Related Experiment Video
Updated: Nov 9, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
Published on: July 22, 2025
Patients' and Clinicians' Visions of a Future Internet-of-Things System to Support Asthma Self-Management: Mixed
Chi Yan Hui1, Brian McKinstry1, Olivia Fulton1
1Asthma UK Centre for Applied Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom.
Background:
Supported self-management for asthma reduces acute attacks and improves control. The internet of things could connect patients to health care providers, community services, and their living environments to provide overarching support for self-management.
Objective:
We aimed to identify patients' and clinicians' preferences for a future internet-of-things system and explore their visions of its potential to support holistic self-management.
Methods:
In an exploratory sequential mixed methods study, we recruited patients from volunteer databases and charities' social media. We purposively sampled participants to interview them about their vision of the design and utility of the internet of things as a future strategy for supporting self-management. Respondents who were not invited to participate in the interviews were invited to complete a web-based questionnaire to prioritize the features suggested by the interviewees. Clinicians were recruited from professional networks. Interviews were transcribed and analyzed thematically using PRISMS self-management taxonomy.
Results:
We interviewed 12 patients and 12 clinicians in the United Kingdom, and 140 patients completed the web-based questionnaires. Patients expressed mostly wanting a system to log their asthma control status automatically; provide real-time advice to help them learn about their asthma, identify and avoid triggers, and adjust their treatment. Peak flow (33/140, 23.6%), environmental (pollen, humidity, air temperature) (33/140, 23.6%), and asthma symptoms (25/140, 17.9%) were the specific data types that patient most wanted. Information about asthma and text or email access to clinical advice provided a feeling of safety for patients. Clinicians wanted automated objective data about the patients' condition that they could access during consultations. The potential reduction in face-to-face consultations was appreciated by clinicians which they perceived could potentially save patients' travel time and health service resources. Lifestyle logs of fitness regimes or weight control were valued by some patients but were of less interest to clinicians.
Conclusions:
An automated internet-of-things system that requires minimal input from the user and provides timely advice in line with an asthma action plan agreed by the patient with their clinician was preferred by most respondents. Links to asthma information and the ability to connect with clinicians by text or email were perceived by patients as features that would provide a sense of safety. Further studies are needed to evaluate the usability and effectiveness of internet-of-things systems in routine clinical practice.
Related Concept Videos
Asthma-IV: Nursing Management
First, in...
Asthma-IV: Diagnostic and Management
Clinical Assessment for Asthma:
This is the first step in diagnosing and managing asthma. It includes:
Asthma: Pathogenesis and Management
Asthma is classified as allergic and non-allergic. Allergens such as dust mites, pollen, and pet dander trigger allergic asthma, while factors like cold air, intense emotions, or exercise can induce non-allergic asthma.
Asthma-I: Introduction
Asthma-II: Pathophysiology and Classification
Additionally, environmental and genetic factors play crucial roles in determining an individual's susceptibility to asthma and the severity of their condition.
Critical processes in asthma pathophysiology include:
Asthma-III: Symptoms and Complications
Classification of Asthma

