Designing a Socially Assistive Robot to Assist Older Patients with Chronic Obstructive Pulmonary Disease in Managing Indoor Air Quality
Source abstract
Abstract
Chronic obstructive pulmonary disease (COPD) stems from airflow blockage and lung damage, and indoor air pollution exacerbates COPD, underscoring the necessity for proactive management. Older COPD patients, prone to respiratory and heat-related issues, require crucial assistance, yet their reduced awareness necessitates ongoing education to identify and enhance indoor air quality. To tackle this challenge, we developed a socially assistive robot (SAR) integrating IoT air quality sensors to guide patients in improving indoor air quality (IAQ). This study evaluated IAQ enhancement among older COPD patients using this technology, uncovering a significant reduction in ‘poor air quality alerts’ with a clear linear trend. Although ‘good alerts’ remained consistent, machine learning models predicted improved air quality post-alerts. Consistent alerts serve as a motivating factor for patients to maintain IAQ standards. However, barriers to SAR utilization, such as psychological and operational hurdles, need to be addressed in future research endeavors.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Chronic Obstructive Pulmonary Disease (COPD) Research · Respiratory Support and Mechanisms · Air Quality and Health Impacts
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Health Policy and Management, Kangwon National University School of Medicine, Chuncheon-si 24341, Gangwon, Republic of Korea
School of Social Work, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon-si 24341, Gangwon, Republic of Korea
Funding
National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)
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