A method of assessing the risk of cold exposure to the hands of rescue personnel
Patent Information
- Application Number
- CN202611165596.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-03
- Publication Date
- 2026-10-27
Smart Images
Figure CN122991608A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of human protective technology, and in particular to a method for assessing the risk of cold exposure of rescue personnel's hands. Background Technology
[0002] In cold-weather work environments, the hands, as the extremities of the human body, are prone to cold injuries due to their large surface area to volume ratio and the susceptibility of blood perfusion to cold. Cold-induced vasodilation (CIVD) is considered a protective response that prevents excessive cooling and frostbite of local tissues by intermittently increasing blood perfusion. Therefore, accurately assessing the risk of cold exposure to the hands and identifying high-risk individuals and high-risk areas of the hands is crucial for preventing cold injuries to the hands.
[0003] Currently, the assessment methods for hand cold exposure risk are mainly based on environmental parameters (such as air temperature, wind speed, and humidity) and empirical models, such as the wind chill index, which describes the cooling effect of air on the skin. This index comprehensively considers the combined effects of air temperature and wind speed, and can more accurately reflect the actual degree of cold felt by the human body in an outdoor environment, making it particularly suitable for cold exposure assessment in outdoor scenarios. Wind chill temperature can be obtained directly from the corresponding table in the EN 11079 standard, or it can be calculated based on wind speed and air temperature parameters, and then the corresponding risk level can be determined according to the wind chill index.
[0004] However, existing assessment methods cannot track the dynamic regulation of heat production and blood flow redistribution caused by changes in activity intensity, making it difficult to effectively assess the evolution of physiological cumulative effects under prolonged cold exposure time, thus reducing the accuracy of hand cold exposure risk assessment. Summary of the Invention
[0005] Therefore, it is necessary to provide a method for assessing the risk of cold exposure of rescuers' hands in response to the above-mentioned technical problems.
[0006] This invention provides a method for assessing the risk of cold exposure to the hands of rescue personnel, comprising: We obtained core body temperature data, weighted average body surface temperature data, and local skin temperature data of different areas of the hands from multiple rescuers in cold exposure environments. The overall cold stress level of each rescuer is assessed based on core body temperature data and weighted average body surface temperature data. When the overall cold stress level indicates that the core body temperature is within the preset normal range and the weighted average body surface temperature is below the preset cold stress threshold, the hand is determined to be in a state prone to cold-induced vasodilation. The core characteristic parameters of each cold-induced vasodilation event are extracted from the local skin temperature data of different areas of the hand. The core characteristic parameters include at least: trigger time, single fluctuation amplitude, fluctuation frequency, and steady-state average skin temperature. Based on the core characteristic parameters of all cold-induced vasodilation events, a cold-induced vasodilation index was constructed for different hand regions of each rescuer. A dual risk assessment was conducted based on the cold-induced vasodilation index of different hand areas of different rescuers to classify the cold exposure risk of different rescuers in the same hand area and to identify high-risk areas in different hand areas of the same rescuer. The risk assessment results were obtained, and hand protective equipment for each rescuer was selected based on the risk assessment results.
[0007] Optionally, the measurement sites for the weighted average body surface temperature data include: forehead, chest, forearm, back of hand, thigh, calf, and foot; the temperature data from all measurement sites are weighted to obtain the weighted average body surface temperature data.
[0008] Optionally, the measurement sites for local skin temperature data in different areas of the hand include: the tip of the thumb, the tip of the index finger, the tip of the middle finger, the tip of the ring finger, the tip of the little finger, the palm, and the back of the hand.
[0009] Optionally, characteristic parameters for each cold-induced vasodilation event are extracted from local skin temperature data of different areas of the hand, specifically including: In the time series of local skin temperature data of the hand, periodic temperature fluctuations of the hand after the temperature drops were detected; The starting point of the trough of the temperature fluctuation within each cycle is taken as the beginning of a cold-induced vasodilation event, the temperature at that point is taken as the starting temperature, and the time from the start of cold exposure to the starting point is taken as the trigger time of cold-induced vasodilation; the temperature value from the trough to the peak is taken as the peak temperature, the difference between the time point corresponding to the peak temperature and the trigger time is taken as the peak time, and the duration of a cold-induced vasodilation event is recorded as the time from the start of the trigger time to the temperature falling back to the trough level; In a single cold-induced vasodilation event, the difference between the peak temperature and the initial temperature was taken as the single fluctuation amplitude, the number of times the peak temperature occurred during the cold exposure phase was taken as the fluctuation frequency, the area enclosed by the temperature time series curve and the baseline was taken as the area under the curve, and the ratio of the average skin temperature of the hand during the cold exposure period to the average skin temperature of the hand in the previous period was taken as the steady-state average skin temperature.
[0010] Optionally, a cold-induced vasodilation index for different hand regions of each rescuer is constructed based on characteristic parameters of all cold-induced vasodilation events, specifically including: Feature extraction is performed on the characteristic parameters of cold-induced vasodilation events in the same or multiple regions to screen key features reflecting the intensity of the cold-induced vasodilation response and obtain core feature parameters; the core feature parameters include at least: trigger time, fluctuation amplitude, fluctuation frequency, and steady-state average skin temperature; Each core feature parameter is standardized to obtain standardized parameters, and a standardized parameter matrix is constructed based on the standardized parameters. Principal component analysis was performed on the standardized parameter matrix to extract comprehensive indicators characterizing the cold-induced vasodilation ability of the hand, and the first principal components of different hand regions were obtained. The score of the first principal component of each hand region is used as the cold-induced vasodilation index for that hand region based on the following formula: ; ; ; in, , The score coefficient of the first principal component is . To standardize parameters, For the first j The loadings of the core feature parameters on the first principal component The eigenvalues of the first principal component are... For the first i The first hand area j The original values of the core feature parameters, The first among all rescuers j The mean of each core feature parameter, The first among all rescuers j The standard deviation of each core feature parameter; Among them, the cold-induced vasodilation index is positively correlated with the strength of the cold-induced vasodilation response in the hands and negatively correlated with the risk level of cold exposure to the hands.
[0011] Optionally, a dual risk assessment can be conducted based on the cold-induced vasodilation index of different hand areas among different rescuers to classify the cold exposure risk of the same hand area among different rescuers and to identify high-risk areas in different hand areas of the same rescuer. Specifically, this includes: Dual risk assessment, including: horizontal assessment and vertical assessment; The cross-sectional assessment includes comparing the cold-induced vasodilation index (CVI) of different rescuers in the same hand area with preset risk level thresholds. When the CVI of the hand area is greater than the first risk level threshold, the hand area is determined to be low-risk; when the CVI of the hand area is not greater than the first risk level threshold and not less than the second risk level threshold, the hand area is determined to be medium-risk; and when the CVI of the hand area is less than the second risk level threshold, the hand area is determined to be high-risk. Longitudinal assessment includes comparing the cold-induced vasodilation index of different areas of the same rescuer's hand, and identifying the area with the lowest cold-induced vasodilation index as a high-risk area.
[0012] The method for assessing the risk of cold exposure of rescuers' hands provided in this embodiment of the invention has the following advantages compared with the prior art: This invention extracts characteristic parameters of each vasodilatory event by analyzing skin temperature fluctuations in rescuers under cold exposure conditions. It captures the dynamic evolution of cold-induced vasodilation in real time and uses this dynamic evolution to perform risk localization in two dimensions: horizontally, it categorizes and screens high-risk rescuers with weak vasodilatory responses and poor cold tolerance; vertically, it precisely identifies and pinpoints the localized vulnerable points of the same rescuer. This technique directly maps cold exposure risk to the actual physiological defense capabilities of each rescuer's hand area, optimizing cold injury prevention from a lagging environmental warning to a physiological warning based on cold-induced vasodilation events in the hand, significantly improving the accuracy of hand cold exposure risk assessment. Attached Figure Description
[0013] Figure 1 This is a flowchart illustrating a method for assessing the risk of cold exposure of rescuers' hands, provided in one embodiment. Figure 2 A flowchart of CIVD feature parameter extraction for a method for assessing the risk of cold exposure of rescuers' hands provided in one embodiment; Figure 3 A schematic diagram of CIVD characteristic parameters for a method for assessing the risk of cold exposure of rescuers' hands provided in one embodiment; Figure 4 A schematic diagram of PCA scores for a method for assessing the risk of cold exposure of rescuers' hands provided in one embodiment; Figure 5 This is a longitudinal risk assessment diagram illustrating a method for assessing the risk of cold exposure of rescue workers' hands, provided in one embodiment. Figure 6 This is a schematic diagram illustrating the lateral risk assessment of a method for assessing the risk of cold exposure of rescuers' hands, provided in one embodiment. Detailed Implementation
[0014] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0015] This invention provides a method for assessing the risk of cold exposure to the hands of rescue personnel, the method comprising: We obtained core body temperature data, weighted average body surface temperature data, and local skin temperature data of different areas of the hands from multiple rescuers in cold exposure environments. The overall cold stress level of each rescuer is assessed based on core body temperature data and weighted average body surface temperature data. When the overall cold stress level indicates that the core body temperature is within the preset normal range and the weighted average body surface temperature is below the preset cold stress threshold, the hand is determined to be in a state prone to cold-induced vasodilation. The core characteristic parameters of each cold-induced vasodilation event are extracted from the local skin temperature data of different areas of the hand. The core characteristic parameters include at least: trigger time, single fluctuation amplitude, fluctuation frequency, and steady-state average skin temperature. Based on the core characteristic parameters of all cold-induced vasodilation events, a cold-induced vasodilation index was constructed for different hand regions of each rescuer. A dual risk assessment was conducted based on the cold-induced vasodilation index of different hand areas of different rescuers to classify the cold exposure risk of different rescuers in the same hand area and to identify high-risk areas in different hand areas of the same rescuer. The risk assessment results were obtained, and hand protective equipment for each rescuer was selected based on the risk assessment results.
[0016] Preferably, the measurement sites for weighted average body surface temperature data include: forehead, chest, forearm, back of hand, thigh, calf, and foot. The temperature data from all measurement sites are weighted to obtain the weighted average body surface temperature data. The measurement sites for local skin temperature data in different areas of the hand include: the tip of the thumb, index finger, middle finger, ring finger, little finger, palm, and back of hand.
[0017] Preferably, characteristic parameters for each cold-induced vasodilation event are extracted from local skin temperature data of different areas of the hand, specifically including: In the time series of local skin temperature data of the hand, periodic temperature fluctuations of the hand after the temperature drops were detected.
[0018] The trough of the temperature fluctuation within each cycle is taken as the start of a cold-induced vasodilation event, and the temperature at that point is taken as the initial temperature. The time from the start of cold exposure to the initial point is taken as the trigger time for cold-induced vasodilation. The temperature value from the trough to the peak is taken as the peak temperature, and the difference between the time point corresponding to the peak temperature and the trigger time is taken as the peak time. The duration of a cold-induced vasodilation event is recorded as the time from the trigger time to the temperature returning to the trough level.
[0019] In a single cold-induced vasodilation event, the difference between the peak temperature and the initial temperature was taken as the single fluctuation amplitude, the number of times the peak temperature occurred during the cold exposure phase was taken as the fluctuation frequency, the area enclosed by the temperature time series curve and the baseline was taken as the area under the curve, and the ratio of the average skin temperature of the hand during the cold exposure period to the average skin temperature of the hand in the previous period was taken as the steady-state average skin temperature.
[0020] Preferably, when the hand is in a condition prone to cold-induced vasodilation, characteristic parameters of each cold-induced vasodilation event in each area of the hand are extracted from the local skin temperature data of the hand. Specifically, this includes detecting periodic temperature fluctuations that occur after the temperature drops in the time series of local skin temperature data of the hand.
[0021] The starting point of the temperature fluctuation trough is taken as the beginning of a cold-induced vasodilation event, and the temperature at this point is recorded as the starting temperature. The time from the start of cold exposure to the starting point is recorded as the trigger time of cold-induced vasodilation. The temperature value from the trough to the peak is recorded as the peak temperature. The difference between the time point corresponding to the peak temperature and the trigger time is recorded as the peak time. The duration of a cold-induced vasodilation event is recorded as the time from the start of the trigger time to the temperature falling back to the trough level.
[0022] In a cold-induced vasodilation event, the difference between the peak temperature and the initial temperature is taken as the single fluctuation amplitude, the number of times the peak temperature occurs during the cold exposure phase is taken as the fluctuation frequency, the area enclosed by the temperature time series curve and the baseline is taken as the area under the curve, and the ratio of the average skin temperature of the hand during the cold exposure period to the average skin temperature of the hand during the previous preset period is taken as the steady-state average skin temperature.
[0023] Preferably, a cold-induced vasodilation index for different hand regions of each rescuer is constructed based on characteristic parameters of all cold-induced vasodilation events, specifically including: Feature extraction is performed on characteristic parameters of cold-induced vasodilation events in the same or multiple regions to screen key features reflecting the intensity of the cold-induced vasodilation response, thus obtaining core feature parameters. Core feature parameters include at least: trigger time, fluctuation amplitude, fluctuation frequency, and steady-state mean skin temperature.
[0024] Each core feature parameter is standardized to obtain standardized parameters, and a standardized parameter matrix is constructed based on the standardized parameters.
[0025] Principal component analysis was performed on the standardized parameter matrix to extract a comprehensive index characterizing the cold-induced vasodilation capacity of the hand. The first principal component of different hand regions was obtained, and the score of the first principal component of each hand region was used as the cold-induced vasodilation index of that hand region.
[0026] A specific embodiment of a method for assessing the risk of cold exposure of rescuers' hands is provided, such as... Figure 1 As shown, it includes: Step 101: Obtain core body temperature data, weighted average body surface temperature data, and local skin temperature data of the hands of the rescue personnel during the mission.
[0027] Specifically, when rescue personnel perform typical tasks such as patrolling, equipment maintenance, and material handling, their bodies are exposed to continuous or intermittent cold environments. Core body temperature data, weighted average body surface temperature data, and local skin temperature data of the hands dynamically change with ambient temperature, activity intensity, and exposure time. Core body temperature reflects the body's overall thermal balance, weighted average body surface temperature reflects the level of vasoconstriction and vasodilation of peripheral blood vessels, and local skin temperature of the hands is a direct physiological indicator for assessing cold stress and cold-induced vasodilation (CIVD) in the hands. By simultaneously acquiring these three types of temperature data, the whole-body and local cold stress response process of rescue personnel in real-world mission scenarios can be comprehensively captured, providing basic data support for subsequent identification of CIVD susceptibility conditions and extraction of CIVD characteristic parameters from different areas of the hands.
[0028] Step 102: Based on core body temperature data and weighted average surface temperature data, assess the rescuer's overall cold stress level and determine whether the hand is in a predisposing condition for cold-induced vasodilation (CIVD). When determining whether the rescuer is in a predisposing condition for CIVD in the hand based on their overall cold stress level, extract characteristic parameters for each CIVD event in each area of the hand from the acquired local skin temperature data.
[0029] Specifically, core body temperature data and weighted average body surface temperature data together reflect the overall cold stress state of rescuers. When the core body temperature is within the preset normal fluctuation range (36.5℃~37.5℃), while the weighted average body surface temperature remains below the cold stress threshold of 28℃, it indicates that the body has entered a stage of strong peripheral vasoconstriction but has not yet experienced severe hypothermia. This stage is the prerequisite for the most easily induced CIVD phenomenon in the hands.
[0030] The weighted average body surface temperature is calculated according to formula (1): (1) in, T sk It is the weighted average temperature of the whole body. T forehead , T Chest , T arm , T hand , T thigh , T calf , T foot These are the skin temperatures of the forehead, chest, forearm, back of hand, thigh, calf, and foot, respectively, in °C.
[0031] Judging CIVD solely based on a drop in localized skin temperature in the hands can easily lead to misdiagnosis of simple vasoconstriction causing a drop in temperature as a CIVD event. Conversely, if core body temperature has already dropped significantly, the body will prioritize blood supply to core organs, and the CIVD response in the hands will be suppressed. Therefore, only when both core body temperature are normal and the weighted average body surface temperature is below a threshold can the predisposing conditions for CIVD in the hands be considered.
[0032] like Figure 2 The diagram illustrates the specific process of the automatic extraction algorithm, including steps such as temperature data preprocessing, trough and peak detection, event segmentation, and parameter calculation. This ensures the objectivity, repeatability, and efficiency of the extraction process, providing a quantitative basis for the subsequent construction of the cold-induced vasodilation index.
[0033] To avoid high-frequency noise in the raw temperature signal interfering with the accurate identification of CIVD events, the collected local skin temperature data of the hand was first preprocessed. Specifically, a second-order Butterworth low-pass filter was used for filtering, with a sampling frequency of 1 Hz and a cutoff frequency of 0.015 Hz.
[0034] After preprocessing, each CIVD event is automatically identified through the core detection function. The specific detection logic is as follows: ①Trough Detection: Traverse the temperature sequence to find local minima (satisfying that the current temperature is less than or equal to the previous and next points), and use these as the starting point (trigger point) of the CIVD event, recording the trough temperature. and trigger time ; ② Peak detection: Search from the trough to the right until the temperature drops more than 0.3℃ from the current maximum value or the sequence ends, recording the highest temperature during this process. and corresponding time And calculate the amplitude of a single fluctuation. and peak time ; ③ Validity screening: Only when the following conditions are met or The event is considered a valid CIVD event only if it occurs; otherwise, it is skipped. ④ Detection of the end of the descent phase: Continue scanning from the peak to find the point where the temperature first drops to the end of the descent phase. or close to The point is taken as the end point of this diastolic-constrictive cycle, and the cycle duration is calculated. ; ⑤ Skip the current cycle: Move the scan index to after the end of the descending segment to avoid repeated detection and continue searching for the next trough.
[0035] For each hand region, after detecting all CIVD events, the overall parameters are further calculated: total number of CIVD events and average fluctuation amplitude. Average peak time Average period duration Steady-state mean skin temperature (average temperature from the start of 10 minutes after the start of cold exposure to the end) and area under the curve (the area of the trapezoidal integral of the temperature-time curve with 0°C as the baseline from the start of cold exposure to the end). Finally, generate a curve for each hand channel as shown below. Figure 3 The CIVD analysis diagram shown below. Figure 3 It includes the original temperature curve, troughs (blue dots), peaks (red dots), and vertical dashed lines. Horizontal solid arrow indicates A horizontal long dashed line represents The blue markers represent the initial temperature and the corresponding time points are the trigger times. The red markers represent the peak temperature. Δt is the peak time, ΔD is the duration, ΔT is the amplitude of a single fluctuation, S is the area under the curve, and T is the peak temperature. mean The steady-state average skin temperature.
[0036] The automated feature extraction process described above ensures the objectivity, repeatability, and efficiency of the results, providing a quantitative basis for the subsequent construction of the cold-induced vasodilation index. All analysis results, including graphs and specific parameters for each event, as well as overall parameters, are output as CSV files for use in the subsequent construction of the cold-induced vasodilation index.
[0037] In addition, this embodiment also performed batch calculations of the area under the curve and steady-state average skin temperature for different protective conditions (bare hand / gloved) and multiple parts (thumb, index finger, middle finger, ring finger, little finger, palm, back of hand) to compare and analyze the impact of different protective measures on the CIVD response of the hand, and also to provide a quantitative basis for the subsequent construction of the cold-induced vasodilation index.
[0038] Step 103: Based on the characteristic parameters of CIVD events in various areas of the rescuers' hands, construct a cold-induced vasodilation index for the hands. By measuring the value of the cold-induced vasodilation index, conduct a horizontal and vertical assessment of the risk of cold exposure to the hands.
[0039] Specifically, the extracted CIVD event characteristic parameters for each region of the hand include trigger time, peak time, initial temperature, peak temperature, duration, single fluctuation amplitude, fluctuation frequency, area under the curve, and steady-state average skin temperature. These parameters have different dimensions and value ranges, making direct comparison impossible. Therefore, core parameters are first selected from the above characteristic parameters, such as trigger time, single fluctuation amplitude, fluctuation frequency, and steady-state average skin temperature. Each core parameter is then standardized to eliminate the influence of dimensions and obtain standardized parameters. The standardization process uses equation (2):
[0040] (2) in, For the first i The first hand area j The original values of the core feature parameters, and They were the first among all rescuers j The mean and standard deviation of the core feature parameters, For standardized parameters; Principal component analysis is performed on the standardized feature parameter matrix. Based on the correlation matrix, eigenvalues and eigenvectors are solved to extract the first principal component. In this embodiment, the variance contribution rate of the first principal component is 45.4%.
[0041] The score of the first principal component was used as the cold-induced vasodilation index. The calculation formula is as follows: (3) in, The score coefficient of the first principal component is . , For the first j The loadings of the core feature parameters on the first principal component The eigenvalues are the eigenvalues of the first principal component. In this embodiment, the scores of each region of the hand are as follows: Figure 4 As shown, the cold-induced vasodilation index is positively correlated with the strength of the cold-induced vasodilation response in the hands and negatively correlated with the risk level of cold exposure to the hands.
[0042] I CIVDA higher index score indicates a stronger CIVD response and a lower risk of frostbite. Based on this, a dual assessment is conducted: In the longitudinal assessment, for the same rescuer, the cold-induced vasodilation index values of different areas of the hand (such as the tip of the thumb, the tip of the index finger, and the back of the hand) are compared. This identifies the little finger as the high-risk area for cold injury to the hands of most rescuers. Figure 5 As shown.
[0043] In cross-sectional assessments, the cold-induced vasodilation index (CVI) values of the same area of the hands are compared among different rescuers. Risk levels are then categorized based on the CVI values to identify individuals at high risk of cold injury, providing a basis for tiered protection. For example... Figure 6 As shown, the risk of cold injury to the little finger was compared among all subjects, revealing that subject 2 had the lowest risk and subject 10 had the highest. This combined cross-sectional and longitudinal assessment system enabled a refined quantification of hand cold exposure risk from a group to an individual level.
[0044] In this embodiment, firstly, core body temperature data, weighted average body surface temperature data, and local skin temperature data of the hands are acquired during the rescue personnel's mission. These three types of data can comprehensively reflect the rescue personnel's overall thermal balance and local cold stress response characteristics of the hands in a real cold environment. Based on this, core body temperature and weighted average body surface temperature are used to determine whether the hands have entered the conditions prone to cold-induced vasodilation (CIVD), avoiding the one-sidedness of assessment based solely on local skin temperature or environmental parameters.
[0045] When the conditions for occurrence are met, characteristic parameters of each CIVD event are extracted from the time series of local skin temperature in various areas of the hand. A dimensionless cold-induced vasodilation index is constructed based on the extracted CIVD characteristic parameters. Combined with the value of this index, the risk of cold exposure to the hand can be assessed both horizontally and longitudinally.
[0046] The assessment involves horizontal comparison of index values for the same area of the hand among different individuals, while the longitudinal assessment compares index values for different areas of the hand of the same rescuer. This method achieves a dual assessment, from group risk grading to identification of high-risk areas for individuals, providing a systematic and objective technical means for proactive prevention and individualized protection against cold injuries to the hands of rescuers.
[0047] In one embodiment, it is assumed that rescuers perform a continuous 60-minute outdoor mission in an environment of -20°C and 3 m / s wind speed, including typical actions such as hiking, carrying equipment, and manually immobilizing the wounded. Three types of temperature data are collected in real time synchronously using a core body temperature sensor, surface temperature sensors at seven body parts, and skin temperature sensors at seven areas of the hand. In the first 10 minutes of the mission, the core body temperature is maintained between 37.0°C and 37.2°C, while the weighted average surface temperature drops to 27.5°C, at which point the system determines that conditions conducive to CIVD (cold-induced vasodilation) have entered the hand region. Taking the index fingertip as an example, the first CIVD event is detected at the 12-minute mark: initial temperature 9.2°C, peak temperature 12.8°C, and single fluctuation amplitude 3.6°C. Similar characteristic parameters are extracted from other areas. The CIVD characteristic parameters are standardized and weighted summed to calculate the cold-induced vasodilation index for each area.
[0048] Horizontal assessment: The rescuer's index fingertip index is 0.62, compared with 0.85 and 0.13 of the other two personnel on the same mission. According to the risk level thresholds (>0.75 (first risk level threshold), low risk; 0.25-0.75, medium risk; <0.25 (second risk level threshold), high risk), this person is judged to be of medium risk, and those with an index of 0.13 are of high risk and need to be given priority in keeping warm.
[0049] Longitudinal assessment: The indices for different areas of the individual's hand were as follows: thumb 0.71, index finger 0.65, middle finger 0.62, ring finger 0.55, little finger 0.48, palm 0.82, and back of hand 0.68. The little fingertip showed the lowest index (0.48), indicating a high-risk area. It is recommended to enhance insulation of the little finger area within protective gloves. This embodiment verifies that the method can achieve inter-individual risk stratification and intra-individual high-risk area identification.
[0050] It can be seen that the present invention can achieve the following functions: (1) Automatic extraction of characteristic parameters of CIVD in the hand: Using temperature time series analysis and periodic fluctuation detection algorithms, the automatic identification and accurate extraction of characteristic parameters of cold-induced vasodilation (CIVD) events in various areas of the hand can be achieved. By detecting the periodic troughs and peaks that appear after the temperature drops, the starting point of each CIVD event can be accurately marked, and key parameters such as trigger time, starting temperature, peak temperature, peak time, duration, single fluctuation amplitude, fluctuation frequency, area under the temperature curve, and steady-state average skin temperature can be automatically calculated. Through this fully automatic and high-precision feature extraction technology, researchers can obtain quantitative indicators of CIVD response in various areas of the hand without manual intervention, providing an objective and repeatable data basis for subsequent risk assessment.
[0051] (2) Hand frostbite risk assessment function: Based on automatically extracted multi-dimensional feature parameters of CIVD, a dimensionless cold-induced vasodilation index is constructed to achieve a quantitative assessment of the risk of cold injury to the hands of rescuers. This index is obtained by standardizing and weighting the selected core feature parameters (such as trigger time, fluctuation amplitude, fluctuation frequency, steady-state average skin temperature, etc.). The higher the value, the stronger the CIVD response, the better the cold resistance of the hands, and the lower the risk of frostbite.
[0052] Based on this, the system provides two modes: horizontal assessment and vertical assessment. Through this dual assessment function, researchers can scientifically guide the optimization of graded protection and individualized protective equipment, significantly improving the proactive prevention capabilities of rescuers for frostbite on their hands.
[0053] The above-described embodiments are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.
Claims
1. A method for assessing the risk of cold exposure of rescuers' hands, characterized in that, include: We obtained core body temperature data, weighted average body surface temperature data, and local skin temperature data of different areas of the hands from multiple rescuers in cold exposure environments. The overall cold stress level of each rescuer is assessed based on the core body temperature data and the weighted average body surface temperature data. When the overall cold stress level indicates that the core body temperature is within a preset normal range and the weighted average body surface temperature is below a preset cold stress threshold, the hands are determined to be in a state prone to cold-induced vasodilation, and core characteristic parameters of each cold-induced vasodilation event are extracted from the local skin temperature data of different areas of the hands. The core characteristic parameters include at least: trigger time, single fluctuation amplitude, fluctuation frequency, and steady-state average skin temperature; Based on the core characteristic parameters of all cold-induced vasodilation events, a cold-induced vasodilation index was constructed for different hand regions of each rescuer. A dual risk assessment was conducted based on the cold-induced vasodilation index of different hand areas of different rescuers to classify the cold exposure risk of different rescuers in the same hand area and to identify high-risk areas in different hand areas of the same rescuer. The risk assessment results were obtained, and hand protective equipment for each rescuer was selected based on the risk assessment results.
2. The method for assessing the risk of cold exposure of rescuers' hands as described in claim 1, characterized in that, The measurement sites for the weighted average body surface temperature data include: forehead, chest, forearm, back of hand, thigh, calf, and foot; the temperature data from all measurement sites are weighted to obtain the weighted average body surface temperature data.
3. The method for assessing the risk of cold exposure of rescuers' hands as described in claim 1, characterized in that, The measurement sites for local skin temperature data in different areas of the hand include: the tip of the thumb, the tip of the index finger, the tip of the middle finger, the tip of the ring finger, the tip of the little finger, the palm, and the back of the hand.
4. The method for assessing the risk of cold exposure of rescuers' hands as described in claim 1, characterized in that, The extraction of characteristic parameters for each cold-induced vasodilation event from local skin temperature data of different areas of the hand specifically includes: In the time series of the local skin temperature data of the hand, periodic temperature fluctuations of the hand after the temperature drops were detected; The starting point of the trough of the temperature fluctuation within each cycle is taken as the beginning of a cold-induced vasodilation event, the temperature at that point is taken as the starting temperature, and the time from the start of cold exposure to the starting point is taken as the trigger time of cold-induced vasodilation; the temperature value from the trough to the peak is taken as the peak temperature, the difference between the time point corresponding to the peak temperature and the trigger time is taken as the peak time, and the duration of a cold-induced vasodilation event is recorded as the time from the start of the trigger time to the temperature falling back to the trough level; In a single cold-induced vasodilation event, the difference between the peak temperature and the initial temperature is taken as the single fluctuation amplitude, the number of times the peak temperature occurs during the cold exposure phase is taken as the fluctuation frequency, the area enclosed by the temperature time series curve and the baseline is taken as the area under the curve, and the ratio of the average skin temperature of the hand during the cold exposure period to the average skin temperature of the hand in the previous period is taken as the steady-state average skin temperature.
5. The method for assessing the risk of cold exposure of rescuers' hands as described in claim 1, characterized in that, The method of constructing cold-induced vasodilation indices for different hand regions of each rescuer based on characteristic parameters of all cold-induced vasodilation events specifically includes: Feature extraction is performed on the characteristic parameters of cold-induced vasodilation events in the same or multiple regions to screen key features reflecting the intensity of the cold-induced vasodilation response, and core feature parameters are obtained; the core feature parameters include at least: trigger time, fluctuation amplitude, fluctuation frequency, and steady-state average skin temperature; Each of the core feature parameters is standardized to obtain standardized parameters, and a standardized parameter matrix is constructed based on the standardized parameters. Principal component analysis was performed on the standardized parameter matrix to extract a comprehensive index characterizing the cold-induced vasodilation ability of the hand, and the first principal component of different hand regions was obtained. The score of the first principal component of each hand region is used as the cold-induced vasodilation index for that hand region based on the following formula: ； ； ； in, , The score coefficient of the first principal component is . To standardize parameters, For the first j The loadings of the core feature parameters on the first principal component The eigenvalues of the first principal component are... For the first i The first hand area j The original values of the core feature parameters, The first among all rescuers j The mean of each core feature parameter, The first among all rescuers j The standard deviation of each core feature parameter; The cold-induced vasodilation index is positively correlated with the strength of the cold-induced vasodilation response in the hand and negatively correlated with the risk of cold exposure to the hand.
6. The method for assessing the risk of cold exposure of rescuers' hands as described in claim 5, characterized in that, The dual risk assessment, based on the cold-induced vasodilation index of different hand areas of different rescuers, aims to classify the cold exposure risk of different rescuers in the same hand area and identify high-risk areas in different hand areas of the same rescuer. Specifically, this includes: The dual risk assessment includes: horizontal assessment and vertical assessment; The lateral assessment includes: comparing the cold-induced vasodilation index of different rescuers in the same hand area with preset risk level thresholds; when the cold-induced vasodilation index of the hand area is greater than the first risk level threshold, the hand area is determined to be at low risk; when the cold-induced vasodilation index of the hand area is not greater than the first risk level threshold and not less than the second risk level threshold, the hand area is determined to be at medium risk; when the cold-induced vasodilation index of the hand area is less than the second risk level threshold, the hand area is determined to be at high risk. The longitudinal assessment includes comparing the cold-induced vasodilation index of different areas of the same rescuer's hand and identifying the area with the lowest cold-induced vasodilation index as a high-risk area.