CN-121983211-A - Alcohol use disorder rehabilitation data processing system and method

CN121983211ACN 121983211 ACN121983211 ACN 121983211ACN-121983211-A

Abstract

The invention relates to the technical field of medical information processing and health behavior intervention, and discloses an alcohol use disorder rehabilitation data processing system and method. The system deploys a physiological monitoring terminal, introduces heart rate variability, skin conductance and skin temperature in a resting state, performs double-point calibration to obtain an individual baseline, enters a high-risk point, establishes a fence, judges whether the individual baseline enters or exits according to a spherical distance, collects three parameters regularly, normalizes according to medical upper and lower limits, judges that a channel can deviate from a sample effectively and calculated in real time, gathers according to natural days to generate a next-day individuation threshold, triggers risks when entering the fence and deviating from the threshold, calculates intensity and carries out four-level classification, carries out micro-intervention and recording according to the grades, retests a fixed window after the intervention to obtain deviation and improvement and gathers, counts the trigger and the risks according to seven days, and gathers the deviation and daily improvement to generate a training duration and period report.

Inventors

TIAN LU
CHI YONG
HOU WEIWEI
XING XIAOMENG
YU HAITING
QI NA
JIA SHENGTAO
ZHOU DANNA
WANG CHUN

Assignees

首都医科大学附属北京安定医院

Dates

Publication Date: 20260505
Application Date: 20260123

Claims (10)

1. A rehabilitation training method for alcohol use disorder, comprising: A physiological monitoring terminal is deployed, baseline stabilization acquisition is executed, three physiological quantities of heart rate variability, skin conductance and skin temperature are imported, and two-point linear calibration and baseline average calculation are completed; Recording high-risk points, generating high-risk fences according to preset fence radiuses, calculating spherical distances between the current position and each high-risk point according to the spherical distances, and giving out in-out judgment; Three types of physiological quantities are imported according to fixed time intervals, normalization is performed based on medical upper and lower limits, channel availability and sample effectiveness are established, and real-time deviation is obtained; summarizing the effective samples according to the natural days, calculating an individuation threshold value at fixed time and executing the individuation threshold value on the next day; Triggering risk judgment when the high-risk fence is entered and the real-time deviation exceeds a threshold value, generating risk intensity and classifying the risk intensity into four stages; generating micro-intervention actions according to the risk level and recording events; Three types of physiological quantities are imported again in a preset dry prognosis observation time window, deviation degree and physiological improvement amplitude after intervention are obtained, and improvement summary on the same day is completed; And counting the triggering and risk intensity by taking seven days as a period, deviating and improving the aggregation days, generating the training duration of the next period and generating a period report.
2. The rehabilitation training method for alcohol use disorder according to claim 1, wherein the deployment of the physiological monitoring terminal and the execution of baseline stabilization acquisition, the introduction of three physiological quantities of heart rate variability, skin conductance and skin temperature, the completion of two-point linear calibration and baseline average calculation, specifically comprise: establishing numbers for people with alcohol use disorder; Wearing a multi-parameter physiological sensing module on the wrist, wherein the multi-parameter physiological sensing module comprises heart rate variability sensing, skin electric conduction sensing and skin temperature sensing; setting the sampling frequency to be once per second, setting the sampling time to be six hundred seconds, and keeping the rest, the eye closing and the sitting posture stable during the sampling; respectively executing two-point linear calibration on the three types of sensors, checking that the voltage difference between the two points is not zero, and reselecting the unqualified calibration point; And acquiring a baseline average value of heart rate variability, skin conductance and skin temperature according to discrete average after sampling.
3. The rehabilitation training method for alcohol use disorder according to claim 2, wherein the recording of the high risk points, the generation of the high risk fence according to the preset fence radius, the calculation of the spherical distance between the current position and each high risk point according to the spherical distance, and the giving of the in-out judgment, specifically comprise: Inputting longitude and latitude of a plurality of high-risk points by doctors; acquiring the current longitude and latitude and uniformly converting the angle into radian; calculating the spherical distance from the current position to each high-risk point according to a spherical cosine method; Comparison with corresponding fence radius generating a decision whether to enter; The corresponding time is marked invalid when the location is missing.
4. The rehabilitation training method for alcohol use disorder according to claim 3, wherein three types of physiological quantities are introduced at fixed time intervals, normalization is performed based on medical upper and lower limits, channel availability and sample availability are established, and real-time deviation is obtained, specifically comprising: Heart rate variability, skin conductance and skin temperature data were imported every five minutes; linearly normalizing the three physiological quantities to a zero-to-one interval according to respective medical lower and upper limits; generating a channel availability and sample validity indication; taking the normalized individual base line as a reference, and acquiring the real-time deviation degree of each moment; only valid samples are stored in the local cache.
5. The alcohol use disorder rehabilitation training method according to claim 4, wherein the step of summarizing the valid samples on a natural day, calculating the individualization threshold at a fixed time and performing on the next day comprises: establishing a natural day index and a current day plan sampling time set; averaging the real-time deviation of the current day valid sample at twenty-two times daily; generating an individuation threshold according to a mixed relation of linearity and proportion; The individualization threshold is employed for all decisions on the next day.
6. The alcohol use disorder rehabilitation training method according to claim 5, wherein the risk determination is triggered when the high-risk fence is entered and the real-time deviation exceeds a threshold value, and the risk intensity is generated and classified into four classes, specifically comprising: generating a fence union indication upon entry into any high risk fence; triggering risks when the high-risk fence is entered and the real-time deviation exceeds an individuation threshold; Generating risk intensity according to deviation degree and threshold value difference and combining fence union indication; the current grade is recorded according to the four grades of safety, light danger, medium danger and heavy danger.
7. The alcohol use disorder rehabilitation training method according to claim 6, wherein the generating micro-intervention actions and recording events according to risk levels, specifically comprises: generating a data packet containing the personnel number of the alcohol use obstacle, the triggering time, the risk level, the current position and the real-time deviation degree when triggering; Pushing a departure prompt when the danger is light; the window is flicked and vibrated for twenty seconds at medium risk, and rhythmic breathing guidance is played at the same time; When the danger is serious, locking the screen and playing a three-minute calm audio; the intervention event is recorded and written into a database, including the execution identification.
8. The rehabilitation training method for alcohol use disorder according to claim 7, wherein three types of physiological quantities are introduced again in a preset stem prognosis observation time window, deviation degree and physiological improvement amplitude after intervention are obtained, and improvement summary on the same day is completed, and the rehabilitation training method specifically comprises the following steps: after the observation time window is finished after the preset intervention, three types of physiological quantities are imported again; the duration of the observation time window after the preset intervention is one thousand and two hundred seconds; normalization is completed according to the upper and lower medical limits, and the deviation degree of the dry prognosis is obtained; calculating physiological improvement amplitude when all three channels are effective; The effective improvement count on the day is counted and the average improvement amplitude on the day is calculated.
9. The rehabilitation training method for alcohol use disorder according to claim 8, wherein the statistics of trigger and risk intensity with seven days as a period, the deviation and improvement of aggregation days, the generation of the next period training duration and the generation of the period report, specifically comprise: Establishing a plurality of latest natural day sets by taking seven days as a period; summarizing all trigger moments in the period and calculating average risk intensity; Mapping the average risk intensity into the training duration of the next period of the third gear; aggregating day-to-day deviations and day improvement for the last several days; updating the training program and generating a periodic report containing the aggregate index, the average risk intensity and the next periodic training period.
10. A system employing the alcohol use disorder personnel rehabilitation training method of claim 9, comprising: The mobile client is used for receiving the trigger, pushing the prompt, executing vibration, playing audio and displaying the guide interface; the positioning module is used for acquiring longitude and latitude and providing space judgment input; The server and the database are used for executing acquisition management, baseline calculation, normalization processing, threshold generation, risk classification, intervention arrangement, evaluation after intervention and period induction and record storage; and the doctor management end is used for inputting high-risk fence parameters and checking periodic reports.

Description

Alcohol use disorder rehabilitation data processing system and method Technical Field The invention relates to the technical field of medical information processing and health behavior intervention, in particular to a system and a method for processing alcohol use disorder rehabilitation data. Background Wine is used as a unique drink, has long history in the development process of human beings and has profound effects. China is one of the earliest brewing countries in the world, has drinking custom since ancient times, and has important roles in life, work, social activities and other activities of people until today. However, alcohol is an addictive substance that has long been recognized, and statistics of World Health Organization (WHO) show that over 20 million drinkers worldwide, of which 7630 ten thousand can be diagnosed as an obstacle caused by alcohol use, whereas harmful use of alcohol results in more than 5% of global disease burden [1], and alcohol abuse and alcohol dependence have caused serious social and medical problems. Currently, rehabilitation for alcohol use impaired rehabilitation people mainly depends on regular outpatient follow-up, drug assisted treatment, traditional psychological consultation and partial behavioral intervention courses. However, the real-time identification and personalized intervention on high-risk space-time behaviors of patients are difficult to realize by purely relying on off-line follow-up and empirical intervention due to objective factors such as long rehabilitation period, poor compliance, high behavior repeatability and the like. In the prior art, part of intelligent wearable equipment (such as a bracelet, a watch and the like) can realize basic physiological signal acquisition (such as heart rate, galvanic skin response, exercise step number and the like), but has limited data processing and risk identification capacity, can only provide simple behavior reminding, basic exercise statistics or abnormal heart rate alarming, and cannot effectively identify and classify special behavior risk scenes of alcohol use obstacle personnel. On the other hand, part of APP carries out rehabilitation supervision through self-filling questionnaires, punching cards, signing in and other modes, but due to the lack of real-time and multidimensional physiological and environmental information, high-risk behavior modes of patients under specific situations are difficult to dynamically capture and analyze, and intervention measures cannot be automatically adjusted according to individual states. In the aspect of space behavior management, the existing geofence technology is mainly applied to few scenes such as child safety, old people lost protection and the like, the core of the geofence technology depends on a static coordinate or regional alarm mechanism, and comprehensive discrimination on behavior data, environmental factors and physiological states is lacking. The existing method is difficult to carry out dynamic threshold adjustment and personalized feedback according to the mood fluctuation, physiological stress or abnormal behavior of alcohol use disorder people in a specific environment. In addition, risk determination based on a static preset threshold cannot adapt to the difference and rehabilitation progress of different individuals, and misinformation, missing report or excessive intervention can be caused, so that the experience and the intervention effect of a patient are affected. In addition, the traditional rehabilitation management system relies on manual analysis and experience judgment, lacks systematic algorithm models and objective data fusion, and is difficult to meet the requirements of large-scale, remote and continuous health management. For the actual alcohol use obstacle rehabilitation scene, a digital rehabilitation intervention system integrating physiological signal real-time monitoring, geographic behavior recognition, self-adaptive threshold judgment and automatic micro-intervention suggestion is not available. The scheme aims to provide an alcohol use obstacle rehabilitation data processing system and method, wherein the real-time acquisition of multi-parameter physiological quantity and personalized baseline calibration are combined with high-risk environment recognition based on a geofence to carry out multi-stage judgment on risks deviating from the physiological baseline, targeted micro-intervention is pushed according to the risk level, the intervention effect is estimated again, and finally the subsequent training intensity and duration are determined through periodical statistical analysis to realize a dynamic, accurate and traceable rehabilitation closed loop. Disclosure of Invention The invention provides a system and a method for processing alcohol use disorder rehabilitation data, which are used for promoting to solve the problems in the background technology. It is emphasized in particular that the present invention is essentia