Research on the Early Warning Model of Children Asthma Acute Attack Based on Wearable Wrist Smart Device of Huami

Recruiting

• Conditions: Asthma in Children

• Registration Number: NCT05243667
• Lead Sponsor: Guangzhou Institute of Respiratory Disease

Brief Summary

Childhood asthma is the most common chronic respiratory disease in childhood. The essence of asthma is chronic airway inflammation and airway hyperresponsiveness.The physiological characteristics of children and adults are very different, and the compensatory ability is very strong. There are often no obvious symptoms at the early stage of attack, or only intermittent or persistent cough of different degrees, without typical chest tightness and asthma.However, at this time, certain physiological indicators such as blood oxygen, heart rate, respiratory rate may have been significantly abnormal.If the disease continues to deteriorate and progresses to decompensation, it can quickly move from an asymptomatic state to a failure stage.Therefore, dynamic and accurate acquisition of real-time vital signs and assessment is of great significance for early warning and improvement of prognosis of asthma attacks in children.Intelligent wearable devices can be used to acquire real-time physiological index data of users, such as heart rate, blood oxygen, exercise and sleep dynamic data.An in-depth analysis of long-term and multi-scene dynamic data before and after asthma attacks can establish an early warning model for children with acute asthma attacks by wearable wrist smart devices, which may provide important help for severity assessment, follow-up tracking and out-of-hospital prevention and control of the disease.

Detailed Description

this project is selected 200 cases of children with asthma diagnosis definitely, collection and heart rate, blood oxygen, exercise and sleep dynamic data, followed up for 3 to 6 months (at least 3 months), records of clinical asthma attacks and clinical data, through the cloud data analysis and deep learning, analysis of children with asthma attacks and multiple physiological parameters (heart rate, blood oxygen, movement and the dynamic data of sleep, etc.), the connection between the building of asthma early warning and illness severity hierarchical evaluation model.Then choose 200 cases of diagnosis in clinical practice to determine follow-up, patients with asthma children to observe to verify the exactness of the model of asthma attack early warning, and according to the collected data to further improve, calibration model, designed to provide children with family members and medical personnel of an asthma attack warning and follow-up management wearable auxiliary equipment and management platform.

Study Timeline

• Study Start: 2021-06-01
• Study First Submitted: 2021-08-15
• Status Verified: 2022-02
• Study First Submitted QC: 2022-02-07
• Last Update Submitted: 2022-02-07
• Study First Posted: 2022-02-17
• Last Update Posted: 2022-02-17
• Primary Completion: 2024-12-30
• Study Completion: 2024-12-30

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 200

Inclusion Criteria

Clinical diagnosis of asthma.

Exclusion Criteria

Severe chronic diseases with organ dysfunction and dyspnea.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Heart rate	up to 24 weeks	Follow-up monitoring of confirmed asthma patients was conducted based on intelligent wearable devices, and multiple physiological parameters such as heart rate were collected in the pre-attack, attack and remission stages
blood oxygen	up to 24 weeks	Follow-up monitoring of confirmed asthma patients was conducted based on intelligent wearable devices, and blood oxygen were collected in the pre-attack, attack and remission stages
exercise	up to 24 weeks	Follow-up monitoring of confirmed asthma patients was conducted based on intelligent wearable devices, and exercise were collected in the pre-attack, attack and remission stages
sleep	up to 24 weeks	Follow-up monitoring of confirmed asthma patients was conducted based on intelligent wearable devices, and sleep were collected in the pre-attack, attack and remission stages

Secondary Outcome Measures

Name	Time	Method
weight	up to 24 weeks	Weight of enrolled asthmatic patients
height	up to 24 weeks	Height of enrolled asthmatic patients

Trial Locations

Locations (1)

Guangzhou institute of respiratory disease; 🇨🇳 Guangzhou, Guangdong, China