Respiratory syncytial virus treatment evaluation method and system based on activity data

Abstract

The present application relates to the field of respiratory syncytial virus treatment evaluation, and discloses a respiratory syncytial virus treatment evaluation method and system based on activity data, which comprises information collection, data processing, judgment evaluation and data storage modules; multi-dimensional daily activity data is collected through a wearable device, baseline period, treatment monitoring period and follow-up period are divided, after effective verification and normalization processing, early response, short-term efficacy and functional outcome three-layer progressive individualized judgment threshold are constructed based on the patient's own baseline, layered logic judgment is sequentially executed according to time sequence, and finally four-level efficacy grades are combined and mapped and output. The present application does not need invasive laboratory detection, can realize whole-cycle dynamic evaluation at home, eliminates individual basic difference interference, covers activity ability and sleep quality in evaluation dimension, is logically consistent with disease rehabilitation process, can objectively and accurately reflect the real functional recovery state of patients, and provides reliable data support for clinical diagnosis and treatment adjustment and home rehabilitation monitoring.

Description

Technical Field

[0001] This invention relates to the field of respiratory syncytial virus (RSV) treatment evaluation, and more specifically, to a method and system for evaluating RSV treatment based on activity data. Background Technology

[0002] Respiratory syncytial virus (RSV) is a common pathogen causing acute respiratory infections, leading to symptoms such as fever, cough, and fatigue, resulting in decreased daily activity levels and sleep quality. It can pose a serious risk of illness in infants, the elderly, and immunocompromised individuals. Timely and accurate evaluation of treatment effectiveness is crucial for adjusting clinical protocols and assessing patient prognosis, directly impacting treatment efficiency and patient recovery quality.

[0003] Currently, the evaluation of the treatment efficacy of respiratory syncytial virus (RSV) mainly relies on two types of technical methods: The first category is laboratory-based pathogen detection, which involves antigen testing, nucleic acid amplification testing, or viral load measurement through nasopharyngeal swab sampling, with viral clearance as the core criterion for evaluating treatment efficacy. Although this type of method has high pathogen specificity, it is an invasive, site-specific test that requires patients to go to a medical institution for professional operation, making continuous dynamic monitoring in a home setting impossible and resulting in poor evaluation timeliness. Furthermore, changes in viral load only reflect the level of pathogens and cannot directly reflect the recovery of the patient's daily activities and overall functional status after treatment, resulting in a single evaluation dimension and a disconnect from the patient's actual recovery experience.

[0004] The second type is the clinical symptom scoring method, in which healthcare professionals or patients complete symptom scales, assessing treatment efficacy based on the severity of subjective symptoms such as cough, wheezing, and fatigue. This method has a low barrier to entry, but the evaluation results are significantly influenced by the patient's subjective feelings, cognitive level, and the judgment standards of healthcare professionals, resulting in insufficient consistency and repeatability. Furthermore, symptom scores are typically discrete assessments, making it difficult to capture subtle changes in a patient's daytime activity levels and accurately reflect the progress of functional recovery after treatment. It is particularly unsuitable for long-term efficacy monitoring of patients receiving home treatment.

[0005] However, existing solutions are mostly designed for general health status monitoring or chronic disease management, and lack a specific evaluation system for the rehabilitation characteristics of respiratory syncytial virus (RSV) infection. Some solutions used for evaluating the efficacy of treatment for infectious diseases generally use standardized normative thresholds for the entire population as the judgment criteria, failing to consider the heterogeneity of baseline activity levels among patients of different ages, with varying basic physical fitness levels and comorbidities. This makes the evaluation results susceptible to interference from individual baseline differences, resulting in insufficient accuracy. Furthermore, existing methods often use comparisons of indicators at single time points to determine efficacy, failing to distinguish between different rehabilitation stages—early treatment response, short-term treatment effects, and long-term functional outcomes—resulting in a coarse-grained evaluation. It is evident that existing respiratory syncytial virus (RSV) treatment evaluation technologies suffer from several shortcomings, including strong subjectivity, insufficient timeliness, inability to accurately reflect the patient's daily functional recovery status, poor individualization, and incomplete judgment logic. These shortcomings make it difficult to meet the needs for dynamic, objective, and accurate efficacy evaluation in home treatment scenarios.

[0006] Therefore, it is necessary to design a respiratory syncytial virus (RSV) treatment evaluation system based on activity data to address the problems of existing RSV treatment evaluation technologies, such as strong subjectivity, insufficient timeliness, inability to truly reflect the patient's daily functional recovery status, poor individualization adaptability, incomplete judgment logic, and difficulty in meeting the needs for dynamic, objective, and accurate efficacy evaluation in home treatment scenarios. Summary of the Invention

[0007] In view of this, the present invention proposes a method and system for evaluating respiratory syncytial virus (RSV) treatment based on activity data, aiming to solve the problems of existing RSV treatment evaluation technologies, such as strong subjectivity, insufficient timeliness, inability to truly reflect the patient's daily functional recovery status, poor individualization adaptability, and incomplete judgment logic, which make it difficult to meet the needs of dynamic, objective, and accurate efficacy evaluation in home treatment scenarios.

[0008] In one aspect, the present invention proposes a respiratory syncytial virus (RSV) treatment evaluation system based on activity data, comprising: The information collection module is used to continuously collect multi-dimensional daily activity data of patients and simultaneously divide the data into a baseline period for establishing benchmarks, a treatment monitoring period for monitoring efficacy, and a follow-up period for assessing recovery levels. The data processing module is used to verify the validity of the activity data collected by the information collection module, remove invalid data, normalize the dimensions, and then calculate the baseline mean and baseline coefficient of variation of each activity dimension based on the valid data of the baseline period. The judgment and evaluation module is used to construct three progressive judgment thresholds—early response threshold, short-term efficacy threshold, and functional outcome threshold—based on the baseline mean and baseline coefficient of variation of each activity dimension of the patient obtained by the data processing module. Simultaneously, the early treatment response judgment, short-term efficacy judgment, and functional outcome judgment are executed sequentially according to the time sequence, and the three judgment results are combined and mapped to output the evaluation result corresponding to the efficacy level. The data storage module is used to store historical daily activity data collected by the information collection module, as well as early response thresholds, short-term efficacy thresholds, and functional outcome thresholds constructed by the judgment and evaluation module.

[0009] Furthermore, the multi-dimensional daily activity data collected by the information collection module includes five dimensions: cumulative daily steps, duration of moderate daily activity, cumulative daily rest time, frequency of daily body position changes, and nighttime sleep fragmentation index. The information collection module is configured to divide the treatment into a baseline period for establishing a benchmark, a treatment monitoring period for monitoring efficacy, and a follow-up period for assessing recovery level. The baseline period is the 7 consecutive days before the start of treatment, the treatment monitoring period is from the start of treatment to the 14th day of treatment, and the follow-up period is the 7 consecutive days after the end of treatment.

[0010] Furthermore, the data processing module is configured to: remove data with a valid collection duration of less than 20 hours on the same day as invalid data, and then use the min-max normalization method to map the processed data of each dimension to the [0,1] interval; then calculate the baseline mean and baseline coefficient of variation of each activity dimension based on the normalized data of each dimension.

[0011] Furthermore, the judgment and evaluation module is configured as follows: Daily cumulative steps, daily moderate activity duration, and daily postural change frequency are used as positive indicators, while daily cumulative resting time and nighttime sleep fragmentation index are used as negative indicators.

[0012] Early response thresholds for each dimension of data were constructed. The coefficient of variation of 1.28 times the baseline corresponding to the 90% confidence interval of one side was used as the change magnitude threshold, which was then converted into a relative change rate threshold and used as the early response threshold. Construct short-term efficacy thresholds for data across various dimensions, including thresholds for the rate of improvement of positive indicators, the rate of decline of negative indicators, and stability thresholds; Construct functional regression thresholds for data in each dimension, including the first positive indicator recovery rate threshold, the second positive indicator recovery rate threshold, the first negative indicator decline rate threshold, the second negative indicator decline rate threshold, and the volatility consistency threshold.

[0013] Furthermore, the judgment and evaluation module is also configured as follows: The observation window period from day 3 to day 7 of treatment was used to assess early treatment response. Calculate the rate of change of each activity indicator relative to the baseline on a daily basis, and count the number of qualified dimensions whose daily rate of change is greater than or equal to the early response threshold of the corresponding dimension. If the number of dimensions that meet the target is greater than or equal to 4 for two consecutive days, it is considered that an early treatment response has occurred; If the number of dimensions that meet the target criteria is less than 4 but greater than or equal to 2 for three consecutive days, it is considered a suspicious treatment response; If the criteria for early treatment response or suspected treatment response are not met by the 7th day of treatment, it is determined that there is no early treatment response, and the conclusion of short-term treatment ineffective is directly output.

[0014] Furthermore, the judgment and evaluation module is also configured to perform a short-term efficacy judgment after the early treatment response judgment is completed: When an early treatment response is determined to be present: The period from day 8 to day 14 of treatment was used as the observation window for short-term efficacy assessment. Calculate the mean and actual coefficient of variation for each dimension using valid data from the most recent three consecutive days. Then, calculate the rate of change of the mean for each dimension relative to the baseline to obtain the actual improvement rate of each positive indicator and the actual decline rate of each negative indicator. When the actual improvement rate of a positive indicator is greater than or equal to the threshold value, the indicator for that dimension is considered to have met the standard. Similarly, when the actual decline rate of a negative indicator is greater than or equal to the threshold value, the indicator for that dimension is considered to have met the standard. When all dimensional indicators meet the standards and the actual interval coefficient of variation is less than or equal to the stability threshold, the short-term treatment is deemed effective. When the number of dimensions that meet the standard is greater than or equal to 1 and less than or equal to 4, or when all 5 dimensions meet the standard but the actual interval coefficient of variation is greater than the stability threshold, the short-term treatment is deemed to be partially effective. If all five dimensions fail to meet the standards, the treatment is immediately deemed ineffective in the short term.

[0015] Furthermore, the judgment and evaluation module is also configured to: when the early treatment response is determined to be a suspicious treatment response, calculate the mean of each dimension and the actual interval coefficient of variation from the data of day 8 to day 10 of treatment to determine the short-term efficacy. Calculate the rate of change of the mean of each dimension relative to the baseline to obtain the actual improvement rate of each positive indicator and the actual decline rate of each negative indicator. When the actual improvement rate of a positive indicator is greater than or equal to the threshold value of the positive indicator improvement rate, the indicator for that dimension is deemed to have met the standard. When the actual decline rate of a negative indicator is greater than or equal to the threshold value of the negative indicator decline rate, the indicator for that dimension is deemed to have met the standard. When all dimensional indicators meet the standards and the actual interval coefficient of variation is less than or equal to the stability threshold, the short-term treatment is deemed effective. If not all dimensional indicators meet the standards, or if the actual interval coefficient of variation is greater than the stability threshold, the treatment is deemed ineffective in the short term.

[0016] Furthermore, the judgment and evaluation module is also configured to: take the valid data from the last 3 days of the follow-up period, calculate the mean of each dimension and the actual interval coefficient of variation, obtain the actual recovery rate of each positive indicator and the actual decline rate of each negative indicator, and then perform a functional reversion judgment: If the short-term efficacy is determined to be effective, the functional outcome is determined as follows: When the actual recovery rate of all positive indicators is greater than or equal to the first positive indicator recovery rate threshold, the actual decline rate of all negative indicators is less than or equal to the first negative indicator decline rate threshold, and the absolute value of the difference between the actual interval coefficient of variation and the baseline coefficient of variation is less than or equal to the fluctuation consistency threshold, it is determined that the function has completely reverted. When the actual recovery rate of all positive indicators is less than the second positive indicator recovery rate threshold, and the actual decline rate of all negative indicators is greater than the second negative indicator decline rate threshold, the function is judged to be not recovered. If neither the criteria for complete functional reversion nor the criteria for functional non-reversion are met, it is determined to be a partial functional reversion. If the short-term efficacy is determined to be partially effective after short-term treatment, the functional outcome is determined as follows: When the recovery rate of all positive indicators is less than the second positive indicator recovery rate threshold, and the actual decline rate of all negative indicators is greater than the second negative indicator decline rate threshold, it is determined that the function has not been restored; otherwise, it is determined that the function has partially reverted.

[0017] Furthermore, the judgment and evaluation module is also configured to: combine and map the three-level judgment results, and output the evaluation result corresponding to the therapeutic effect level: When an early treatment response is determined to be an early treatment response, a short-term efficacy is determined to be a short-term treatment effect, and a functional outcome is determined to be a complete functional outcome, the efficacy level is Grade 1, which is excellent. When the early treatment response is determined to be an early treatment response, the short-term efficacy is determined to be effective in short-term treatment, and the functional outcome is determined to be partial functional outcome, or when the early treatment response is determined to be a suspicious treatment response, the short-term efficacy is determined to be effective in short-term treatment, and the functional outcome is determined to be complete functional outcome, the efficacy level is Grade 2, which is good. When an early treatment response is determined to be an early treatment response, a short-term efficacy is determined to be partially effective, and a functional outcome is determined to be partially functional, or when an early treatment response is determined to be a questionable treatment response, a short-term efficacy is determined to be effective, and a functional outcome is determined to be partially functional, the efficacy level is grade 3, moderate efficacy. When the early treatment response is determined to be non-responsive, or when the short-term efficacy is determined to be ineffective, or when the functional outcome is determined to be functional failure, the efficacy level is grade 4, which is considered poor.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention uses objective activity data as the core evaluation basis, enabling daily dynamic evaluation throughout the entire treatment cycle. It overcomes the shortcomings of traditional etiological testing, such as poor timeliness and limited operational scenarios. It can promptly capture functional changes after treatment, providing real-time data support for tracking the efficacy of home-based treatment patients and adjusting clinical protocols.

[0019] 2. This invention adopts a three-tiered progressive judgment framework of "early response - short-term efficacy - long-term outcome". The results of the preceding judgment directly determine the branch path of the subsequent judgment, and the logical chain is tightly closed. The evaluation dimensions cover three levels: symptom response, functional improvement and stable recovery. It not only reflects the immediate effect of treatment, but also reflects the recovery level of the patient's real daily activity ability, making up for the functional evaluation blind spots of traditional virological indicators and subjective scores.

[0020] 3. All judgment thresholds in this invention are generated based on the patient's own baseline data and statistical rules, without relying on population norms. This eliminates the interference of individual differences caused by factors such as age, basic physical fitness, and comorbidities, and can be adapted to different types of RSV-infected populations such as infants, the elderly, and those with weakened immune systems, resulting in higher evaluation accuracy.

[0021] On the other hand, this application also provides a method for evaluating respiratory syncytial virus (RSV) treatment based on activity data, including the following steps: Continuously collect multi-dimensional daily activity data from patients, and simultaneously divide the data into a baseline period for establishing benchmarks, a treatment monitoring period for monitoring efficacy, and a follow-up period for assessing recovery levels. The collected activity data is validated to remove invalid data, then normalized in terms of dimensions, and then the baseline mean and baseline coefficient of variation of each activity dimension are calculated based on the valid data of the baseline period. Based on the baseline mean and baseline coefficient of variation of each activity dimension of the patients, three progressive thresholds were constructed: early response threshold, short-term efficacy threshold, and functional outcome threshold. The early treatment response assessment, short-term efficacy assessment, and functional outcome assessment are performed sequentially according to the time sequence. The results of the three assessments are then combined and mapped to output the evaluation results corresponding to the efficacy level.

[0022] It is understandable that the above-mentioned respiratory syncytial virus treatment evaluation methods and systems based on activity data have the same beneficial effects, and will not be elaborated further here. Attached Figure Description

[0023] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A functional block diagram of a respiratory syncytial virus (RSV) treatment evaluation system based on activity data provided in an embodiment of the present invention; Figure 2 A flowchart of a respiratory syncytial virus (RSV) treatment evaluation method based on activity data provided in an embodiment of the present invention. Detailed Implementation

[0024] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0025] Reference Figure 1 In some embodiments of this application, a respiratory syncytial virus (RSV) treatment evaluation system based on activity data includes: The information collection module is used to continuously collect multi-dimensional daily activity data of patients and simultaneously divide the data into a baseline period for establishing benchmarks, a treatment monitoring period for monitoring efficacy, and a follow-up period for assessing recovery levels. The data processing module is used to verify the validity of the activity data collected by the information collection module, remove invalid data, normalize the dimensions, and then calculate the baseline mean and baseline coefficient of variation of each activity dimension based on the valid data of the baseline period. The judgment and evaluation module is used to construct three progressive judgment thresholds—early response threshold, short-term efficacy threshold, and functional outcome threshold—based on the baseline mean and baseline coefficient of variation of each activity dimension of the patient obtained by the data processing module. Simultaneously, the early treatment response judgment, short-term efficacy judgment, and functional outcome judgment are executed sequentially according to the time sequence, and the three judgment results are combined and mapped to output the evaluation result corresponding to the efficacy level. The data storage module is used to store historical daily activity data collected by the information collection module, as well as early response thresholds, short-term efficacy thresholds, and functional outcome thresholds constructed by the judgment and evaluation module.

[0026] Specifically, the information acquisition module, serving as the system's data input port, establishes a stable connection with the patient's wrist-worn wearable accelerometer via Bluetooth 5.0, receiving raw acceleration vector data and resting heart rate data uploaded by the sensor in real time. The module incorporates period segmentation logic, automatically dividing the evaluation into three phases—baseline, treatment monitoring, and follow-up—based on the patient's entered treatment start date, providing a precise time reference for subsequent phased assessments. The core function of this module is to ensure continuous, time-sequential data acquisition, serving as the data foundation for all evaluation logic.

[0027] The data processing module receives the raw data output from the information collection module and performs data cleaning and statistical calculations according to preset rules. First, it filters out low-quality and excessively missing data through validity checks. Then, it eliminates numerical scale differences between different dimensions of indicators through dimensional normalization. Finally, it calculates individual baseline statistical parameters based on valid baseline data. The core principle of this module is to eliminate data noise and dimensional differences through standardized preprocessing, constructing a purely individualized benchmark system, and fundamentally avoiding the interference of population heterogeneity such as age, basic physical fitness, and comorbidities on the evaluation results.

[0028] The judgment and evaluation module is the core computational and decision-making unit of the system. On one hand, based on the baseline statistics output by the data processing module, it generates three levels of individualized judgment thresholds according to preset statistical rules, without relying on population norms. On the other hand, it strictly follows the chronological order, sequentially performing a three-level progressive logical judgment of early treatment response, short-term efficacy, and functional outcome. The judgment result of the previous level directly serves as the input and branching basis for the judgment of the next level, ultimately generating a standardized four-level efficacy rating through combination mapping. This module adopts a hierarchical progressive judgment logic that precisely matches the natural recovery process after RSV infection: "early drug response - mid-term symptom improvement - long-term functional recovery," and the evaluation logic fully conforms to clinical pathophysiological laws.

[0029] Data storage module: Deployed using an encrypted relational database, with four storage partitions: original data table, baseline parameter table, threshold configuration table, and evaluation result table, storing historical activity data, baseline statistical parameters, judgment thresholds at each level, and final evaluation results respectively; at the same time, an off-site backup mechanism is configured to ensure medical data security and full-process traceability.

[0030] Understandably, this invention uses objective activity data as the core evaluation basis, enabling daily dynamic evaluation throughout the entire treatment cycle. It overcomes the shortcomings of traditional etiological testing, such as poor timeliness and limited operational scenarios, and can promptly capture functional changes after treatment, providing real-time data support for tracking the efficacy of home-based treatment patients and adjusting clinical protocols.

[0031] It is understandable that this invention adopts a three-tiered progressive judgment framework of "early response - short-term efficacy - long-term outcome". The results of the preceding judgment directly determine the branch path of the subsequent judgment, and the logical chain is tightly closed. The evaluation dimensions cover three levels: symptom response, functional improvement and stable recovery. It not only reflects the immediate effect of treatment, but also reflects the recovery level of the patient's real daily activity ability, making up for the functional evaluation blind spots of traditional virological indicators and subjective scores.

[0032] It is understood that all the judgment thresholds in this invention are generated based on the patient's own baseline data and statistical rules, without relying on population norms. This eliminates the interference of individual differences caused by factors such as age, basic physical fitness, and comorbidities, and can be adapted to different types of RSV-infected populations such as infants, the elderly, and those with weakened immune systems, resulting in higher evaluation accuracy.

[0033] In some specific embodiments of the present invention, the multi-dimensional daily activity data collected by the information collection module includes five dimensions: daily cumulative steps, daily moderate activity duration, daily cumulative rest duration, daily body position change frequency, and nighttime sleep fragmentation index. The information collection module is configured to divide the treatment into a baseline period for establishing a benchmark, a treatment monitoring period for monitoring efficacy, and a follow-up period for assessing recovery level. The baseline period is the 7 consecutive days before the start of treatment, the treatment monitoring period is from the start of treatment to the 14th day of treatment, and the follow-up period is the 7 consecutive days after the end of treatment.

[0034] Specifically, the selection of the five activity dimensions closely corresponds to the core impact of RSV infection on human function, and the specific calculation rules for each dimension are as follows: Daily cumulative steps: Step peaks are identified through an acceleration peak detection algorithm, and effective step points are screened by a step frequency threshold of 1.5Hz~3Hz. The total number of all effective step points in a single day is accumulated, which reflects the patient's overall activity tolerance and total daily activity volume.

[0035] The duration of moderate activity in a single day is defined as a motor segment with a synthetic acceleration amplitude ≥0.5g and a single duration ≥10s. The total duration of all segments in a single day is accumulated, which is the core indicator of the patient's physical recovery level and ability to move independently.

[0036] Daily cumulative resting time: A resting segment is defined as a state segment with a synthetic acceleration amplitude of <0.1g and a single duration of ≥30s. The total duration of all segments on the day is accumulated, which mainly reflects the patient's fatigue level and bed rest time, and conversely reflects the degree of physical exertion caused by infection.

[0037] Daily positional change frequency: By identifying two types of positional transitions, sitting-to-standing and lying-to-sitting, through an acceleration vector space angle change of ≥60° and stable duration of ≥2s, the total number of transitions per day is counted, which is the core indicator of the patient's daily self-care ability and muscle strength recovery.

[0038] Nighttime sleep fragmentation index: The period from 22:00 to 6:00 the next day is defined as the sleep period. The number of rest interruptions per hour during this period is counted (interruption duration ≥1min is counted as 1 awakening). The hourly average is taken, which mainly reflects the impact of infection on the patient's sleep quality and the recovery of sleep structure.

[0039] The baseline period is taken for 7 consecutive days before the start of treatment. A sufficient sample size can stably characterize the patient's baseline level of daily activities before the onset of the disease and avoid the impact of random daily fluctuations on the accuracy of the baseline. The treatment monitoring period is from the start of treatment to day 14 of treatment, covering the entire course of routine antiviral treatment for RSV, and can fully monitor functional changes throughout the treatment process; The follow-up period is 7 consecutive days after the end of treatment, used to assess the maintenance and outcome of function after treatment cessation, and to reflect the long-term effects of treatment.

[0040] If the patient's treatment begins on the 10th of the month, the baseline period is from the 3rd to the 9th of the month, the treatment monitoring period is from the 10th to the 23rd of the month, and the follow-up period is from the 24th to the 30th of the month. The system automatically calculates five data points for the patient each day: steps, duration of moderate activity, resting time, frequency of changes in body position, and sleep fragmentation index, which serve as the basis for subsequent judgment.

[0041] It is understandable that the five dimensions collected in this invention cover five core rehabilitation dimensions: activity endurance, physical fitness level, fatigue level, self-care ability, and sleep quality. At the same time, it includes both positive activity ability and negative symptom load from a dual perspective, which completely makes up for the single-dimensional deficiency of traditional evaluation that only focuses on viral load. The evaluation results are more correlated with the patient's real quality of life. Meanwhile, the division of the three cycles strictly follows the clinical course and treatment cycle of RSV, and the setting of evaluation nodes has clear clinical significance, avoiding evaluation bias caused by arbitrarily setting time nodes. Moreover, all dimensions are calculated based on acceleration data, requiring no additional sensor hardware and can be achieved simply through a regular wearable wristband, resulting in low implementation costs and high patient acceptance.

[0042] In some specific embodiments of the present invention, the data processing module is configured to: remove data with a valid collection duration of less than 20 hours on the same day as invalid data, and then use the min-max normalization method to map the processed data of each dimension to the [0,1] interval; and then calculate the baseline mean and baseline coefficient of variation of each activity dimension based on the normalized data of each dimension.

[0043] Specifically, the validity verification rule is as follows: Each day, the effective data collection duration is checked to see if it is ≥20 hours. Data less than 20 hours is considered invalid and directly discarded. The principle behind setting the 20-hour threshold is that this duration fully covers the 14-hour daytime activity period and the 6-hour nighttime sleep period. If the daily collection duration is less than 20 hours, it indicates that the device has been detached or shut down for an extended period, and the data cannot represent the patient's true activity level that day. Including this data in the judgment would distort the results.

[0044] For the five active dimensions of the remaining valid data, min-max normalization is performed to map the values ​​to the [0,1] interval. The calculation formula is as follows: Where x is the measured value for that day. , These are the minimum and maximum values ​​of the data for the entire period of this dimension, respectively. The core function of normalization is to eliminate the differences in units between different dimensions (such as steps being measured in "steps" and duration in "minutes"), making the rates of change of different dimensions comparable and providing a unified numerical basis for subsequent multi-dimensional joint judgments.

[0045] Baseline statistics calculation: Based on valid data within the baseline period, the baseline means µ for each of the five dimensions are calculated. b Compared with baseline coefficient of variation (CV) b ,in , This represents the standard deviation of this dimension at baseline. The coefficient of variation is a dimensionless indicator that accurately characterizes the natural fluctuations in a patient's baseline activity level and is a core parameter for subsequently constructing individualized thresholds.

[0046] For example, if a patient's device wear time was only 16 hours on one day within the 7-day baseline period, the system would determine it as invalid data and remove it directly. The remaining 6 days of valid data would be used to calculate the baseline parameters. For the step count dimension, the minimum value for the entire period was 2000 steps and the maximum value was 10000 steps. A measured value of 6000 steps was normalized to a value of 0.5. Finally, the patient's baseline mean step count was calculated to be 8000 steps, the standard deviation was 800 steps, and the baseline coefficient of variation was 10%.

[0047] Understandably, the rigorous validity verification of this invention filters out low-quality data from the source, preventing abnormal situations such as equipment detachment and data loss from interfering with the evaluation results and ensuring the reliability of the evaluation data. At the same time, min-max normalization achieves standardization and unification of multi-dimensional data, solving the technical problem that indicators of different dimensions cannot be directly compared and judged, and laying the algorithmic foundation for multi-dimensional joint judgment. Moreover, this invention uses the baseline coefficient of variation as a fluctuation characterization parameter, eliminating the influence of numerical scale, and can be used uniformly across dimensions and populations, ensuring the scientific nature and universality of the individualized threshold system.

[0048] In some specific embodiments of the present invention, the judgment and evaluation module is configured as follows: Daily cumulative steps, daily moderate activity duration, and daily postural change frequency are used as positive indicators, while daily cumulative resting time and nighttime sleep fragmentation index are used as negative indicators.

[0049] Early response thresholds for each dimension of data were constructed. The coefficient of variation of 1.28 times the baseline corresponding to the 90% confidence interval of one side was used as the change magnitude threshold, which was then converted into a relative change rate threshold and used as the early response threshold. Construct short-term efficacy thresholds for data across various dimensions, including thresholds for the rate of improvement of positive indicators, the rate of decline of negative indicators, and stability thresholds; Construct functional regression thresholds for data in each dimension, including the first positive indicator recovery rate threshold, the second positive indicator recovery rate threshold, the first negative indicator decline rate threshold, the second negative indicator decline rate threshold, and the volatility consistency threshold.

[0050] Specifically, daily cumulative steps, daily moderate activity duration, and daily postural change frequency are classified as positive indicators, with higher values ​​indicating better functional activity. Daily cumulative resting time and nighttime sleep fragmentation index are classified as negative indicators, with lower values ​​indicating better functional activity. The core purpose of classifying indicators as positive and negative is to unify the logic for judging the rate of change, ensuring that the rule of "values ​​changing in a positive direction reaching a threshold indicate compliance" is uniformly applied to all dimensions, avoiding confusion in the judgment logic of different indicator directions.

[0051] Early response threshold: Based on a one-sided 90% confidence interval, the value is set to the relative rate of change corresponding to 1.28 times the baseline standard deviation, i.e., early response threshold T1 = 1.28 × CV. b The statistical principle behind this is that when the magnitude of the change in an indicator exceeds the 90% confidence interval of the baseline's natural fluctuations, the change can be considered not to be caused by random fluctuations, but rather to be a statistically significant effect produced by the treatment, and is used to identify functional change signals in the early stages of treatment.

[0052] Short-term efficacy thresholds include three sub-thresholds: a 20% improvement rate threshold for positive indicators (meaning a positive indicator improves by at least 20% from the baseline mean); a 15% decline rate threshold for negative indicators (meaning a negative indicator declines by at least 15% from the baseline mean); and a stability threshold where the coefficient of variation of data over three consecutive days does not exceed 80% of the baseline coefficient of variation. The amplitude threshold corresponds to the degree of clinically significant functional improvement, while the stability threshold corresponds to the reliability of the sustained improvement. Combining these two thresholds allows for accurate determination of a stable treatment effect.

[0053] Functional outcome thresholds comprise five sub-thresholds: The first positive indicator recovery rate threshold is 90%, meaning the positive indicator recovers to more than 90% of the baseline mean; the second positive indicator recovery rate threshold is 70%, meaning the positive indicator recovers to more than 70% of the baseline mean; the first negative indicator decline rate threshold is 110%, meaning the negative indicator declines to less than 110% of the baseline mean; the second negative indicator decline rate threshold is 130%, meaning the negative indicator declines to less than 130% of the baseline mean; and the consistency of fluctuation threshold is 10%, meaning the absolute value of the difference between the coefficient of variation during the follow-up period and the baseline coefficient of variation does not exceed 10%. The first threshold corresponds to a near-pre-illness level of complete recovery, the second threshold corresponds to a clinically significant minimum recovery line, and consistency of fluctuation corresponds to the degree of recovery of activity rhythm. The combination of these three thresholds provides a comprehensive assessment of the quality of functional outcome.

[0054] If a patient's baseline step count coefficient of variation is 10%, then the early response threshold is 12.8%, meaning that an increase in daily steps exceeding 12.8% is considered to have achieved an early response in this dimension; the short-term efficacy positive improvement rate threshold is 20%, meaning that an increase in steps of ≥20% from baseline is considered to have achieved a short-term efficacy in this dimension; the stability threshold is 8% (80% of the baseline coefficient of variation); the first recovery threshold for functional outcome is 90%, and the second recovery threshold is 70%, meaning that a recovery in steps to 90% or more of the baseline is considered near-complete recovery, and 70% or more is considered to have met the minimum recovery standard; the fluctuation consistency threshold is 10%.

[0055] Understandably, all thresholds are generated based on the patient's own baseline data, without relying on a unified population norm, thus completely eliminating the interference of individual differences such as age, basic physical fitness, and comorbidities. It is applicable to ordinary young and middle-aged patients, as well as special RSV-infected populations such as infants, the elderly, and those with weakened immune systems, making it more widely applicable. The three thresholds correspond to different stages of rehabilitation. The threshold settings are based on both statistical evidence and clinical significance, ensuring the scientific nature of the evaluation while meeting actual clinical needs. The unified division of positive and negative indicators makes the judgment logic simpler and clearer, reduces the complexity of the algorithm, and improves the system's operating efficiency.

[0056] In some specific embodiments of the present invention, the judgment and evaluation module is further configured as follows: The observation window period from day 3 to day 7 of treatment was used to assess early treatment response. Calculate the rate of change of each activity indicator relative to the baseline on a daily basis, and count the number of qualified dimensions whose daily rate of change is greater than or equal to the early response threshold of the corresponding dimension. If the number of dimensions that meet the target is greater than or equal to 4 for two consecutive days, it is considered that an early treatment response has occurred; If the number of dimensions that meet the target criteria is less than 4 but greater than or equal to 2 for three consecutive days, it is considered a suspicious treatment response; If the criteria for early treatment response or suspected treatment response are not met by the 7th day of treatment, it is determined that there is no early treatment response, and the conclusion of short-term treatment ineffective is directly output.

[0057] Specifically, the period from day 3 to day 7 of treatment was selected as the early response observation window. The clinical basis for this is that the onset time of RSV antiviral treatment is usually 2 to 3 days after treatment, and detectable functional improvements begin to appear from day 3. If there is still no clear response signal by day 7, it suggests that the treatment regimen is likely ineffective. Therefore, day 7 is the final determination point for early response.

[0058] Calculate the rate of change of each activity indicator relative to the baseline on a daily basis; the rate of change of positive indicators is... The rate of change of negative indicators The number of dimensions that meet the early response threshold for the corresponding dimension and whose daily change rate reaches the target value is counted.

[0059] Three-category result determination principle: For two consecutive days, the number of dimensions meeting the standard is ≥4: if more than 4 out of 5 dimensions improve simultaneously and for 2 consecutive days, single-day random fluctuations can be ruled out, and an early treatment response can be clearly identified. After the determination, the subsequent determination of this layer is immediately terminated, and the short-term efficacy determination is directly entered to avoid subsequent data fluctuations from interfering with the conclusion.

[0060] If the number of dimensions meeting the target is 2-3 for 3 consecutive days: there are signs of improvement, but the dimension coverage is insufficient and the intensity is weak, and it is judged as a suspicious treatment response, which requires further confirmation of efficacy.

[0061] If the first two conditions are not met by day 7: there is no clear response signal throughout the treatment, it is determined that there is no early treatment response, the conclusion of short-term treatment ineffective is directly output, all subsequent evaluations are terminated, and the clinic is promptly notified that the treatment plan is ineffective.

[0062] For example, if Patient A achieves 3 target dimensions on day 3 of treatment, 4 on day 4, and 4 on day 5, with ≥4 target dimensions for 2 consecutive days, the system will determine on day 5 that an early treatment response has occurred, terminate the current assessment, and proceed to short-term efficacy evaluation; if Patient B achieves 2 target dimensions on days 3-5 of treatment, with 2-3 target dimensions for 3 consecutive days, the system will determine a questionable treatment response; if Patient C achieves ≤1 target dimensions for the first 5 days of treatment, but still fails to meet the first two conditions by day 7, the system will determine no early treatment response and directly output a conclusion of short-term ineffective treatment.

[0063] Understandably, early response assessment can quickly identify the treatment response status within one week of treatment, provide timely warnings of ineffective treatment, and provide early evidence for clinical adjustment of treatment plans, thus avoiding patients receiving ineffective treatment and delaying their condition. This invention adopts the "continuous achievement" judgment rule, which effectively eliminates false positive results caused by occasional fluctuations in daily activity levels and balances the sensitivity and specificity of the evaluation. Moreover, the three-level grading judgment of this invention covers all scenarios from strong response to no response, providing accurate preliminary basis for subsequent stratification of short-term efficacy and making the overall evaluation system more adaptable.

[0064] In some specific embodiments of the present invention, the judgment and evaluation module is further configured to perform short-term efficacy judgment after the early treatment response judgment is completed: When an early treatment response is determined to be present: The period from day 8 to day 14 of treatment was used as the observation window for short-term efficacy assessment. Calculate the mean and actual coefficient of variation for each dimension using valid data from the most recent three consecutive days. Then, calculate the rate of change of the mean for each dimension relative to the baseline to obtain the actual improvement rate of each positive indicator and the actual decline rate of each negative indicator. When the actual improvement rate of a positive indicator is greater than or equal to the threshold value, the indicator for that dimension is considered to have met the standard. Similarly, when the actual decline rate of a negative indicator is greater than or equal to the threshold value, the indicator for that dimension is considered to have met the standard. When all dimensional indicators meet the standards and the actual interval coefficient of variation is less than or equal to the stability threshold, the short-term treatment is deemed effective. When the number of dimensions that meet the standard is greater than or equal to 1 and less than or equal to 4, or when all 5 dimensions meet the standard but the actual interval coefficient of variation is greater than the stability threshold, the short-term treatment is deemed to be partially effective. If all five dimensions fail to meet the standards, the treatment is immediately deemed ineffective in the short term.

[0065] Specifically, short-term efficacy assessment employs a rolling assessment mechanism. Starting from day 10 of treatment (when three consecutive days of valid data are collected for the first time within the treatment window), after data collection is completed each day, a single assessment is performed using three consecutive days of valid data consisting of the current day and the previous two days. The principle behind using three consecutive days of data is to eliminate occasional fluctuations in single-day data and reflect the patient's stable functional status. The daily rolling assessment allows for confirmation of efficacy as soon as the target is achieved, without waiting for the window to end, significantly improving the timeliness of the evaluation.

[0066] The short-term efficacy assessment adopts a single-dimensional target achievement judgment: based on the data of three consecutive days, the mean of each dimension interval and the actual interval coefficient of variation are calculated, and the actual improvement rate of positive indicators and the actual decline rate of negative indicators are calculated respectively. When the corresponding threshold is reached, the target of that dimension is determined to be achieved.

[0067] Regarding the rules for determining the short-term efficacy of this invention: If all five dimensions meet the criteria and the actual interval coefficient of variation is less than or equal to the stability threshold, the treatment is deemed effective in the short term. All subsequent assessments at this stage are immediately terminated, and the treatment proceeds directly to the functional outcome assessment.

[0068] If the number of criteria is 1 to 4, or all 5 criteria are met but the actual interval coefficient of variation is greater than the stability threshold: the treatment is deemed to be partially effective in the short term. The current level of assessment is not terminated, and the observation continues on a daily rolling basis, with the possibility of being upgraded to be effective in the short term in the future.

[0069] If all five dimensions fail to meet the standards, the treatment is deemed ineffective in the short term, and the evaluation of this stage and all subsequent efficacy should be terminated immediately.

[0070] For example, for a patient who shows an early response, if data from days 8 to 10 are used to calculate the response on day 10 of treatment and three dimensions meet the target, the patient is judged to be partially effective in the short-term treatment and continues to be observed; if data from days 10 to 12 of treatment are used to calculate the response on day 12 and all five dimensions meet the target, and the coefficient of variation is 7% (≤8% stability threshold), the patient is judged to be effective in the short-term treatment on that day, the assessment at this level is terminated, and the patient enters the functional outcome assessment; if the patient only meets the target in two dimensions until day 14, the final conclusion of "partially effective in the short-term treatment" is used to enter the functional outcome assessment.

[0071] It is understandable that the daily rolling + termination upon reaching the target mechanism adopted in this invention not only ensures the stability of efficacy assessment but also greatly improves the timeliness of evaluation, allowing patients to know the efficacy results without waiting for the 14-day treatment course to end. The three-level assessment of this invention accurately distinguishes between three efficacy states: "completely stable improvement, partial improvement, and no improvement," providing finer evaluation granularity and richer decision-making references for clinical practice. This invention separately classifies "the magnitude of improvement is met but the stability is insufficient" as partially effective, and distinguishes between two different response modes: "insufficient improvement" and "improvement but large fluctuations". The evaluation results are more in line with the patient's actual recovery status and have higher clinical guidance value.

[0072] In some specific embodiments of the present invention, the judgment and evaluation module is further configured to: when the early treatment response is determined to be a suspicious treatment response, calculate the mean of each dimension and the actual interval coefficient of variation from the data of day 8 to day 10 of treatment to determine the short-term efficacy. Calculate the rate of change of the mean of each dimension relative to the baseline to obtain the actual improvement rate of each positive indicator and the actual decline rate of each negative indicator. When the actual improvement rate of a positive indicator is greater than or equal to the threshold value of the positive indicator improvement rate, the indicator for that dimension is deemed to have met the standard. When the actual decline rate of a negative indicator is greater than or equal to the threshold value of the negative indicator decline rate, the indicator for that dimension is deemed to have met the standard. When all dimensional indicators meet the standards and the actual interval coefficient of variation is less than or equal to the stability threshold, the short-term treatment is deemed effective. If not all dimensional indicators meet the standards, or if the actual interval coefficient of variation is greater than the stability threshold, the treatment is deemed ineffective in the short term.

[0073] Specifically, patients with suspected treatment response have weak early improvement signals and unclear responses. Therefore, stricter standards are set for their short-term efficacy assessment. Only those who fully meet the highest standard of "achieving all-dimensional targets + achieving stability targets" are considered effective. All other cases are considered ineffective to avoid overly optimistic judgments on weak response groups and to control the probability of false positives.

[0074] A one-time assessment mechanism is adopted: a final assessment is performed only on day 10 of treatment, without daily rolling assessments. Data from days 11 to 14 of treatment is only stored as a backup and does not participate in the assessment at this stage. The significance of setting the day 10 node is that it extends the observation period by 3 days compared to day 7, allowing more time for the treatment effect to manifest, while not requiring the completion of the full 14-day treatment course, thus balancing the accuracy and efficiency of the evaluation.

[0075] For example, for a patient with a questionable treatment response, if data from days 8 to 10 are used to calculate the response on day 10 of treatment, and all five dimensions meet the target, and the coefficient of variation is 7.5% (≤8% stability threshold), the patient is considered to have effective short-term treatment and enters the functional outcome evaluation. If only three dimensions meet the target, or if all dimensions meet the target but the coefficient of variation is 9%, the patient is directly considered to have ineffective short-term treatment and all subsequent efficacy evaluations are terminated.

[0076] Understandably, setting differentiated judgment rules for different groups of people with different early response strengths has achieved stratified adaptation of efficacy evaluation, which has not only avoided missing effective cases in weak response groups, but also strictly controlled the false positive rate of suspected groups, and significantly improved the overall evaluation accuracy. The one-time final determination mechanism simplifies the evaluation process for weak-responder populations, eliminating the need for continuous monitoring for up to 14 days. It can identify ineffective treatments earlier, helping clinicians to adjust treatment plans in a timely manner and reducing the medical burden on patients. Complementing the long-window rolling judgment, this makes the entire short-term efficacy judgment system both sensitive and rigorous, with stronger logical consistency.

[0077] In some specific embodiments of the present invention, the judgment and evaluation module is further configured to: take the effective data of the last 3 days of the follow-up period, calculate the mean of each dimension and the actual interval coefficient of variation, obtain the actual recovery rate of each positive indicator and the actual decline rate of each negative indicator, and then perform functional regression judgment: If the short-term efficacy is determined to be effective, the functional outcome is determined as follows: When the actual recovery rate of all positive indicators is greater than or equal to the first positive indicator recovery rate threshold, the actual decline rate of all negative indicators is less than or equal to the first negative indicator decline rate threshold, and the absolute value of the difference between the actual interval coefficient of variation and the baseline coefficient of variation is less than or equal to the fluctuation consistency threshold, it is determined that the function has completely reverted. When the actual recovery rate of all positive indicators is less than the second positive indicator recovery rate threshold, and the actual decline rate of all negative indicators is greater than the second negative indicator decline rate threshold, the function is judged to be not recovered. If neither the criteria for complete functional reversion nor the criteria for functional non-reversion are met, it is determined to be a partial functional reversion. If the short-term efficacy is determined to be partially effective after short-term treatment, the functional outcome is determined as follows: When the recovery rate of all positive indicators is less than the second positive indicator recovery rate threshold, and the actual decline rate of all negative indicators is greater than the second negative indicator decline rate threshold, it is determined that the function has not been restored; otherwise, it is determined that the function has partially reverted.

[0078] Specifically, the mean of each dimension interval and the actual interval coefficient of variation were calculated using valid data from the last 3 days of the follow-up period. The principle of selecting data from the end of the follow-up period is that the treatment effect has been sufficiently stabilized at this time, which can truly reflect the final functional recovery level of the patient after treatment and avoid the influence of fluctuations in the early follow-up period on the outcome determination.

[0079] For patients who respond to short-term treatment, a three-tiered assessment is established: priority is given to those who have achieved complete functional recovery: the actual recovery rate of all positive indicators is ≥ the first positive recovery rate threshold, the actual decline rate of all negative indicators is ≤ the first negative decline rate threshold, and the absolute value of the difference between the coefficient of variation of the follow-up period and the baseline coefficient of variation is ≤ the fluctuation consistency threshold. In other words, the activity amplitude and rhythm have recovered to near the pre-illness level, which is considered as complete functional recovery.

[0080] Further determination of non-recovery of function: The actual recovery rate of all positive indicators is less than the second positive recovery rate threshold, and the actual decline rate of all negative indicators is greater than the second negative decline rate threshold. In other words, the activity level is far from reaching the minimum recovery standard, and the function is determined to be non-recovery.

[0081] All cases that do not meet the criteria of complete reversion or failure to recover are uniformly judged as partial functional reversion.

[0082] For patients who respond to short-term treatment but do not meet the criteria for complete effectiveness in the medium term, the probability of achieving complete remission in the long term is extremely low. Therefore, no complete remission level is set. Instead, only the distinction between non-recovery of function and partial functional remission is made. The baseline for judgment is completely consistent with the former, ensuring the uniformity of the "non-recovery" standard across the entire treatment plan.

[0083] For example, a patient who responded well to short-term treatment showed a 92% recovery rate in steps, 95% in moderate activity, 91% in postural changes, a 105% reduction rate in resting duration, and a 108% reduction in sleep fragmentation during the last 3 days of follow-up. The coefficient of variation during the follow-up period was 8% (≤10%) compared to baseline, and was therefore judged to have a complete functional outcome. Another patient had a 85% recovery rate in steps, and all other indicators reached the first threshold. Because the patient did not meet the criteria for complete outcome and was not considered to have not recovered, the patient was judged to have a partial functional outcome. A patient who responded partially to short-term treatment showed a recovery rate of <70% for all positive indicators and a reduction rate of >130% for all negative indicators, and was judged to have not recovered functionally. All other cases were judged to have a partial functional outcome.

[0084] It is understandable that setting differentiated outcome levels for patients with different mid-term efficacy is in line with the objective rehabilitation law that "the better the mid-term efficacy, the higher the upper limit of long-term recovery," and avoids the logical leap of "poor mid-term efficacy and complete remission in the end stage," so that the evaluation results are more in line with clinical reality. It considers both the extent of functional recovery and the stability of activity rhythm, evaluating not only "whether or not one can move," but also "whether the activity pattern has returned to normal," providing a more comprehensive reflection of the patient's true quality of life and offering a more in-depth evaluation dimension.

[0085] In some specific embodiments of the present invention, the judgment and evaluation module is further configured to: combine and map the three-layer judgment results to output the evaluation result corresponding to the therapeutic effect level: When an early treatment response is determined to be an early treatment response, a short-term efficacy is determined to be a short-term treatment effect, and a functional outcome is determined to be a complete functional outcome, the efficacy level is Grade 1, which is excellent. When the early treatment response is determined to be an early treatment response, the short-term efficacy is determined to be effective in short-term treatment, and the functional outcome is determined to be partial functional outcome, or when the early treatment response is determined to be a suspicious treatment response, the short-term efficacy is determined to be effective in short-term treatment, and the functional outcome is determined to be complete functional outcome, the efficacy level is Grade 2, which is good. When an early treatment response is determined to be an early treatment response, a short-term efficacy is determined to be partially effective, and a functional outcome is determined to be partially functional, or when an early treatment response is determined to be a questionable treatment response, a short-term efficacy is determined to be effective, and a functional outcome is determined to be partially functional, the efficacy level is grade 3, moderate efficacy. When the early treatment response is determined to be non-responsive, or when the short-term efficacy is determined to be ineffective, or when the functional outcome is determined to be functional failure, the efficacy level is grade 4, which is considered poor.

[0086] Specifically, the design of the four-level efficacy gradation follows the logic of "stratified progression, with the weakest link determining the lower limit." The intensity of early response, the extent of short-term efficacy, and the level of long-term outcome jointly determine the final grade. The specific mapping logic is as follows: Level 1 (Excellent Efficacy): Clear early response, completely stable short-term efficacy, and complete functional recovery in the long term. All three levels meet the highest standards, representing rapid treatment response, good effect, and thorough recovery. It is the optimal efficacy state.

[0087] Level 2 (Good Efficacy): This category includes two combinations. One combination shows a clear early response and complete short-term efficacy, but only partial functional recovery. The other combination shows a questionable early response but complete short-term efficacy and complete functional recovery. Both categories indicate good overall efficacy but have minor deficiencies at a certain level, and are still considered to fall within the category of good efficacy overall.

[0088] Level 3 (Moderate Efficacy): This category includes two combinations. One combination shows a clear early response but only partial short-term efficacy and functional remission. The other combination shows a questionable early response and only partial short-term efficacy and functional remission. Both combinations demonstrate a clear therapeutic effect, but the extent of improvement and recovery is limited, thus representing moderate efficacy.

[0089] Level 4 (Poor Efficacy): Any situation of no early response, ineffective short-term treatment, or failure to restore function is classified as the worst level, indicating that the treatment has not produced effective benefits and the treatment plan needs to be adjusted in time.

[0090] The core design principle of this mapping rule is that any serious deficiency in any link will directly lower the final efficacy level. In particular, the three negative results of no response, ineffectiveness, and no recovery will directly trigger the worst level, ensuring the clinical warning value of the evaluation results.

[0091] Understandably, the four-level classification is clear and intuitive, allowing patients to quickly understand the level of efficacy without professional interpretation. It is suitable for various scenarios, such as rapid diagnosis and treatment by clinicians and self-assessment by patients. At the same time, the level settings are directly linked to clinical decision-making. Level 1 may recommend stopping medication and continuing home rest, Level 2 may maintain the existing treatment plan for consolidation, Level 3 may require adjustment of the symptomatic treatment plan to strengthen supportive treatment, and Level 4 requires immediate follow-up and adjustment of the antiviral plan. It is highly practical in clinical practice and can directly assist in clinical diagnosis and treatment decisions.

[0092] In some specific embodiments of the present invention, the present invention also provides a method for evaluating respiratory syncytial virus (RSV) treatment based on activity data, comprising the following steps: Continuously collect multi-dimensional daily activity data from patients, and simultaneously divide the data into a baseline period for establishing benchmarks, a treatment monitoring period for monitoring efficacy, and a follow-up period for assessing recovery levels. The collected activity data is validated to remove invalid data, then normalized in terms of dimensions, and then the baseline mean and baseline coefficient of variation of each activity dimension are calculated based on the valid data of the baseline period. Based on the baseline mean and baseline coefficient of variation of each activity dimension of the patients, three progressive thresholds were constructed: early response threshold, short-term efficacy threshold, and functional outcome threshold. The early treatment response assessment, short-term efficacy assessment, and functional outcome assessment are performed sequentially according to the time sequence. The results of the three assessments are then combined and mapped to output the evaluation results corresponding to the efficacy level.

[0093] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0094] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0095] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0096] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A respiratory syncytial virus (RSV) treatment evaluation system based on activity data, characterized in that, include: The information collection module is used to continuously collect multi-dimensional daily activity data of patients and simultaneously divide the data into a baseline period for establishing benchmarks, a treatment monitoring period for monitoring efficacy, and a follow-up period for assessing recovery levels. The data processing module is used to verify the validity of the activity data collected by the information collection module, remove invalid data, normalize the dimensions, and then calculate the baseline mean and baseline coefficient of variation of each activity dimension based on the valid data of the baseline period. The judgment and evaluation module is used to construct three progressive judgment thresholds—early response threshold, short-term efficacy threshold, and functional outcome threshold—based on the baseline mean and baseline coefficient of variation of each activity dimension of the patient obtained by the data processing module. Simultaneously, the early treatment response judgment, short-term efficacy judgment, and functional outcome judgment are executed sequentially according to the time sequence, and the three judgment results are combined and mapped to output the evaluation result corresponding to the efficacy level. The data storage module is used to store historical daily activity data collected by the information collection module, as well as early response thresholds, short-term efficacy thresholds, and functional outcome thresholds constructed by the judgment and evaluation module.

2. The respiratory syncytial virus treatment evaluation system based on activity data according to claim 1, characterized in that, The information collection module collects multi-dimensional daily activity data, including five dimensions: daily cumulative steps, daily moderate activity duration, daily cumulative rest duration, daily frequency of body position changes, and nighttime sleep fragmentation index. The information collection module is configured to divide the treatment into a baseline period for establishing a benchmark, a treatment monitoring period for monitoring efficacy, and a follow-up period for assessing recovery level. The baseline period is the 7 consecutive days before the start of treatment, the treatment monitoring period is from the start of treatment to the 14th day of treatment, and the follow-up period is the 7 consecutive days after the end of treatment.

3. The respiratory syncytial virus treatment evaluation system based on activity data according to claim 2, characterized in that, The data processing module is configured to: remove data with a valid collection duration of less than 20 hours on the same day as invalid data; then use the min-max normalization method to map the processed data of each dimension to the [0,1] interval; and then calculate the baseline mean and baseline coefficient of variation of each activity dimension based on the normalized data of each dimension.

4. The respiratory syncytial virus treatment evaluation system based on activity data according to claim 3, characterized in that, The judgment and evaluation module is configured as follows: The daily cumulative steps, daily moderate activity duration, and daily postural change frequency are used as positive indicators, while the daily cumulative resting time and nighttime sleep fragmentation index are used as negative indicators. Early response thresholds for each dimension of data were constructed. The coefficient of variation of 1.28 times the baseline corresponding to the 90% confidence interval of one side was used as the change magnitude threshold, which was then converted into a relative change rate threshold and used as the early response threshold. Construct short-term efficacy thresholds for data across various dimensions, including thresholds for the rate of improvement of positive indicators, the rate of decline of negative indicators, and stability thresholds; Construct functional regression thresholds for data in each dimension, including the first positive indicator recovery rate threshold, the second positive indicator recovery rate threshold, the first negative indicator decline rate threshold, the second negative indicator decline rate threshold, and the volatility consistency threshold.

5. The respiratory syncytial virus treatment evaluation system based on activity data according to claim 4, characterized in that, The judgment and evaluation module is further configured as follows: The observation window period from day 3 to day 7 of treatment was used to assess early treatment response. Calculate the rate of change of each activity indicator relative to the baseline on a daily basis, and count the number of qualified dimensions whose daily rate of change is greater than or equal to the early response threshold of the corresponding dimension. If the number of dimensions that meet the target is greater than or equal to 4 for two consecutive days, it is considered that an early treatment response has occurred; If the number of dimensions that meet the target criteria is less than 4 but greater than or equal to 2 for three consecutive days, it is considered a suspicious treatment response; If the criteria for early treatment response or suspected treatment response are not met by the 7th day of treatment, it is determined that there is no early treatment response, and the conclusion of short-term treatment ineffective is directly output.

6. The respiratory syncytial virus treatment evaluation system based on activity data according to claim 5, characterized in that, The judgment and evaluation module is also configured to perform short-term efficacy judgment after the early treatment response judgment is completed: When an early treatment response is determined to be present: The period from day 8 to day 14 of treatment was used as the observation window for short-term efficacy assessment. Calculate the mean and actual coefficient of variation for each dimension using valid data from the most recent three consecutive days. Then, calculate the rate of change of the mean for each dimension relative to the baseline to obtain the actual improvement rate of each positive indicator and the actual decline rate of each negative indicator. When the actual improvement rate of a positive indicator is greater than or equal to the threshold value, the indicator for that dimension is considered to have met the standard. Similarly, when the actual decline rate of a negative indicator is greater than or equal to the threshold value, the indicator for that dimension is considered to have met the standard. When all dimensional indicators meet the standards and the actual interval coefficient of variation is less than or equal to the stability threshold, the short-term treatment is deemed effective. When the number of dimensions that meet the standard is greater than or equal to 1 and less than or equal to 4, or when all 5 dimensions meet the standard but the actual interval coefficient of variation is greater than the stability threshold, the short-term treatment is deemed to be partially effective. If all five dimensions fail to meet the standards, the treatment is immediately deemed ineffective in the short term.

7. The respiratory syncytial virus treatment evaluation system based on activity data according to claim 6, characterized in that, The judgment and evaluation module is further configured to: when the early treatment response is judged as a suspicious treatment response, calculate the mean of each dimension and the actual interval coefficient of variation from the data of day 8 to day 10 of treatment to determine the short-term efficacy. Calculate the rate of change of the mean of each dimension relative to the baseline to obtain the actual improvement rate of each positive indicator and the actual decline rate of each negative indicator. When the actual improvement rate of a positive indicator is greater than or equal to the threshold value of the positive indicator improvement rate, the indicator for that dimension is deemed to have met the standard. When the actual decline rate of a negative indicator is greater than or equal to the threshold value of the negative indicator decline rate, the indicator for that dimension is deemed to have met the standard. When all dimensional indicators meet the standards and the actual interval coefficient of variation is less than or equal to the stability threshold, the short-term treatment is deemed effective. If not all dimensional indicators meet the standards, or if the actual interval coefficient of variation is greater than the stability threshold, the treatment is deemed ineffective in the short term.

8. The respiratory syncytial virus treatment evaluation system based on activity data according to claim 7, characterized in that, The judgment and evaluation module is also configured to: take the effective data from the last 3 days of the follow-up period, calculate the mean and actual interval coefficient of variation of each dimension, obtain the actual recovery rate of each positive indicator and the actual decline rate of each negative indicator, and then perform a functional reversion judgment: If the short-term efficacy is determined to be effective, the functional outcome is determined as follows: When the actual recovery rate of all positive indicators is greater than or equal to the first positive indicator recovery rate threshold, the actual decline rate of all negative indicators is less than or equal to the first negative indicator decline rate threshold, and the absolute value of the difference between the actual interval coefficient of variation and the baseline coefficient of variation is less than or equal to the fluctuation consistency threshold, it is determined that the function has completely reverted. When the actual recovery rate of all positive indicators is less than the second positive indicator recovery rate threshold, and the actual decline rate of all negative indicators is greater than the second negative indicator decline rate threshold, the function is judged to be not recovered. If neither the criteria for complete functional reversion nor the criteria for functional non-reversion are met, it is determined to be a partial functional reversion. If the short-term efficacy is determined to be partially effective after short-term treatment, the functional outcome is determined as follows: When the recovery rate of all positive indicators is less than the second positive indicator recovery rate threshold, and the actual decline rate of all negative indicators is greater than the second negative indicator decline rate threshold, it is determined that the function has not been restored; otherwise, it is determined that the function has partially reverted.

9. The respiratory syncytial virus treatment evaluation system based on activity data according to claim 8, characterized in that, The judgment and evaluation module is further configured to: combine and map the three-level judgment results, and output the evaluation result corresponding to the therapeutic effect level: When an early treatment response is determined to be an early treatment response, a short-term efficacy is determined to be a short-term treatment effect, and a functional outcome is determined to be a complete functional outcome, the efficacy level is Grade 1, which is excellent. When the early treatment response is determined to be an early treatment response, the short-term efficacy is determined to be effective in short-term treatment, and the functional outcome is determined to be partial functional outcome, or when the early treatment response is determined to be a suspicious treatment response, the short-term efficacy is determined to be effective in short-term treatment, and the functional outcome is determined to be complete functional outcome, the efficacy level is Grade 2, which is good. When an early treatment response is determined to be an early treatment response, a short-term efficacy is determined to be partially effective, and a functional outcome is determined to be partially functional, or when an early treatment response is determined to be a questionable treatment response, a short-term efficacy is determined to be effective, and a functional outcome is determined to be partially functional, the efficacy level is grade 3, moderate efficacy. When the early treatment response is determined to be non-responsive, or when the short-term efficacy is determined to be ineffective, or when the functional outcome is determined to be functional failure, the efficacy level is grade 4, which is considered poor.

10. A method for evaluating respiratory syncytial virus (RSV) treatment based on activity data, characterized in that, A respiratory syncytial virus (RSV) treatment evaluation system based on activity data as described in any one of claims 1-9, comprising the following steps: Continuously collect multi-dimensional daily activity data from patients, and simultaneously divide the data into a baseline period for establishing benchmarks, a treatment monitoring period for monitoring efficacy, and a follow-up period for assessing recovery levels. The collected activity data is validated to remove invalid data, then normalized in terms of dimensions, and then the baseline mean and baseline coefficient of variation of each activity dimension are calculated based on the valid data of the baseline period. Based on the baseline mean and baseline coefficient of variation of each activity dimension of the patients, three progressive thresholds were constructed: early response threshold, short-term efficacy threshold, and functional outcome threshold. The early treatment response assessment, short-term efficacy assessment, and functional outcome assessment are performed sequentially according to the time sequence. The results of the three assessments are then combined and mapped to output the evaluation results corresponding to the efficacy level.

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