[0154] In some embodiments the heat flux sensor may be arranged away from the auxiliary sensors. In some embodiments the heat flux sensor may be arranged adjacently with respect to one or more auxiliary sensors while one or more other auxiliary sensor may be arranged spaced apart from the heat flux sensor, to optimize their location for the respective effects to be measured.

[0155] Fig. 5 illustrates an example embodiment of the method steps for estimating calories consumed in the calorie estimation apparatus 100. The steps are as follows:

[0156] • 500 Capturing data on the flow of heat between the human body of a user and the user’s environment

[0157] • 510 Detecting periods of caloric consumption

[0158] • 520 This step indicates that detecting periods of caloric consumption 510 and detecting heat affecting conditions caused by other effects than consumption of calories 530 may occur simultaneously. Alternatively, the method may be configured to operate with only step 510 and / or step 530

[0159] • 530 Detecting heat affecting conditions caused by other effects than consumption of calories

[0160] • 540 Detecting changes in the flow of heat before, during and / or after a period of caloric consumption

[0161] • 550 Estimating calories consumed based on determined changes in the flow of heat This sequence is presented as an example embodiment, and other configurations may allow for variations in the order and / or combination of these steps, depending on the specific requirements of the calorie estimation process. Fig. 6 illustrates an example graph depicting the accuracy achieved with the configuration of the calorie estimation apparatus 100. The graph provides a comparison between actual and predicted calorie values to demonstrate the calorie estimation apparatus’ 100 estimation performance.

[0162] • 600 Accuracy results graph, showing a plot of the calorie estimation accuracy.

[0163] • 610 The x-axis represents the actual values, serving as a proxy for the actual calories consumed. These values are obtained by manually tracking calories prior to a specific data collection, with units in kilocalories (kcal).

[0164] • 620 The y-axis represents the predicted values as calculated by the processing unit based on determined changes in the flow of heat. These predictions are given in kilocalories (kcal).

[0165] • 630 Statistical metrics that quantify the accuracy of the calorie estimation apparatus 100. The following statistics are included:

[0166] o MAE (Mean Absolute Error)

[0167] o MSE (Mean Squared Error)

[0168] o RMSE (Root Mean Squared Error)

[0169] o R2(Coefficient of Determination)

[0170] o Adjusted R2

[0171] o AIC (Akaike Information Criterion)

[0172] o BIC (Bayesian Information Criterion)

[0173] This example graph is intended to illustrate one possible configuration of the calorie estimation apparatus, and other embodiments may achieve different accuracy metrics depending on specific sensor arrangements and data processing methods.

[0174] Fig. 7 illustrates an example data sample from the heat flux sensor 200 of the calorie estimation apparatus 100. The graph demonstrates how data from the heat flux sensor changes in response to a meal and continues to be monitored post-consumption.

[0175] • 700 Data sample from the heat flux sensor

[0176] • 710 A meal of approximately 424 kcal is consumed. The meal is consumed in the time period from 9:50 to 10:00. The data collection continues for two hours following the meal

[0177] This data sample is provided as an example and may vary based on different sensor configurations and monitoring conditions.

[0178] Fig. 8 illustrates an example embodiment of the method steps for estimating calories consumed in the calorie estimation apparatus 100. The steps are as follows:

[0179] • 800 Placing a contact site of a main body against a user’s skin. • 810 Obtaining, from a heat-flux sensor arranged at the contact site, data indicative of a signed heat transfer rate per unit area between the user’s skin and the main body at the contact site.

[0180] • 820 Obtaining auxiliary sensor data indicative of at least one of: environmental conditions, user behavior, or user state.

[0181] • 830 Detecting, based on the auxiliary sensor data, one or more periods of caloric consumption.

[0182] • 840 Steps 830 and 850 may be performed concurrently; alternatively, the method may be configured to operate with only step 830 and / or step 850.

[0183] • 850 Detecting, based on the auxiliary sensor data, heat-affecting conditions unrelated to caloric consumption.

[0184] • 860 In response to detecting a period of caloric consumption, determining changes in the signed heat transfer rate per unit area before, during, and after the detected period of caloric consumption.

[0185] • 870 Estimating calories consumed by the user based on the determined changes in the signed heat transfer rate per unit area.

[0186] The sequence above is presented as one example embodiment; other implementations may vary the order and / or combine steps as appropriate.

[0187] Fig. 8A illustrates an example embodiment of the method steps for estimating calories consumed in the calorie estimation apparatus 100, where support sensor data is used when estimating calories consumed. The extra steps compared to figure 8 are as follows:

[0188] • 855 Obtaining at least one of: (a) a vascular dilation indicator from an optical sensor; or (b) a local circulation indicator from a bioimpedance sensor.

[0189] • 865 Using one or both of the vascular dilation indicator and the local circulation indicator to perform at least one of:

[0190] i) assigning weights to different time portions of the signed heat transfer rate per unit area;

[0191] ii) tuning a person-specific conversion from the signed heat transfer rate per unit area to calories consumed;

[0192] iii) updating model parameters representing local blood flow and heat transfer at the measurement site.

[0193] • 875 Estimating calories consumed by the user based on the determined changes of step 860 and, in implementations practicing step 855, the weighted / tuned / updated outputs produced using the vascular dilation indicator and / or local circulation indicator. The sequence above is presented as one example embodiment; other implementations may vary the order and / or combine steps as appropriate.

[0194] LIST OF REFERENCES

[0195] 100 Calorie estimation apparatus

[0196] 110 A first module of the calorie estimation apparatus

[0197] 120 A second module of the calorie estimation apparatus

[0198] 130 A display of the calorie estimation apparatus

[0199] 140 A strap of the calorie estimation apparatus

[0200] 150 A button of the calorie estimation apparatus

[0201] 200 Heat flux sensor

[0202] 210 Ambient temperature sensor

[0203] 220 Skin temperature sensor

[0204] 230 Heart rate sensor

[0205] 240 Accelerometer / gyroscope sensor

[0206] 250 Optical sensor

[0207] 300 General sensor placement layouts of the first module

[0208] 310 Placement of the ambient temperature sensor 210

[0209] 320 Placement of the skin temperature sensor 220

[0210] 330 Placement of the heart rate sensor 230

[0211] 340 Placement of the accelerometer / gyroscope sensor 240

[0212] 400 General sensor placement layouts of the second module

[0213] 410 Placement of the heat flux sensor 200

[0214] 420 Placement of the support sensor in the form of an optical sensor 250

[0215] 500 Capturing data on the flow of heat between the human body of a user and the user’s environment

[0216] 510 Detecting periods of caloric consumption

[0217] 520 This step indicates that detecting periods of caloric consumption 510 and detecting heat affecting conditions caused by other effects than consumption of calories 530 may occur simultaneously. Alternatively, the method may be configured to operate with only step 510 and / or step 530

[0218] 530 Detecting heat affecting conditions caused by other effects than consumption of calories 540 Detecting changes in the flow of heat before, during and / or after a period of caloric consumption

[0219] 550 Estimating calories consumed based on determined changes in the flow of heat 600 Accuracy results graph, showing a plot of the calorie estimation accuracy.

[0220] 610 The x-axis represents the actual values, serving as a proxy for the actual calories consumed.

[0221] 620 The y-axis represents the predicted values as calculated by the processing unit based on determined changes in the flow of heat.

[0222] 630 Statistical metrics that quantify the accuracy of the calorie estimation apparatus 100.

[0223] 700 Data sample from the heat flux sensor

[0224] 710 A meal of approximately 424 kcal is consumed.

[0225] 800 Placing a contact site of a main body against a user’s skin.

[0226] 810 Obtaining, from a heat-flux sensor arranged at the contact site, data indicative of a signed heat transfer rate per unit area between the user’s skin and the main body at the contact site.

[0227] 820 Obtaining auxiliary sensor data indicative of at least one of: environmental conditions, user behavior, or user state.

[0228] 830 Detecting, based on the auxiliary sensor data, one or more periods of caloric consumption.

[0229] 840 Steps 830 and 850 may be performed concurrently; alternatively, the method may be configured to operate with only step 830 and / or step 850.

[0230] 850 Detecting, based on the auxiliary sensor data, heat-affecting conditions unrelated to caloric consumption.

[0231] 855 Obtaining at least one of: (a) a vascular dilation indicator from an optical sensor; or (b) a local circulation indicator from a bioimpedance sensor.

[0232] 860 In response to detecting a period of caloric consumption, determining changes in the signed heat transfer rate per unit area before, during, and after the detected period of caloric consumption.

[0233] 865 Using one or both of the vascular dilation indicator and the local circulation indicator to perform at least one of:

[0234] i) assigning weights to different time portions of the signed heat transfer rate per unit area; ii) tuning a person-specific conversion from the signed heat transfer rate per unit area to calories consumed;

[0235] iii) updating model parameters representing local blood flow and heat transfer at the measurement site.

[0236] 870 Estimating calories consumed by the user based on the determined changes in the signed heat transfer rate per unit area.

[0237] 875 Estimating calories consumed by the user based on the determined changes of step 860 and, in implementations practicing step 855, the weighted / tuned / updated outputs produced using the vascular dilation indicator and / or local circulation indicator.

Claims

CLAIMS1. A calorie estimation apparatus for automatically tracking a user’s consumed calories, said calorie estimation apparatus comprising:a main body having a contact site configured to be placed against a user’s skin;a heat flux sensor arranged at the contact site and configured to provide a signal indicative of a signed heat transfer rate per unit area between the user’s skin and the main body at the contact site;one or more auxiliary sensors each sensor configured to provide auxiliary sensor data indicative of at least one of: environmental conditions, user behavior, or user state; and a processing unit, the processing unit being configured to:- receive the signed heat transfer rate per unit area and the auxiliary sensor data, and- detect, based on the auxiliary sensor data, one or more periods of caloric consumption and / or heat-affecting conditions unrelated to caloric consumption, and- in response to detecting a period of caloric consumption, determine changes in the signed heat transfer rate per unit area before, during, and after the detected period of caloric consumption, and- estimate calories consumed by the user based on determined changes in the signed heat transfer rate per unit area.

2. The calorie estimation apparatus according to claim 1, comprising a first module and a second module, said first module comprising at least one auxiliary sensor and said second module comprising said heat flux sensor.

3. The calorie estimation apparatus according to claim 1 or 2, wherein the one or more auxiliary sensors are disposed at one or more locations selected from:i) the contact site of the main body, including being co-located with the heat flux sensor; ii) a portion of the main body other than the contact site; andiii) within one or more modules of the calorie estimation apparatus.

4. The calorie estimation apparatus according to any of the preceding claims, at least one of the one or more auxiliary sensors being selected from a group consisting of an ambient temperature sensor, a skin temperature sensor, a heart rate sensor, an accelerometer, and a gyroscope.

5. The calorie estimation apparatus according to any of the preceding claims, further comprising one or more support sensors configured to acquire support-sensor data from the user, wherein the processing unit is further configured to receive the support-sensor data and, when estimating calories consumed, to combine the support-sensor data with one or both of: i) a signal from the heat flux sensor indicative of a signed heat transfer rate per unit area between the user’s skin and the main body at the contact site;ii) the determined changes in the signed heat transfer rate per unit area.

6. The calorie estimation apparatus according to any of the preceding claims, wherein the processing unit is configured to:i) receive the support sensor data and the signed heat transfer rate per unit area; ii) compute, from at least a portion of the received support sensor data, one or more derived quantities; andiii) to estimate calories consumed using the determined changes in the signed heat transfer rate per unit area together with selected derived quantities.

7. The calorie estimation apparatus according to any of the preceding claims, wherein the one or more support sensors are disposed at one or more locations selected from:i) the contact site of the main body, including being co-located with the heat flux sensor; ii) a portion of the main body other than the contact site; andiii) within one or more modules of the calorie estimation apparatus.

8. The calorie estimation apparatus according to any of the claims 5-7, wherein the one or more support sensors is an optical sensor configured to acquire optical signals from tissue of the user, and wherein the processing unit is configured to generate, from the optical signals, a vascular dilation indicator that varies over time with one or both of i) blood vessel caliber and ii) local blood content.

9. The calorie estimation apparatus according to any of the claims 5-7, wherein the one or more support sensors is a bioimpedance sensor configured to acquire electrical signals from tissue of the user, and wherein the processing unit is configured to generate, from the electrical signals, a local circulation indicator that varies over time with one or both of i) blood volume, and ii) blood flow.

10. The calorie estimation apparatus according to any of the claims 8-9, wherein the processing unit is configured to use one or both of the vascular dilation indicator and the local circulation indicator to perform at least one of:i) assigning weights to respective time portions of the signed heat transfer rate per unit area; ii) tuning a person-specific conversion from the signed heat transfer rate per unit area to calories consumed;iii) updating model parameters representing local blood flow and heat transfer at the measurement site.

11. The calorie estimation apparatus according to any of the preceding claims, wherein the heat flux sensor is implemented using at least one of:i) a passive gradient arrangement configured to sense a temperature difference across a known thermal path and to provide a signal indicative of the signed heat transfer rate per unit area; ii) an active isothermal arrangement configured to maintain a controlled interface temperature and to provide a signal indicative of the signed heat transfer rate per unit area based on control power;iii) one or more thermoelectric Seebeck-effect transducers selected from the group consisting of thermocouples and thermopiles, and configured to provide a signal indicative of the signed heat transfer rate per unit area;iv) a calorimetric power-balance assembly configured to provide a signal indicative of the signed heat transfer rate per unit area based on power required to hold a defined thermal condition, normalized by a known or calibrated effective area;v) a thin-film heat flux sensor, a microelectromechanical systems (MEMS) heat flux sensor, or a thin-film MEMS heat flux sensor integrated into a wearable assembly and configured to provide a signal indicative of the signed heat transfer rate per unit area;vi) a multi-sensor arrangement including two or more temperature sensors, wherein the processing unit executes a thermal model with known or calibrated parameters to compute the signed heat transfer rate per unit area; wherein any two or more of i)-vi) may be used in combination.

12. The calorie estimation apparatus according to claim 1, said calorie estimation apparatus being configured to be a wearable device.

13. The calorie estimation apparatus according to claim 12, wherein the wearable device comprises a retention structure comprising an adjustable strap for securing the device to the wrist of the user or around another suitable body part of the user.

14. A method for automatically tracking a user’s calories consumed, said method comprising the steps of:placing a contact site of a main body against a user’s skin;obtaining, from a heat flux sensor arranged at the contact site, data indicative of a signed heat transfer rate per unit area between the user’s skin and the main body at the contact site;obtaining auxiliary sensor data indicative of at least one of: environmental conditions, user behavior, or user state;detecting, based on the auxiliary sensor data, one or more periods of caloric consumption, and / or heat-affecting conditions unrelated to caloric consumption; in response to detecting a period of caloric consumption, determining changes in the signed heat transfer rate per unit area before, during, and after the detected period of caloric consumption; andestimating calories consumed by the user based on the determined changes in the signed heat transfer rate per unit area.

15. The method of claim 14, further comprising obtaining at least one of: (a) a vascular dilation indicator from an optical sensor; or (b) a local circulation indicator from a bioimpedance sensor; and using one or both of the vascular dilation indicator and the local circulation indicator to perform at least one of:i) assigning weights to different time portions of the signed heat transfer rate per unit area; ii) tuning a person-specific conversion from the signed heat transfer rate per unit area to calories consumed;iii) updating model parameters representing local blood flow and heat transfer at the measurement site.

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