Monitoring Respiratory Health in Children With Acute Asthma Using Wearable Electrical Bioimpedance and Breath Sounds: Observational Case-Control Study
Notice bibliographique
Résumé
BACKGROUND: Asthma remains one of the most serious chronic diseases of childhood. Individuals with severe asthma experience sudden episodes of breathlessness due to acute airflow obstruction, leading to recurrent pediatric intensive care unit (PICU) admissions that often result in mechanical ventilation and even death. Existing clinical assessments lack temporal resolution to effectively track the rapidly changing physiology. OBJECTIVE: This study aimed to evaluate the feasibility of quantifying respiratory health during acute asthma in children using wearable multimodal sensing. METHODS: Wearable-based impedance pneumography (IP) and multichannel lung sounds (LSs) were measured on 17 children admitted to the PICU with an acute asthma attack and on 9 healthy controls. Short-term multimodal measurements were obtained throughout hospitalization, specifically at PICU admission (T1) and discharge (T2). Measurements were also obtained from controls without any signs of acute asthma or otherwise healthy. Statistical and clustering analyses were performed to identify trends in IP- and LS-derived respiratory markers from T1 to T2 across all patients with paired time points (n=13), as well as across the matched cohort (T1: n=10 and T2: n=7), who were compared against controls (n=9). Five features were computed from the IP signal: respiratory rate, inspiration time (Ti), expiration time (Te), expiration-to-inspiration time ratio (Te:Ti), and the normalized Ti by interbreath interval (Ti/IBI). Leveraging the breathing context provided by the IP signal, 4 spectral integrated intensity (SI) acoustic features were computed in 4 different subbands for the inspiration and expiration phases. RESULTS: Within the patient group (n=13), we found that respiratory rate decreased (W(12)=79; P=.02), whereas Te (W(12)=12; P=.02) and Ti (W(12)=13; P=.02) lengthened. Meanwhile, the SIs for the lowest subband (100-300 Hz) decreased for both inspiration and expiration phases (P<.01), while they increased for the highest subband (800-1000 Hz) for both inspiration and expiration phases (P<.01). Significant differences also existed between T1 and control and T2 and control of the matched cohort. We found that all features were significantly different between T1 and control (P<.05), and all SIs together with Te:Ti and Ti/IBI were significantly different between T2 and control (P<.05), all exhibiting trends toward normalcy. CONCLUSIONS: These results demonstrate the feasibility of quantifying and tracking respiratory health in children with acute asthma using wearable multimodal sensing, specifically with the fusion of IP- and LS-derived markers. Such technology may provide a new adjunctive clinical tool for real-time respiratory monitoring and enable timely titration of care, thereby improving patient outcomes.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».