Socially assistive robot-based alerts on indoor and outdoor air-quality for patients with chronic obstructive pulmonary disease.

Purpose Socially assistive robots (SARs) are utilized to help older adults requiring cognitive support such as affective therapy, cognitive training, and social-skill enhancement (Feil-Seifer & Mataric., 2005). In addition, the SAR has advantages in providing home-based healthcare services since it can become intimate with its users, allow verbal and non-verbal interactions, and enable timely monitoring (Abdi, Al-Hindawi, Ng & Vizcaychipi, 2018). Meanwhile, poor IAQ (Indoor air quality) can adversely affect health and thus require IAQ management (WHO, 2010). The elderly with chronic obstructive pulmonary disease (COPD) spends more time indoors, so they are affected by the indoor air quality (IAQ) and require the management of IAQ. Therefore, we developed a SAR platform by networking the IAQ sensor, weather open API, conversation engine, and SAR to provide air quality alerts and support patients in activities that can improve or maintain IAQ. We evaluated whether the ability to management of older adults is improved through IAQ alerts. Additionally, we provided personalized instructions on inhaler usage and confirmed whether clinical indicators were improved. Method We conducted an unblinded, single group, observational pilot test and assessed the feasibility of the IoT-based SAR system. Sixteen patients with COPD (n=l6) participated in the study. The pilot study persisted for 16 weeks. For 8 weeks in the first phase, participants utilized a SAR with an IAQ sensor. During the 8 weeks of the second phase, voice message alerts concerning inhaler use were plated by SAR. Results and Discussion Results from machine learning indicate that the SAR platform can assist older adults to control IAQ by giving alerts. And, the alerts may improve the capability of older adults to maintain IAQ. In addition, after receiving the instructions on inhaler use, adherence to inhaler usage (TAI) was significantly improved (z=-1.98, P=0.048), and the breathlessness scale was significantly decreased (z=-2112, P=0.035). The results present empirical evidence that SAR integrated with environmental alarm systems is helpful in the behavioral change of the patients. We do believe that our findings could provide a basis for systems integrating SAR and IoT in healthcare fields. [ABSTRACT FROM AUTHOR]